%PDF-1.3 1 0 obj << /Type /Catalog /Outlines 2 0 R /Pages 3 0 R >> endobj 2 0 obj << /Type /Outlines /Count 0 >> endobj 3 0 obj << /Type /Pages /Kids [6 0 R 158 0 R 196 0 R 264 0 R 306 0 R 327 0 R 335 0 R ] /Count 7 /Resources << /ProcSet 4 0 R /Font << /F1 8 0 R /F2 9 0 R /F3 10 0 R /F4 11 0 R >> /XObject << /I1 12 0 R /I2 13 0 R /I3 198 0 R /I4 199 0 R /I5 200 0 R /I6 201 0 R /I7 202 0 R /I8 203 0 R /I9 204 0 R /I10 205 0 R /I11 206 0 R /I12 207 0 R /I13 208 0 R /I14 209 0 R /I15 210 0 R /I16 211 0 R /I17 220 0 R /I18 221 0 R /I19 222 0 R /I20 223 0 R /I21 224 0 R /I22 225 0 R /I23 226 0 R /I24 227 0 R /I25 228 0 R /I26 229 0 R /I27 230 0 R /I28 231 0 R /I29 232 0 R /I30 233 0 R /I31 242 0 R /I32 243 0 R /I33 244 0 R /I34 245 0 R /I35 246 0 R /I36 247 0 R /I37 248 0 R /I38 249 0 R /I39 250 0 R /I40 251 0 R /I41 252 0 R /I42 253 0 R /I43 254 0 R /I44 255 0 R /I45 268 0 R /I46 271 0 R /I47 272 0 R /I48 275 0 R /I49 284 0 R /I50 285 0 R /I51 296 0 R /I52 297 0 R /I53 304 0 R /I54 305 0 R /I55 312 0 R >> >> /MediaBox [0.000 0.000 612.000 792.000] >> endobj 4 0 obj [/PDF /Text /ImageC ] endobj 5 0 obj << /Creator (DOMPDF) /CreationDate (D:20180721162652+00'00') /ModDate (D:20180721162652+00'00') /Title (Stability of white matter changes related to Huntingtons disease in the presence of imaging noise: a DTI study PLOS Currents Huntington Disease) >> endobj 6 0 obj << /Type /Page /Parent 3 0 R /Annots [ 14 0 R 16 0 R 18 0 R 20 0 R 22 0 R 24 0 R 26 0 R 28 0 R 30 0 R 32 0 R 34 0 R 36 0 R 38 0 R 40 0 R 42 0 R 44 0 R 46 0 R 48 0 R 50 0 R 52 0 R 54 0 R 56 0 R 58 0 R 60 0 R 62 0 R 64 0 R 66 0 R 68 0 R 70 0 R 72 0 R 74 0 R 76 0 R 78 0 R 80 0 R 82 0 R 84 0 R 86 0 R 88 0 R 90 0 R 92 0 R 94 0 R 96 0 R 98 0 R 100 0 R 102 0 R 104 0 R 106 0 R 108 0 R 110 0 R 112 0 R 114 0 R 116 0 R 118 0 R 120 0 R 122 0 R 124 0 R 126 0 R 128 0 R 130 0 R 132 0 R 134 0 R 136 0 R 138 0 R 140 0 R 142 0 R 144 0 R 146 0 R 148 0 R 150 0 R 152 0 R 154 0 R 156 0 R ] /Contents 7 0 R >> endobj 7 0 obj << /Length 29846 >> stream q 375.000 0 0 39.000 222.000 738.000 cm /I2 Do Q q 15.000 684.354 577.500 53.646 re W n 0.267 0.267 0.267 rg BT 15.000 718.042 Td /F2 21.0 Tf [(Stability of white matter changes related to Huntingtons )] TJ ET BT 15.000 693.094 Td /F2 21.0 Tf [(disease in the presence of imaging noise: a DTI study)] TJ ET Q 0.271 0.267 0.267 rg BT 15.000 675.088 Td /F3 9.8 Tf [(June 7, 2011)] TJ ET BT 69.971 675.088 Td /F3 9.8 Tf [()] TJ ET 0.267 0.267 0.267 rg BT 74.846 675.088 Td /F3 9.8 Tf [(Biomarkers)] TJ ET BT 26.250 663.247 Td /F1 9.8 Tf [(Hans-Peter Mller)] TJ ET 0.271 0.267 0.267 rg BT 104.806 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 110.227 663.247 Td /F1 9.8 Tf [(Volkmar Glauche)] TJ ET 0.271 0.267 0.267 rg BT 185.000 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 190.421 663.247 Td /F1 9.8 Tf [(Marianne Novak)] TJ ET 0.271 0.267 0.267 rg BT 261.401 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 266.822 663.247 Td /F1 9.8 Tf [(Thao Nguyen-Thanh)] TJ ET 0.271 0.267 0.267 rg BT 356.239 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 361.660 663.247 Td /F1 9.8 Tf [(Alexander Unrath)] TJ ET 0.271 0.267 0.267 rg BT 437.524 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 442.945 663.247 Td /F1 9.8 Tf [(Nayana Lahiri Swales)] TJ ET 0.271 0.267 0.267 rg BT 537.228 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 542.649 663.247 Td /F1 9.8 Tf [(Joy )] TJ ET BT 26.250 651.342 Td /F1 9.8 Tf [(Read)] TJ ET 0.271 0.267 0.267 rg BT 49.552 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 54.974 651.342 Td /F1 9.8 Tf [(Miranda Julia Say)] TJ ET 0.271 0.267 0.267 rg BT 132.457 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 137.878 651.342 Td /F1 9.8 Tf [(Sarah J Tabrizi)] TJ ET 0.271 0.267 0.267 rg BT 203.437 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 208.858 651.342 Td /F1 9.8 Tf [(Jan Kassubek)] TJ ET 0.271 0.267 0.267 rg BT 270.098 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 275.519 651.342 Td /F1 9.8 Tf [(Stefan Kloppel)] TJ ET 0.271 0.267 0.267 rg BT 26.250 639.438 Td /F1 9.8 Tf [(Mller H, Glauche V, Novak M, Nguyen-Thanh T, Unrath A, Lahiri Swales N, Read J, Say MJ, Tabrizi SJ, Kassubek J, Kloppel )] TJ ET BT 26.250 627.533 Td /F1 9.8 Tf [(S. Stability of white matter changes related to Huntingtons disease in the presence of imaging noise: a DTI study. PLOS )] TJ ET BT 26.250 615.628 Td /F1 9.8 Tf [(Currents Huntington Disease. 2011 Jun 7 . Edition 1. doi: 10.1371/currents.RRN1232.)] TJ ET q 15.000 26.911 577.500 586.337 re W n 0.271 0.267 0.267 rg BT 26.250 586.526 Td /F4 12.0 Tf [(Abstract)] TJ ET BT 26.250 566.571 Td /F1 9.8 Tf [(Movement artifacts and other sources of noise are a matter of concern particularly in the neuroimaging research of movement )] TJ ET BT 26.250 554.667 Td /F1 9.8 Tf [(disorders such as Huntingtons disease \(HD\). Using diffusion weighted imaging \(DWI\) and fractional anisotropy \(FA\) as a )] TJ ET BT 26.250 542.762 Td /F1 9.8 Tf [(compound marker of white matter integrity, we investigated the effect of movement on HD specific changes in magnetic )] TJ ET BT 26.250 530.857 Td /F1 9.8 Tf [(resonance imaging \(MRI\) data and how post hoc compensation for it affects the MRI results. To this end, we studied by 3T MRI: )] TJ ET BT 26.250 518.952 Td /F1 9.8 Tf [(18 early affected, 22 premanifest gene-positive subjects, 23 healthy controls \(50 slices of 2.3 mm thickness per volume, 64 )] TJ ET BT 26.250 507.048 Td /F1 9.8 Tf [(diffusion-weighted directions \(b = 1000 s/mm2\), 8 minimal diffusion-weighting \(b = 100 s/mm2\)\); and by 1.5 T imaging: 29 )] TJ ET BT 26.250 495.143 Td /F1 9.8 Tf [(premanifest HD, 30 controls \(40 axial slices of 2.3 mm thickness per volume, 61 diffusion-weighted directions \(b = 1000 s/mm2\), )] TJ ET BT 26.250 483.238 Td /F1 9.8 Tf [(minimal diffusion-weighting \(b = 100 s/mm2\)\). An outlier based method was developed to identify movement and other sources )] TJ ET BT 26.250 471.333 Td /F1 9.8 Tf [(of noise by comparing the index DWI direction against a weighted average computed from all other directions of the same )] TJ ET BT 26.250 459.429 Td /F1 9.8 Tf [(subject. No significant differences were observed when separately comparing each group of patients with and without removal )] TJ ET BT 26.250 447.524 Td /F1 9.8 Tf [(of DWI volumes that contained artifacts. In line with previous DWI-based studies, decreased FA in the corpus callosum and )] TJ ET BT 26.250 435.619 Td /F1 9.8 Tf [(increased FA around the basal ganglia were observed when premanifest mutation carriers and early affected patients were )] TJ ET BT 26.250 423.714 Td /F1 9.8 Tf [(compared with healthy controls. These findings demonstrate the robustness of the FA value in the presence of movement and )] TJ ET BT 26.250 411.810 Td /F1 9.8 Tf [(thus encourage multi-center imaging studies in HD.)] TJ ET BT 26.250 375.207 Td /F4 12.0 Tf [(Funding Statement)] TJ ET BT 26.250 355.253 Td /F1 9.8 Tf [(This work was supported by the European HD network \(EHDN project 070\). MN is funded from a Wellcome Trust grant held by )] TJ ET BT 26.250 343.348 Td /F1 9.8 Tf [(ST \(075696/Z/04/Z\). The 3T MRI scans were acquired as part of the London site TRACK-HD cohort. TRACK-HD is supported )] TJ ET BT 26.250 331.443 Td /F1 9.8 Tf [(by the CHDI Foundation, a not for profit organization dedicated to finding treatments for HD. Some of this work was undertaken )] TJ ET BT 26.250 319.539 Td /F1 9.8 Tf [(at UCLH/UCL who acknowledge support from the respective Department of Healths NIHR Biomedical Research Centres.)] TJ ET BT 26.250 290.436 Td /F4 12.0 Tf [(Introduction)] TJ ET BT 26.250 270.482 Td /F1 9.8 Tf [(White matter \(WM\) changes in Huntingtons Disease \(HD\) have been shown in a number of studies \(see )] TJ ET 0.267 0.267 0.267 rg BT 478.163 270.482 Td /F1 9.8 Tf [([1])] TJ ET 0.271 0.267 0.267 rg BT 489.005 270.482 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 494.425 270.482 Td /F1 9.8 Tf [([2])] TJ ET 0.271 0.267 0.267 rg BT 505.267 270.482 Td /F1 9.8 Tf [( for reviews\) and )] TJ ET BT 26.250 258.577 Td /F1 9.8 Tf [(have mainly been studied using diffusion weighted imaging \(DWI\) and diffusion tensor imaging \(DTI\). DWI is based on the )] TJ ET BT 26.250 246.672 Td /F1 9.8 Tf [(diffusion of water which is influenced by local tissue properties, and DWI-sequences combine several gradient directions, each )] TJ ET BT 26.250 234.768 Td /F1 9.8 Tf [(of which codes the diffusion along its direction )] TJ ET 0.267 0.267 0.267 rg BT 227.305 234.768 Td /F1 9.8 Tf [([3])] TJ ET 0.271 0.267 0.267 rg BT 238.147 234.768 Td /F1 9.8 Tf [( so that DTI characterises the combination of diffusion directions in each voxel. )] TJ ET BT 26.250 222.863 Td /F1 9.8 Tf [(The tensor takes the form of a sphere when diffusion is equal in all directions and a cigar-like shape when a single diffusion )] TJ ET BT 26.250 210.958 Td /F1 9.8 Tf [(direction dominates. The shape information can be converted into compound measures such as fractional anisotropy \(FA\), a )] TJ ET BT 26.250 199.053 Td /F1 9.8 Tf [(dimensionless scalar ranging from zero \(in water\) to one, in order to compare groups and to correlate clinical markers with )] TJ ET BT 26.250 187.149 Td /F1 9.8 Tf [(imaging data. In the field of HD research, recent studies indicate that DTI can be useful to measure longitudinal change )] TJ ET 0.267 0.267 0.267 rg BT 542.171 187.149 Td /F1 9.8 Tf [([4])] TJ ET 0.271 0.267 0.267 rg BT 553.013 187.149 Td /F1 9.8 Tf [(, or to )] TJ ET BT 26.250 175.244 Td /F1 9.8 Tf [(detect early changes in the sensorimotor cortex in premanifest HD )] TJ ET 0.267 0.267 0.267 rg BT 314.528 175.244 Td /F1 9.8 Tf [([5])] TJ ET 0.271 0.267 0.267 rg BT 325.370 175.244 Td /F1 9.8 Tf [( so that DTI is an important tool to understand the )] TJ ET BT 26.250 163.339 Td /F1 9.8 Tf [(phenotypical variability seen in HD )] TJ ET 0.267 0.267 0.267 rg BT 177.970 163.339 Td /F1 9.8 Tf [([6])] TJ ET 0.271 0.267 0.267 rg BT 188.812 163.339 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 143.934 Td /F1 9.8 Tf [(Given these high expectations, it is important to optimise DWI sequences and to perform a rigorous hardware quality control. )] TJ ET BT 26.250 132.030 Td /F1 9.8 Tf [(Physical phantoms play a critical part in large studies such as PREDICT-HD )] TJ ET 0.267 0.267 0.267 rg BT 356.765 132.030 Td /F1 9.8 Tf [([7])] TJ ET 0.271 0.267 0.267 rg BT 367.607 132.030 Td /F1 9.8 Tf [( and TRACK-HD )] TJ ET 0.267 0.267 0.267 rg BT 442.370 132.030 Td /F1 9.8 Tf [([8])] TJ ET 0.271 0.267 0.267 rg BT 453.212 132.030 Td /F1 9.8 Tf [(. However, subject-related )] TJ ET BT 26.250 120.125 Td /F1 9.8 Tf [(factors are equally important for data quality, particularly in a hyperkinetic movement disorder in which the extent of movement-)] TJ ET BT 26.250 108.220 Td /F1 9.8 Tf [(related artifacts increases as the disease progresses. There is no systematic effect of movement on FA: it can either increase or )] TJ ET BT 26.250 96.315 Td /F1 9.8 Tf [(decrease as a result of movement artifacts. Longitudinal studies need to take the effect of those movements on data quality into )] TJ ET BT 26.250 84.411 Td /F1 9.8 Tf [(consideration in order to remain sensitive to longitudinal change this is essential to provide biomarkers useful for clinical trials )] TJ ET 0.267 0.267 0.267 rg BT 26.250 72.506 Td /F1 9.8 Tf [([2])] TJ ET 0.271 0.267 0.267 rg BT 37.092 72.506 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 53.101 Td /F1 9.8 Tf [(In the present study, we developed a framework to detect and remove motion artifacts in DWI as an instrument of quality control )] TJ ET BT 26.250 41.196 Td /F1 9.8 Tf [(\(QC\). Here, DWI data with a high number of different diffusion directions present various challenges including motion-related )] TJ ET Q q 15.000 684.354 577.500 53.646 re W n 0.267 0.267 0.267 rg BT 15.000 718.042 Td /F2 21.0 Tf [(Stability of white matter changes related to Huntingtons )] TJ ET BT 15.000 693.094 Td /F2 21.0 Tf [(disease in the presence of imaging noise: a DTI study)] TJ ET Q 0.271 0.267 0.267 rg BT 15.000 675.088 Td /F3 9.8 Tf [(June 7, 2011)] TJ ET BT 69.971 675.088 Td /F3 9.8 Tf [()] TJ ET 0.267 0.267 0.267 rg BT 74.846 675.088 Td /F3 9.8 Tf [(Biomarkers)] TJ ET BT 26.250 663.247 Td /F1 9.8 Tf [(Hans-Peter Mller)] TJ ET 0.271 0.267 0.267 rg BT 104.806 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 110.227 663.247 Td /F1 9.8 Tf [(Volkmar Glauche)] TJ ET 0.271 0.267 0.267 rg BT 185.000 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 190.421 663.247 Td /F1 9.8 Tf [(Marianne Novak)] TJ ET 0.271 0.267 0.267 rg BT 261.401 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 266.822 663.247 Td /F1 9.8 Tf [(Thao Nguyen-Thanh)] TJ ET 0.271 0.267 0.267 rg BT 356.239 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 361.660 663.247 Td /F1 9.8 Tf [(Alexander Unrath)] TJ ET 0.271 0.267 0.267 rg BT 437.524 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 442.945 663.247 Td /F1 9.8 Tf [(Nayana Lahiri Swales)] TJ ET 0.271 0.267 0.267 rg BT 537.228 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 542.649 663.247 Td /F1 9.8 Tf [(Joy )] TJ ET BT 26.250 651.342 Td /F1 9.8 Tf [(Read)] TJ ET 0.271 0.267 0.267 rg BT 49.552 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 54.974 651.342 Td /F1 9.8 Tf [(Miranda Julia Say)] TJ ET 0.271 0.267 0.267 rg BT 132.457 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 137.878 651.342 Td /F1 9.8 Tf [(Sarah J Tabrizi)] TJ ET 0.271 0.267 0.267 rg BT 203.437 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 208.858 651.342 Td /F1 9.8 Tf [(Jan Kassubek)] TJ ET 0.271 0.267 0.267 rg BT 270.098 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 275.519 651.342 Td /F1 9.8 Tf [(Stefan Kloppel)] TJ ET 0.271 0.267 0.267 rg BT 26.250 639.438 Td /F1 9.8 Tf [(Mller H, Glauche V, Novak M, Nguyen-Thanh T, Unrath A, Lahiri Swales N, Read J, Say MJ, Tabrizi SJ, Kassubek J, Kloppel )] TJ ET BT 26.250 627.533 Td /F1 9.8 Tf [(S. Stability of white matter changes related to Huntingtons disease in the presence of imaging noise: a DTI study. PLOS )] TJ ET BT 26.250 615.628 Td /F1 9.8 Tf [(Currents Huntington Disease. 2011 Jun 7 . Edition 1. doi: 10.1371/currents.RRN1232.)] TJ ET q 15.000 26.911 577.500 586.337 re W n 0.271 0.267 0.267 rg BT 26.250 586.526 Td /F4 12.0 Tf [(Abstract)] TJ ET BT 26.250 566.571 Td /F1 9.8 Tf [(Movement artifacts and other sources of noise are a matter of concern particularly in the neuroimaging research of movement )] TJ ET BT 26.250 554.667 Td /F1 9.8 Tf [(disorders such as Huntingtons disease \(HD\). Using diffusion weighted imaging \(DWI\) and fractional anisotropy \(FA\) as a )] TJ ET BT 26.250 542.762 Td /F1 9.8 Tf [(compound marker of white matter integrity, we investigated the effect of movement on HD specific changes in magnetic )] TJ ET BT 26.250 530.857 Td /F1 9.8 Tf [(resonance imaging \(MRI\) data and how post hoc compensation for it affects the MRI results. To this end, we studied by 3T MRI: )] TJ ET BT 26.250 518.952 Td /F1 9.8 Tf [(18 early affected, 22 premanifest gene-positive subjects, 23 healthy controls \(50 slices of 2.3 mm thickness per volume, 64 )] TJ ET BT 26.250 507.048 Td /F1 9.8 Tf [(diffusion-weighted directions \(b = 1000 s/mm2\), 8 minimal diffusion-weighting \(b = 100 s/mm2\)\); and by 1.5 T imaging: 29 )] TJ ET BT 26.250 495.143 Td /F1 9.8 Tf [(premanifest HD, 30 controls \(40 axial slices of 2.3 mm thickness per volume, 61 diffusion-weighted directions \(b = 1000 s/mm2\), )] TJ ET BT 26.250 483.238 Td /F1 9.8 Tf [(minimal diffusion-weighting \(b = 100 s/mm2\)\). An outlier based method was developed to identify movement and other sources )] TJ ET BT 26.250 471.333 Td /F1 9.8 Tf [(of noise by comparing the index DWI direction against a weighted average computed from all other directions of the same )] TJ ET BT 26.250 459.429 Td /F1 9.8 Tf [(subject. No significant differences were observed when separately comparing each group of patients with and without removal )] TJ ET BT 26.250 447.524 Td /F1 9.8 Tf [(of DWI volumes that contained artifacts. In line with previous DWI-based studies, decreased FA in the corpus callosum and )] TJ ET BT 26.250 435.619 Td /F1 9.8 Tf [(increased FA around the basal ganglia were observed when premanifest mutation carriers and early affected patients were )] TJ ET BT 26.250 423.714 Td /F1 9.8 Tf [(compared with healthy controls. These findings demonstrate the robustness of the FA value in the presence of movement and )] TJ ET BT 26.250 411.810 Td /F1 9.8 Tf [(thus encourage multi-center imaging studies in HD.)] TJ ET BT 26.250 375.207 Td /F4 12.0 Tf [(Funding Statement)] TJ ET BT 26.250 355.253 Td /F1 9.8 Tf [(This work was supported by the European HD network \(EHDN project 070\). MN is funded from a Wellcome Trust grant held by )] TJ ET BT 26.250 343.348 Td /F1 9.8 Tf [(ST \(075696/Z/04/Z\). The 3T MRI scans were acquired as part of the London site TRACK-HD cohort. TRACK-HD is supported )] TJ ET BT 26.250 331.443 Td /F1 9.8 Tf [(by the CHDI Foundation, a not for profit organization dedicated to finding treatments for HD. Some of this work was undertaken )] TJ ET BT 26.250 319.539 Td /F1 9.8 Tf [(at UCLH/UCL who acknowledge support from the respective Department of Healths NIHR Biomedical Research Centres.)] TJ ET BT 26.250 290.436 Td /F4 12.0 Tf [(Introduction)] TJ ET BT 26.250 270.482 Td /F1 9.8 Tf [(White matter \(WM\) changes in Huntingtons Disease \(HD\) have been shown in a number of studies \(see )] TJ ET 0.267 0.267 0.267 rg BT 478.163 270.482 Td /F1 9.8 Tf [([1])] TJ ET 0.271 0.267 0.267 rg BT 489.005 270.482 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 494.425 270.482 Td /F1 9.8 Tf [([2])] TJ ET 0.271 0.267 0.267 rg BT 505.267 270.482 Td /F1 9.8 Tf [( for reviews\) and )] TJ ET BT 26.250 258.577 Td /F1 9.8 Tf [(have mainly been studied using diffusion weighted imaging \(DWI\) and diffusion tensor imaging \(DTI\). DWI is based on the )] TJ ET BT 26.250 246.672 Td /F1 9.8 Tf [(diffusion of water which is influenced by local tissue properties, and DWI-sequences combine several gradient directions, each )] TJ ET BT 26.250 234.768 Td /F1 9.8 Tf [(of which codes the diffusion along its direction )] TJ ET 0.267 0.267 0.267 rg BT 227.305 234.768 Td /F1 9.8 Tf [([3])] TJ ET 0.271 0.267 0.267 rg BT 238.147 234.768 Td /F1 9.8 Tf [( so that DTI characterises the combination of diffusion directions in each voxel. )] TJ ET BT 26.250 222.863 Td /F1 9.8 Tf [(The tensor takes the form of a sphere when diffusion is equal in all directions and a cigar-like shape when a single diffusion )] TJ ET BT 26.250 210.958 Td /F1 9.8 Tf [(direction dominates. The shape information can be converted into compound measures such as fractional anisotropy \(FA\), a )] TJ ET BT 26.250 199.053 Td /F1 9.8 Tf [(dimensionless scalar ranging from zero \(in water\) to one, in order to compare groups and to correlate clinical markers with )] TJ ET BT 26.250 187.149 Td /F1 9.8 Tf [(imaging data. In the field of HD research, recent studies indicate that DTI can be useful to measure longitudinal change )] TJ ET 0.267 0.267 0.267 rg BT 542.171 187.149 Td /F1 9.8 Tf [([4])] TJ ET 0.271 0.267 0.267 rg BT 553.013 187.149 Td /F1 9.8 Tf [(, or to )] TJ ET BT 26.250 175.244 Td /F1 9.8 Tf [(detect early changes in the sensorimotor cortex in premanifest HD )] TJ ET 0.267 0.267 0.267 rg BT 314.528 175.244 Td /F1 9.8 Tf [([5])] TJ ET 0.271 0.267 0.267 rg BT 325.370 175.244 Td /F1 9.8 Tf [( so that DTI is an important tool to understand the )] TJ ET BT 26.250 163.339 Td /F1 9.8 Tf [(phenotypical variability seen in HD )] TJ ET 0.267 0.267 0.267 rg BT 177.970 163.339 Td /F1 9.8 Tf [([6])] TJ ET 0.271 0.267 0.267 rg BT 188.812 163.339 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 143.934 Td /F1 9.8 Tf [(Given these high expectations, it is important to optimise DWI sequences and to perform a rigorous hardware quality control. )] TJ ET BT 26.250 132.030 Td /F1 9.8 Tf [(Physical phantoms play a critical part in large studies such as PREDICT-HD )] TJ ET 0.267 0.267 0.267 rg BT 356.765 132.030 Td /F1 9.8 Tf [([7])] TJ ET 0.271 0.267 0.267 rg BT 367.607 132.030 Td /F1 9.8 Tf [( and TRACK-HD )] TJ ET 0.267 0.267 0.267 rg BT 442.370 132.030 Td /F1 9.8 Tf [([8])] TJ ET 0.271 0.267 0.267 rg BT 453.212 132.030 Td /F1 9.8 Tf [(. However, subject-related )] TJ ET BT 26.250 120.125 Td /F1 9.8 Tf [(factors are equally important for data quality, particularly in a hyperkinetic movement disorder in which the extent of movement-)] TJ ET BT 26.250 108.220 Td /F1 9.8 Tf [(related artifacts increases as the disease progresses. There is no systematic effect of movement on FA: it can either increase or )] TJ ET BT 26.250 96.315 Td /F1 9.8 Tf [(decrease as a result of movement artifacts. Longitudinal studies need to take the effect of those movements on data quality into )] TJ ET BT 26.250 84.411 Td /F1 9.8 Tf [(consideration in order to remain sensitive to longitudinal change this is essential to provide biomarkers useful for clinical trials )] TJ ET 0.267 0.267 0.267 rg BT 26.250 72.506 Td /F1 9.8 Tf [([2])] TJ ET 0.271 0.267 0.267 rg BT 37.092 72.506 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 53.101 Td /F1 9.8 Tf [(In the present study, we developed a framework to detect and remove motion artifacts in DWI as an instrument of quality control )] TJ ET BT 26.250 41.196 Td /F1 9.8 Tf [(\(QC\). Here, DWI data with a high number of different diffusion directions present various challenges including motion-related )] TJ ET Q q 15.000 684.354 577.500 53.646 re W n 0.267 0.267 0.267 rg BT 15.000 718.042 Td /F2 21.0 Tf [(Stability of white matter changes related to Huntingtons )] TJ ET BT 15.000 693.094 Td /F2 21.0 Tf [(disease in the presence of imaging noise: a DTI study)] TJ ET Q 0.271 0.267 0.267 rg BT 15.000 675.088 Td /F3 9.8 Tf [(June 7, 2011)] TJ ET BT 69.971 675.088 Td /F3 9.8 Tf [()] TJ ET 0.267 0.267 0.267 rg BT 74.846 675.088 Td /F3 9.8 Tf [(Biomarkers)] TJ ET BT 26.250 663.247 Td /F1 9.8 Tf [(Hans-Peter Mller)] TJ ET 0.271 0.267 0.267 rg BT 104.806 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 110.227 663.247 Td /F1 9.8 Tf [(Volkmar Glauche)] TJ ET 0.271 0.267 0.267 rg BT 185.000 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 190.421 663.247 Td /F1 9.8 Tf [(Marianne Novak)] TJ ET 0.271 0.267 0.267 rg BT 261.401 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 266.822 663.247 Td /F1 9.8 Tf [(Thao Nguyen-Thanh)] TJ ET 0.271 0.267 0.267 rg BT 356.239 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 361.660 663.247 Td /F1 9.8 Tf [(Alexander Unrath)] TJ ET 0.271 0.267 0.267 rg BT 437.524 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 442.945 663.247 Td /F1 9.8 Tf [(Nayana Lahiri Swales)] TJ ET 0.271 0.267 0.267 rg BT 537.228 663.247 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 542.649 663.247 Td /F1 9.8 Tf [(Joy )] TJ ET BT 26.250 651.342 Td /F1 9.8 Tf [(Read)] TJ ET 0.271 0.267 0.267 rg BT 49.552 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 54.974 651.342 Td /F1 9.8 Tf [(Miranda Julia Say)] TJ ET 0.271 0.267 0.267 rg BT 132.457 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 137.878 651.342 Td /F1 9.8 Tf [(Sarah J Tabrizi)] TJ ET 0.271 0.267 0.267 rg BT 203.437 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 208.858 651.342 Td /F1 9.8 Tf [(Jan Kassubek)] TJ ET 0.271 0.267 0.267 rg BT 270.098 651.342 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 275.519 651.342 Td /F1 9.8 Tf [(Stefan Kloppel)] TJ ET 0.271 0.267 0.267 rg BT 26.250 639.438 Td /F1 9.8 Tf [(Mller H, Glauche V, Novak M, Nguyen-Thanh T, Unrath A, Lahiri Swales N, Read J, Say MJ, Tabrizi SJ, Kassubek J, Kloppel )] TJ ET BT 26.250 627.533 Td /F1 9.8 Tf [(S. Stability of white matter changes related to Huntingtons disease in the presence of imaging noise: a DTI study. PLOS )] TJ ET BT 26.250 615.628 Td /F1 9.8 Tf [(Currents Huntington Disease. 2011 Jun 7 . Edition 1. doi: 10.1371/currents.RRN1232.)] TJ ET q 15.000 26.911 577.500 586.337 re W n 0.271 0.267 0.267 rg BT 26.250 586.526 Td /F4 12.0 Tf [(Abstract)] TJ ET BT 26.250 566.571 Td /F1 9.8 Tf [(Movement artifacts and other sources of noise are a matter of concern particularly in the neuroimaging research of movement )] TJ ET BT 26.250 554.667 Td /F1 9.8 Tf [(disorders such as Huntingtons disease \(HD\). Using diffusion weighted imaging \(DWI\) and fractional anisotropy \(FA\) as a )] TJ ET BT 26.250 542.762 Td /F1 9.8 Tf [(compound marker of white matter integrity, we investigated the effect of movement on HD specific changes in magnetic )] TJ ET BT 26.250 530.857 Td /F1 9.8 Tf [(resonance imaging \(MRI\) data and how post hoc compensation for it affects the MRI results. To this end, we studied by 3T MRI: )] TJ ET BT 26.250 518.952 Td /F1 9.8 Tf [(18 early affected, 22 premanifest gene-positive subjects, 23 healthy controls \(50 slices of 2.3 mm thickness per volume, 64 )] TJ ET BT 26.250 507.048 Td /F1 9.8 Tf [(diffusion-weighted directions \(b = 1000 s/mm2\), 8 minimal diffusion-weighting \(b = 100 s/mm2\)\); and by 1.5 T imaging: 29 )] TJ ET BT 26.250 495.143 Td /F1 9.8 Tf [(premanifest HD, 30 controls \(40 axial slices of 2.3 mm thickness per volume, 61 diffusion-weighted directions \(b = 1000 s/mm2\), )] TJ ET BT 26.250 483.238 Td /F1 9.8 Tf [(minimal diffusion-weighting \(b = 100 s/mm2\)\). An outlier based method was developed to identify movement and other sources )] TJ ET BT 26.250 471.333 Td /F1 9.8 Tf [(of noise by comparing the index DWI direction against a weighted average computed from all other directions of the same )] TJ ET BT 26.250 459.429 Td /F1 9.8 Tf [(subject. No significant differences were observed when separately comparing each group of patients with and without removal )] TJ ET BT 26.250 447.524 Td /F1 9.8 Tf [(of DWI volumes that contained artifacts. In line with previous DWI-based studies, decreased FA in the corpus callosum and )] TJ ET BT 26.250 435.619 Td /F1 9.8 Tf [(increased FA around the basal ganglia were observed when premanifest mutation carriers and early affected patients were )] TJ ET BT 26.250 423.714 Td /F1 9.8 Tf [(compared with healthy controls. These findings demonstrate the robustness of the FA value in the presence of movement and )] TJ ET BT 26.250 411.810 Td /F1 9.8 Tf [(thus encourage multi-center imaging studies in HD.)] TJ ET BT 26.250 375.207 Td /F4 12.0 Tf [(Funding Statement)] TJ ET BT 26.250 355.253 Td /F1 9.8 Tf [(This work was supported by the European HD network \(EHDN project 070\). MN is funded from a Wellcome Trust grant held by )] TJ ET BT 26.250 343.348 Td /F1 9.8 Tf [(ST \(075696/Z/04/Z\). The 3T MRI scans were acquired as part of the London site TRACK-HD cohort. TRACK-HD is supported )] TJ ET BT 26.250 331.443 Td /F1 9.8 Tf [(by the CHDI Foundation, a not for profit organization dedicated to finding treatments for HD. Some of this work was undertaken )] TJ ET BT 26.250 319.539 Td /F1 9.8 Tf [(at UCLH/UCL who acknowledge support from the respective Department of Healths NIHR Biomedical Research Centres.)] TJ ET BT 26.250 290.436 Td /F4 12.0 Tf [(Introduction)] TJ ET BT 26.250 270.482 Td /F1 9.8 Tf [(White matter \(WM\) changes in Huntingtons Disease \(HD\) have been shown in a number of studies \(see )] TJ ET 0.267 0.267 0.267 rg BT 478.163 270.482 Td /F1 9.8 Tf [([1])] TJ ET 0.271 0.267 0.267 rg BT 489.005 270.482 Td /F1 9.8 Tf [(, )] TJ ET 0.267 0.267 0.267 rg BT 494.425 270.482 Td /F1 9.8 Tf [([2])] TJ ET 0.271 0.267 0.267 rg BT 505.267 270.482 Td /F1 9.8 Tf [( for reviews\) and )] TJ ET BT 26.250 258.577 Td /F1 9.8 Tf [(have mainly been studied using diffusion weighted imaging \(DWI\) and diffusion tensor imaging \(DTI\). DWI is based on the )] TJ ET BT 26.250 246.672 Td /F1 9.8 Tf [(diffusion of water which is influenced by local tissue properties, and DWI-sequences combine several gradient directions, each )] TJ ET BT 26.250 234.768 Td /F1 9.8 Tf [(of which codes the diffusion along its direction )] TJ ET 0.267 0.267 0.267 rg BT 227.305 234.768 Td /F1 9.8 Tf [([3])] TJ ET 0.271 0.267 0.267 rg BT 238.147 234.768 Td /F1 9.8 Tf [( so that DTI characterises the combination of diffusion directions in each voxel. )] TJ ET BT 26.250 222.863 Td /F1 9.8 Tf [(The tensor takes the form of a sphere when diffusion is equal in all directions and a cigar-like shape when a single diffusion )] TJ ET BT 26.250 210.958 Td /F1 9.8 Tf [(direction dominates. The shape information can be converted into compound measures such as fractional anisotropy \(FA\), a )] TJ ET BT 26.250 199.053 Td /F1 9.8 Tf [(dimensionless scalar ranging from zero \(in water\) to one, in order to compare groups and to correlate clinical markers with )] TJ ET BT 26.250 187.149 Td /F1 9.8 Tf [(imaging data. In the field of HD research, recent studies indicate that DTI can be useful to measure longitudinal change )] TJ ET 0.267 0.267 0.267 rg BT 542.171 187.149 Td /F1 9.8 Tf [([4])] TJ ET 0.271 0.267 0.267 rg BT 553.013 187.149 Td /F1 9.8 Tf [(, or to )] TJ ET BT 26.250 175.244 Td /F1 9.8 Tf [(detect early changes in the sensorimotor cortex in premanifest HD )] TJ ET 0.267 0.267 0.267 rg BT 314.528 175.244 Td /F1 9.8 Tf [([5])] TJ ET 0.271 0.267 0.267 rg BT 325.370 175.244 Td /F1 9.8 Tf [( so that DTI is an important tool to understand the )] TJ ET BT 26.250 163.339 Td /F1 9.8 Tf [(phenotypical variability seen in HD )] TJ ET 0.267 0.267 0.267 rg BT 177.970 163.339 Td /F1 9.8 Tf [([6])] TJ ET 0.271 0.267 0.267 rg BT 188.812 163.339 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 143.934 Td /F1 9.8 Tf [(Given these high expectations, it is important to optimise DWI sequences and to perform a rigorous hardware quality control. )] TJ ET BT 26.250 132.030 Td /F1 9.8 Tf [(Physical phantoms play a critical part in large studies such as PREDICT-HD )] TJ ET 0.267 0.267 0.267 rg BT 356.765 132.030 Td /F1 9.8 Tf [([7])] TJ ET 0.271 0.267 0.267 rg BT 367.607 132.030 Td /F1 9.8 Tf [( and TRACK-HD )] TJ ET 0.267 0.267 0.267 rg BT 442.370 132.030 Td /F1 9.8 Tf [([8])] TJ ET 0.271 0.267 0.267 rg BT 453.212 132.030 Td /F1 9.8 Tf [(. However, subject-related )] TJ ET BT 26.250 120.125 Td /F1 9.8 Tf [(factors are equally important for data quality, particularly in a hyperkinetic movement disorder in which the extent of movement-)] TJ ET BT 26.250 108.220 Td /F1 9.8 Tf [(related artifacts increases as the disease progresses. There is no systematic effect of movement on FA: it can either increase or )] TJ ET BT 26.250 96.315 Td /F1 9.8 Tf [(decrease as a result of movement artifacts. Longitudinal studies need to take the effect of those movements on data quality into )] TJ ET BT 26.250 84.411 Td /F1 9.8 Tf [(consideration in order to remain sensitive to longitudinal change this is essential to provide biomarkers useful for clinical trials )] TJ ET 0.267 0.267 0.267 rg BT 26.250 72.506 Td /F1 9.8 Tf [([2])] TJ ET 0.271 0.267 0.267 rg BT 37.092 72.506 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 53.101 Td /F1 9.8 Tf [(In the present study, we developed a framework to detect and remove motion artifacts in DWI as an instrument of quality control )] TJ ET BT 26.250 41.196 Td /F1 9.8 Tf [(\(QC\). Here, DWI data with a high number of different diffusion directions present various challenges including motion-related )] TJ ET Q q 0.000 0.000 0.000 rg BT 291.710 19.825 Td /F1 11.0 Tf [(1)] TJ ET BT 25.000 19.825 Td /F1 11.0 Tf [(PLOS Currents Huntington Disease)] TJ ET Q endstream endobj 8 0 obj << /Type /Font /Subtype /Type1 /Name /F1 /BaseFont /Helvetica /Encoding /WinAnsiEncoding >> endobj 9 0 obj << /Type /Font /Subtype /Type1 /Name /F2 /BaseFont /Times-Bold /Encoding /WinAnsiEncoding >> endobj 10 0 obj << /Type /Font /Subtype /Type1 /Name /F3 /BaseFont /Times-Italic /Encoding /WinAnsiEncoding >> endobj 11 0 obj << /Type /Font /Subtype /Type1 /Name /F4 /BaseFont /Helvetica-Bold /Encoding /WinAnsiEncoding >> endobj 12 0 obj << /Type /XObject /Subtype /Image /Width 500 /Height 52 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 500 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 144>> stream x1 0 'ݲ؎"e{dzAdzAdzAdzAdzAdzAdzAdzAdzAdzAdzAdzAtlM0\ endstream endobj 13 0 obj << /Type /XObject /Subtype /Image /Width 500 /Height 52 /SMask 12 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 500 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 4223>> stream xە8=,8C#h!hGv#0=j$q1uaNĥT*J&a_Zaa0 a0 a0 H^UUUUX!0 3SY|^G0 ÌÔ{]wa_>"OeYaG!8e}a6̖{4M&d:"qʲ\QUUMS<ϛNld2l6Z a<=2B(2vK7M\.GW0 rrWWavߖe9C?Eq8Gqy~~}_qdϽ(neYʒGjK4EQNjͷm{X?|7m۶mqP:Ȳp8Kmu]lNzuZ,NTeY"jlUUQW\,aRiVbȗLkHkEsjd.L6=Iו P]1t7Sc2uIuMM; K5>A$Ǒ$I׋nY 0_Hat;aq䃰U$nR ,zO7bT mhhԫܻu1F*qm'P}ܙ<ϕALO6Lw3nB.T4co{߽.lV $laԀIu!gwChxJ]Ne (+M"d-Eqc=P ! "nf(7>ce,Řm[!ʝD!m)Bs@)ta3}g˲}ZbշONKFp倫Rg(,I2 C%5y B v o9϶m+ІXcTwV5;8dHF{7Qm6'N۠%$HSMk!D4i:ŕS*bS̹"2=ԓH51$UfZVtli<0]nDZlcWv;LQrxhk+},CVeD8]ې/.m[nc)2XAOMo&}"&ڨv宇EqX$tcGc,|`5)yO(U\͠&ԭC&~1ynKoC~kqqltV\4M8NTre#sT|>+GJ W]$Ii EMHdD70_ rEЀa:c4u U0.RH=SN4/z2pȤfx$]1 wt<]׭U$%=wi~ܮ{=×w\Բ!s^__=Axa1|=(l´i4MEUUm6y)~E5UU~gѥJ'+WTN'!H>{=nytH{{xzo<8aOw0lN]? gNR2Ɍ6Z摤Ww(eYv̲ b\aHɟ,J6 ܺ= ^'ҵ4^.˲rIaJ'RC]Qѯr洱lf?>ȩ_Ye=3ʆ:Fy0D&y%0zU^5ἧԯgFeYqƈhz#ms[o$+0Qz2-Z\"#f29:WGVzlBPD;CW+Dye$ 6HQ"\&_$Tp]Ah eHyR1' p'sD)ZDpB/Y_SVGӌ;Oo[Am+(Uܮ+UʽN=PJ/>^;?9ogmYѲ=k@._ (V{#z/,@Y,1e`& i$<=EQl6|A4b%'X[ѶaSh/QM&$NgSٲ,奭ֻDH>EeSFo['ķriVa߶ ї5,lj* QÈ=TqEMD 4N6MCL(PƯ%n^ w~oSrDfe0^F]G$IY?v+rEQ-WUmpP^ :vz֝2q#3Dƾt: ~Gv(,$j:NpCˏS)=ϛL&xlۆ+i8}CH,t%z\MD 0 ^tC>(4;ن]螞Pt:5f[@oqg{L̷gYD"maI4coKE殂 'ٲt2_,m[|QafLuDZ( W 5oOiy{0oqNF;rj%zwuo10)BwܮC!}Έ3H(.E' h]jDA 6.M T8zqy~oeO#]PWp0<;F܆b+ɽnKQy\8nڶd/خ^^o|N.[vOz`'Ef̈+""/cL<" Ƅ_~W|¿Tt"fiY_uWx<ŠM(0L891a>ao\|[C~mX3 3;o6|>ϻ#ChR0 Ì`r뚢#~#N*0 Fk%ʪrOd6u͊Akdfwܧ),Y0 ܡܛ4ۈa 0 -0 )rgrgrgrgzm endstream endobj 14 0 obj << /Type /Annot /Subtype /Link /A 15 0 R /Border [0 0 0] /H /I /Rect [ 15.0000 716.1516 530.6340 736.9416 ] >> endobj 15 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article/stability-of-white-matter-changes-related-to-huntingtons-disease-in-the-presence-of-imaging-noise-a-dti-study/) >> endobj 16 0 obj << /Type /Annot /Subtype /Link /A 17 0 R /Border [0 0 0] /H /I /Rect [ 15.0000 691.2036 488.0880 711.9936 ] >> endobj 17 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article/stability-of-white-matter-changes-related-to-huntingtons-disease-in-the-presence-of-imaging-noise-a-dti-study/) >> endobj 18 0 obj << /Type /Annot /Subtype /Link /A 19 0 R /Border [0 0 0] /H /I /Rect [ 74.8455 674.2101 120.3390 683.8626 ] >> endobj 19 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article_category/biomarkers/) >> endobj 20 0 obj << /Type /Annot /Subtype /Link /A 21 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 662.3453 104.8058 672.2659 ] >> endobj 21 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/hanspetermuller/) >> endobj 22 0 obj << /Type /Annot /Subtype /Link /A 23 0 R /Border [0 0 0] /H /I /Rect [ 110.2268 662.3453 184.9995 672.2659 ] >> endobj 23 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/volkmarglauche/) >> endobj 24 0 obj << /Type /Annot /Subtype /Link /A 25 0 R /Border [0 0 0] /H /I /Rect [ 190.4205 662.3453 261.4005 672.2659 ] >> endobj 25 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/mariannenovak/) >> endobj 26 0 obj << /Type /Annot /Subtype /Link /A 27 0 R /Border [0 0 0] /H /I /Rect [ 266.8215 662.3453 356.2387 672.2659 ] >> endobj 27 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/thaonguyenthanh/) >> endobj 28 0 obj << /Type /Annot /Subtype /Link /A 29 0 R /Border [0 0 0] /H /I /Rect [ 361.6597 662.3453 437.5245 672.2659 ] >> endobj 29 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/alexanderunrath/) >> endobj 30 0 obj << /Type /Annot /Subtype /Link /A 31 0 R /Border [0 0 0] /H /I /Rect [ 442.9455 662.3453 537.2280 672.2659 ] >> endobj 31 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/nayanalahiriswales/) >> endobj 32 0 obj << /Type /Annot /Subtype /Link /A 33 0 R /Border [0 0 0] /H /I /Rect [ 542.6490 662.3453 560.5305 672.2659 ] >> endobj 33 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/joyread/) >> endobj 34 0 obj << /Type /Annot /Subtype /Link /A 35 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 650.4406 49.5525 660.3612 ] >> endobj 35 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/joyread/) >> endobj 36 0 obj << /Type /Annot /Subtype /Link /A 37 0 R /Border [0 0 0] /H /I /Rect [ 54.9735 650.4406 132.4567 660.3612 ] >> endobj 37 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/mirandajuliasay/) >> endobj 38 0 obj << /Type /Annot /Subtype /Link /A 39 0 R /Border [0 0 0] /H /I /Rect [ 137.8777 650.4406 203.4367 660.3612 ] >> endobj 39 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/sarahjtabrizi/) >> endobj 40 0 obj << /Type /Annot /Subtype /Link /A 41 0 R /Border [0 0 0] /H /I /Rect [ 208.8578 650.4406 270.0975 660.3612 ] >> endobj 41 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/jankassubek/) >> endobj 42 0 obj << /Type /Annot /Subtype /Link /A 43 0 R /Border [0 0 0] /H /I /Rect [ 275.5185 650.4406 338.9325 660.3612 ] >> endobj 43 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/stefankloppel/) >> endobj 44 0 obj << /Type /Annot /Subtype /Link /A 45 0 R /Border [0 0 0] /H /I /Rect [ 478.1625 269.5801 489.0045 279.5007 ] >> endobj 45 0 obj << /Type /Action >> endobj 46 0 obj << /Type /Annot /Subtype /Link /A 47 0 R /Border [0 0 0] /H /I /Rect [ 494.4255 269.5801 505.2675 279.5007 ] >> endobj 47 0 obj << /Type /Action >> endobj 48 0 obj << /Type /Annot /Subtype /Link /A 49 0 R /Border [0 0 0] /H /I /Rect [ 227.3048 233.8658 238.1468 243.7865 ] >> endobj 49 0 obj << /Type /Action >> endobj 50 0 obj << /Type /Annot /Subtype /Link /A 51 0 R /Border [0 0 0] /H /I /Rect [ 542.1712 186.2468 553.0132 196.1675 ] >> endobj 51 0 obj << /Type /Action >> endobj 52 0 obj << /Type /Annot /Subtype /Link /A 53 0 R /Border [0 0 0] /H /I /Rect [ 314.5283 174.3421 325.3702 184.2627 ] >> endobj 53 0 obj << /Type /Action >> endobj 54 0 obj << /Type /Annot /Subtype /Link /A 55 0 R /Border [0 0 0] /H /I /Rect [ 177.9698 162.4373 188.8118 172.3579 ] >> endobj 55 0 obj << /Type /Action >> endobj 56 0 obj << /Type /Annot /Subtype /Link /A 57 0 R /Border [0 0 0] /H /I /Rect [ 356.7652 131.1278 367.6072 141.0484 ] >> endobj 57 0 obj << /Type /Action >> endobj 58 0 obj << /Type /Annot /Subtype /Link /A 59 0 R /Border [0 0 0] /H /I /Rect [ 442.3702 131.1278 453.2122 141.0484 ] >> endobj 59 0 obj << /Type /Action >> endobj 60 0 obj << /Type /Annot /Subtype /Link /A 61 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 71.6041 37.0920 81.5247 ] >> endobj 61 0 obj << /Type /Action >> endobj 62 0 obj << /Type /Annot /Subtype /Link /A 63 0 R /Border [0 0 0] /H /I /Rect [ 15.0000 716.1516 530.6340 736.9416 ] >> endobj 63 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article/stability-of-white-matter-changes-related-to-huntingtons-disease-in-the-presence-of-imaging-noise-a-dti-study/) >> endobj 64 0 obj << /Type /Annot /Subtype /Link /A 65 0 R /Border [0 0 0] /H /I /Rect [ 15.0000 691.2036 488.0880 711.9936 ] >> endobj 65 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article/stability-of-white-matter-changes-related-to-huntingtons-disease-in-the-presence-of-imaging-noise-a-dti-study/) >> endobj 66 0 obj << /Type /Annot /Subtype /Link /A 67 0 R /Border [0 0 0] /H /I /Rect [ 74.8455 674.2101 120.3390 683.8626 ] >> endobj 67 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article_category/biomarkers/) >> endobj 68 0 obj << /Type /Annot /Subtype /Link /A 69 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 662.3453 104.8058 672.2659 ] >> endobj 69 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/hanspetermuller/) >> endobj 70 0 obj << /Type /Annot /Subtype /Link /A 71 0 R /Border [0 0 0] /H /I /Rect [ 110.2268 662.3453 184.9995 672.2659 ] >> endobj 71 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/volkmarglauche/) >> endobj 72 0 obj << /Type /Annot /Subtype /Link /A 73 0 R /Border [0 0 0] /H /I /Rect [ 190.4205 662.3453 261.4005 672.2659 ] >> endobj 73 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/mariannenovak/) >> endobj 74 0 obj << /Type /Annot /Subtype /Link /A 75 0 R /Border [0 0 0] /H /I /Rect [ 266.8215 662.3453 356.2387 672.2659 ] >> endobj 75 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/thaonguyenthanh/) >> endobj 76 0 obj << /Type /Annot /Subtype /Link /A 77 0 R /Border [0 0 0] /H /I /Rect [ 361.6597 662.3453 437.5245 672.2659 ] >> endobj 77 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/alexanderunrath/) >> endobj 78 0 obj << /Type /Annot /Subtype /Link /A 79 0 R /Border [0 0 0] /H /I /Rect [ 442.9455 662.3453 537.2280 672.2659 ] >> endobj 79 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/nayanalahiriswales/) >> endobj 80 0 obj << /Type /Annot /Subtype /Link /A 81 0 R /Border [0 0 0] /H /I /Rect [ 542.6490 662.3453 560.5305 672.2659 ] >> endobj 81 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/joyread/) >> endobj 82 0 obj << /Type /Annot /Subtype /Link /A 83 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 650.4406 49.5525 660.3612 ] >> endobj 83 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/joyread/) >> endobj 84 0 obj << /Type /Annot /Subtype /Link /A 85 0 R /Border [0 0 0] /H /I /Rect [ 54.9735 650.4406 132.4567 660.3612 ] >> endobj 85 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/mirandajuliasay/) >> endobj 86 0 obj << /Type /Annot /Subtype /Link /A 87 0 R /Border [0 0 0] /H /I /Rect [ 137.8777 650.4406 203.4367 660.3612 ] >> endobj 87 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/sarahjtabrizi/) >> endobj 88 0 obj << /Type /Annot /Subtype /Link /A 89 0 R /Border [0 0 0] /H /I /Rect [ 208.8578 650.4406 270.0975 660.3612 ] >> endobj 89 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/jankassubek/) >> endobj 90 0 obj << /Type /Annot /Subtype /Link /A 91 0 R /Border [0 0 0] /H /I /Rect [ 275.5185 650.4406 338.9325 660.3612 ] >> endobj 91 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/stefankloppel/) >> endobj 92 0 obj << /Type /Annot /Subtype /Link /A 93 0 R /Border [0 0 0] /H /I /Rect [ 478.1625 269.5801 489.0045 279.5007 ] >> endobj 93 0 obj << /Type /Action >> endobj 94 0 obj << /Type /Annot /Subtype /Link /A 95 0 R /Border [0 0 0] /H /I /Rect [ 494.4255 269.5801 505.2675 279.5007 ] >> endobj 95 0 obj << /Type /Action >> endobj 96 0 obj << /Type /Annot /Subtype /Link /A 97 0 R /Border [0 0 0] /H /I /Rect [ 227.3048 233.8658 238.1468 243.7865 ] >> endobj 97 0 obj << /Type /Action >> endobj 98 0 obj << /Type /Annot /Subtype /Link /A 99 0 R /Border [0 0 0] /H /I /Rect [ 542.1712 186.2468 553.0132 196.1675 ] >> endobj 99 0 obj << /Type /Action >> endobj 100 0 obj << /Type /Annot /Subtype /Link /A 101 0 R /Border [0 0 0] /H /I /Rect [ 314.5283 174.3421 325.3702 184.2627 ] >> endobj 101 0 obj << /Type /Action >> endobj 102 0 obj << /Type /Annot /Subtype /Link /A 103 0 R /Border [0 0 0] /H /I /Rect [ 177.9698 162.4373 188.8118 172.3579 ] >> endobj 103 0 obj << /Type /Action >> endobj 104 0 obj << /Type /Annot /Subtype /Link /A 105 0 R /Border [0 0 0] /H /I /Rect [ 356.7652 131.1278 367.6072 141.0484 ] >> endobj 105 0 obj << /Type /Action >> endobj 106 0 obj << /Type /Annot /Subtype /Link /A 107 0 R /Border [0 0 0] /H /I /Rect [ 442.3702 131.1278 453.2122 141.0484 ] >> endobj 107 0 obj << /Type /Action >> endobj 108 0 obj << /Type /Annot /Subtype /Link /A 109 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 71.6041 37.0920 81.5247 ] >> endobj 109 0 obj << /Type /Action >> endobj 110 0 obj << /Type /Annot /Subtype /Link /A 111 0 R /Border [0 0 0] /H /I /Rect [ 15.0000 716.1516 530.6340 736.9416 ] >> endobj 111 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article/stability-of-white-matter-changes-related-to-huntingtons-disease-in-the-presence-of-imaging-noise-a-dti-study/) >> endobj 112 0 obj << /Type /Annot /Subtype /Link /A 113 0 R /Border [0 0 0] /H /I /Rect [ 15.0000 691.2036 488.0880 711.9936 ] >> endobj 113 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article/stability-of-white-matter-changes-related-to-huntingtons-disease-in-the-presence-of-imaging-noise-a-dti-study/) >> endobj 114 0 obj << /Type /Annot /Subtype /Link /A 115 0 R /Border [0 0 0] /H /I /Rect [ 74.8455 674.2101 120.3390 683.8626 ] >> endobj 115 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/article_category/biomarkers/) >> endobj 116 0 obj << /Type /Annot /Subtype /Link /A 117 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 662.3453 104.8058 672.2659 ] >> endobj 117 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/hanspetermuller/) >> endobj 118 0 obj << /Type /Annot /Subtype /Link /A 119 0 R /Border [0 0 0] /H /I /Rect [ 110.2268 662.3453 184.9995 672.2659 ] >> endobj 119 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/volkmarglauche/) >> endobj 120 0 obj << /Type /Annot /Subtype /Link /A 121 0 R /Border [0 0 0] /H /I /Rect [ 190.4205 662.3453 261.4005 672.2659 ] >> endobj 121 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/mariannenovak/) >> endobj 122 0 obj << /Type /Annot /Subtype /Link /A 123 0 R /Border [0 0 0] /H /I /Rect [ 266.8215 662.3453 356.2387 672.2659 ] >> endobj 123 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/thaonguyenthanh/) >> endobj 124 0 obj << /Type /Annot /Subtype /Link /A 125 0 R /Border [0 0 0] /H /I /Rect [ 361.6597 662.3453 437.5245 672.2659 ] >> endobj 125 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/alexanderunrath/) >> endobj 126 0 obj << /Type /Annot /Subtype /Link /A 127 0 R /Border [0 0 0] /H /I /Rect [ 442.9455 662.3453 537.2280 672.2659 ] >> endobj 127 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/nayanalahiriswales/) >> endobj 128 0 obj << /Type /Annot /Subtype /Link /A 129 0 R /Border [0 0 0] /H /I /Rect [ 542.6490 662.3453 560.5305 672.2659 ] >> endobj 129 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/joyread/) >> endobj 130 0 obj << /Type /Annot /Subtype /Link /A 131 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 650.4406 49.5525 660.3612 ] >> endobj 131 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/joyread/) >> endobj 132 0 obj << /Type /Annot /Subtype /Link /A 133 0 R /Border [0 0 0] /H /I /Rect [ 54.9735 650.4406 132.4567 660.3612 ] >> endobj 133 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/mirandajuliasay/) >> endobj 134 0 obj << /Type /Annot /Subtype /Link /A 135 0 R /Border [0 0 0] /H /I /Rect [ 137.8777 650.4406 203.4367 660.3612 ] >> endobj 135 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/sarahjtabrizi/) >> endobj 136 0 obj << /Type /Annot /Subtype /Link /A 137 0 R /Border [0 0 0] /H /I /Rect [ 208.8578 650.4406 270.0975 660.3612 ] >> endobj 137 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/jankassubek/) >> endobj 138 0 obj << /Type /Annot /Subtype /Link /A 139 0 R /Border [0 0 0] /H /I /Rect [ 275.5185 650.4406 338.9325 660.3612 ] >> endobj 139 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/author/stefankloppel/) >> endobj 140 0 obj << /Type /Annot /Subtype /Link /A 141 0 R /Border [0 0 0] /H /I /Rect [ 478.1625 269.5801 489.0045 279.5007 ] >> endobj 141 0 obj << /Type /Action >> endobj 142 0 obj << /Type /Annot /Subtype /Link /A 143 0 R /Border [0 0 0] /H /I /Rect [ 494.4255 269.5801 505.2675 279.5007 ] >> endobj 143 0 obj << /Type /Action >> endobj 144 0 obj << /Type /Annot /Subtype /Link /A 145 0 R /Border [0 0 0] /H /I /Rect [ 227.3048 233.8658 238.1468 243.7865 ] >> endobj 145 0 obj << /Type /Action >> endobj 146 0 obj << /Type /Annot /Subtype /Link /A 147 0 R /Border [0 0 0] /H /I /Rect [ 542.1712 186.2468 553.0132 196.1675 ] >> endobj 147 0 obj << /Type /Action >> endobj 148 0 obj << /Type /Annot /Subtype /Link /A 149 0 R /Border [0 0 0] /H /I /Rect [ 314.5283 174.3421 325.3702 184.2627 ] >> endobj 149 0 obj << /Type /Action >> endobj 150 0 obj << /Type /Annot /Subtype /Link /A 151 0 R /Border [0 0 0] /H /I /Rect [ 177.9698 162.4373 188.8118 172.3579 ] >> endobj 151 0 obj << /Type /Action >> endobj 152 0 obj << /Type /Annot /Subtype /Link /A 153 0 R /Border [0 0 0] /H /I /Rect [ 356.7652 131.1278 367.6072 141.0484 ] >> endobj 153 0 obj << /Type /Action >> endobj 154 0 obj << /Type /Annot /Subtype /Link /A 155 0 R /Border [0 0 0] /H /I /Rect [ 442.3702 131.1278 453.2122 141.0484 ] >> endobj 155 0 obj << /Type /Action >> endobj 156 0 obj << /Type /Annot /Subtype /Link /A 157 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 71.6041 37.0920 81.5247 ] >> endobj 157 0 obj << /Type /Action >> endobj 158 0 obj << /Type /Page /Parent 3 0 R /Annots [ 160 0 R 162 0 R 164 0 R 166 0 R 168 0 R 170 0 R 172 0 R 174 0 R 176 0 R 178 0 R 180 0 R 182 0 R 184 0 R 186 0 R 188 0 R 190 0 R 192 0 R 194 0 R ] /Contents 159 0 R >> endobj 159 0 obj << /Length 44203 >> stream 0.271 0.267 0.267 rg q 15.000 43.336 577.500 733.664 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(signal dropouts \(cf. Figure 1\).)] TJ ET BT 26.250 748.071 Td /F1 9.8 Tf [(Using DWI data from different stages of HD, we explored a weighted average approach to detect artifacts in two dimensions )] TJ ET BT 26.250 736.167 Td /F1 9.8 Tf [(\(slicewise approach\): For each gradient direction, the weighted variance was computed from all remaining directions in the )] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(sequence by weighting with the angle in which they differ from the index gradient direction. This novel approach was applied to )] TJ ET BT 26.250 712.357 Td /F1 9.8 Tf [(data acquired with different field strengths \(i.e., 1.5 and 3 Tesla\).)] TJ ET BT 26.250 675.755 Td /F4 12.0 Tf [(Material and Methods)] TJ ET BT 26.250 655.800 Td /F1 9.8 Tf [(Data from two scanners were used. Table 1 provides demographic details and the motor scale of the Unified Huntingtons )] TJ ET BT 26.250 643.896 Td /F1 9.8 Tf [(Disease Rating Scale \(UHDRS\) for the subjects. It also provides the estimated years to the onset of typical motor signs, based )] TJ ET BT 26.250 631.991 Td /F1 9.8 Tf [(on CAG repeat length and age at a 60% certainty level )] TJ ET 0.267 0.267 0.267 rg BT 264.716 631.991 Td /F1 9.8 Tf [([9])] TJ ET 0.271 0.267 0.267 rg BT 275.558 631.991 Td /F1 9.8 Tf [(. Given the purpose of this study, we ignored the outcome of a visual )] TJ ET BT 26.250 620.086 Td /F1 9.8 Tf [(data inspection step which would have led to the exclusion of subjects with extensive artifacts. The study was approved by the )] TJ ET BT 26.250 608.181 Td /F1 9.8 Tf [(local ethics committees, and written informed consent was obtained from each subject.)] TJ ET BT 26.250 588.777 Td /F4 9.8 Tf [(1.5 Tesla Data)] TJ ET BT 26.250 569.372 Td /F1 9.8 Tf [(Twenty-nine premanifest HD patients and 30 controls were scanned on the same Siemens Sonata 1.5 Tesla scanner \(a )] TJ ET BT 26.250 557.467 Td /F1 9.8 Tf [(subgroup of this cohort has been reported in our earlier work )] TJ ET 0.267 0.267 0.267 rg BT 290.163 557.467 Td /F1 9.8 Tf [([6])] TJ ET 0.271 0.267 0.267 rg BT 301.005 557.467 Td /F1 9.8 Tf [(\). DWI was performed with an echo planar sequence with a )] TJ ET BT 26.250 545.562 Td /F1 9.8 Tf [(double spin-echo module to reduce the effect of eddy currents )] TJ ET 0.267 0.267 0.267 rg BT 296.686 545.562 Td /F1 9.8 Tf [([10])] TJ ET 0.271 0.267 0.267 rg BT 312.949 545.562 Td /F1 9.8 Tf [(. Each data volume consisted of 40 axial slices of 2.3 mm )] TJ ET BT 26.250 533.658 Td /F1 9.8 Tf [(thickness, with no inter-slice gaps, and an acquisition matrix of 96 x 96 in a FOV of 220 x 220 mm)] TJ ET BT 446.767 537.546 Td /F1 8.7 Tf [(2)] TJ ET BT 451.586 533.658 Td /F1 9.8 Tf [(, resulting in 2.3 mm)] TJ ET BT 539.365 537.546 Td /F1 8.7 Tf [(3)] TJ ET BT 26.250 521.753 Td /F1 9.8 Tf [(isotropic voxels \(inter-slice temporal separation = 155 ms, TE=90 ms, flip angle 90, fat saturation, bandwidth 2003 Hz/pixel\). )] TJ ET BT 26.250 509.848 Td /F1 9.8 Tf [(Each DWI data set consisted of 61 high diffusion-weighted images \(b = 1000 s/mm)] TJ ET BT 383.100 513.736 Td /F1 8.7 Tf [(2)] TJ ET BT 387.919 509.848 Td /F1 9.8 Tf [(\), with diffusion gradients applied along 61 )] TJ ET BT 26.250 497.943 Td /F1 9.8 Tf [(diffusion directions and 7 additional images with minimal diffusion-weighting \(b = 100 s/mm)] TJ ET BT 417.752 501.832 Td /F1 8.7 Tf [(2)] TJ ET BT 422.570 497.943 Td /F1 9.8 Tf [(\). We fit the diffusion tensor using )] TJ ET BT 26.250 486.039 Td /F1 9.8 Tf [(the standard linear least squares fit to the log measurements )] TJ ET 0.267 0.267 0.267 rg BT 290.709 486.039 Td /F1 9.8 Tf [([11])] TJ ET 0.271 0.267 0.267 rg BT 306.972 486.039 Td /F1 9.8 Tf [( which also provides an effective b = 0 image. Data acquisition )] TJ ET BT 26.250 474.134 Td /F1 9.8 Tf [(was cardiac-gated to reduce motion artifacts caused by pulsation of the cerebrospinal fluid )] TJ ET 0.267 0.267 0.267 rg BT 418.054 474.134 Td /F1 9.8 Tf [([12])] TJ ET 0.271 0.267 0.267 rg BT 434.317 474.134 Td /F1 9.8 Tf [(. Diffusion data acquisition time )] TJ ET BT 26.250 462.229 Td /F1 9.8 Tf [(was 22 min on average, depending on heart rate. An additional T1 weighted MDEFT sequence was acquired \(176 slices, 1 mm )] TJ ET BT 26.250 450.324 Td /F1 9.8 Tf [(thickness, sagittal, phase encoding in anterior/posterior, FOV 224 x 256 mm)] TJ ET BT 354.103 454.213 Td /F1 8.7 Tf [(2)] TJ ET BT 358.922 450.324 Td /F1 9.8 Tf [(, matrix 224 x 256, TR=20.66 ms, TE=8.42 ms, )] TJ ET BT 26.250 438.420 Td /F1 9.8 Tf [(TI=640 ms, flip angle 25, fat saturation, bandwidth 178 Hz/pixel\) )] TJ ET 0.267 0.267 0.267 rg BT 308.435 438.420 Td /F1 9.8 Tf [([13])] TJ ET 0.271 0.267 0.267 rg BT 324.697 438.420 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 419.015 Td /F4 9.8 Tf [(Table 1:)] TJ ET BT 63.095 419.015 Td /F1 9.8 Tf [( demographic details for the subjects.)] TJ ET 1.000 1.000 1.000 rg 26.250 229.884 555.000 179.250 re f 0.267 0.267 0.267 rg 26.625 408.009 167.356 0.750 re f 26.625 392.128 0.750 16.631 re f 193.231 408.009 84.796 0.750 re f 193.231 392.128 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 398.154 Td /F4 9.8 Tf [(1.5 T)] TJ ET 0.267 0.267 0.267 rg 277.277 408.009 78.856 0.750 re f 277.277 392.128 0.750 16.631 re f 355.383 408.009 83.167 0.750 re f 355.383 392.128 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 398.154 Td /F4 9.8 Tf [(3.0 T)] TJ ET 0.267 0.267 0.267 rg 437.800 408.009 74.623 0.750 re f 437.800 392.128 0.750 16.631 re f 511.673 408.009 69.202 0.750 re f 511.673 392.128 0.750 16.631 re f 580.125 392.128 0.750 16.631 re f 26.625 392.128 167.356 0.750 re f 26.625 376.247 0.750 16.631 re f 193.231 392.128 84.796 0.750 re f 193.231 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 382.273 Td /F4 9.8 Tf [(Controls)] TJ ET 0.267 0.267 0.267 rg 277.277 392.128 78.856 0.750 re f 277.277 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 382.273 Td /F4 9.8 Tf [(PM)] TJ ET 0.267 0.267 0.267 rg 355.383 392.128 83.167 0.750 re f 355.383 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 382.273 Td /F4 9.8 Tf [(Controls)] TJ ET 0.267 0.267 0.267 rg 437.800 392.128 74.623 0.750 re f 437.800 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 382.273 Td /F4 9.8 Tf [(PM)] TJ ET 0.267 0.267 0.267 rg 511.673 392.128 69.202 0.750 re f 511.673 376.247 0.750 16.631 re f 580.125 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 382.273 Td /F4 9.8 Tf [(HD)] TJ ET 0.267 0.267 0.267 rg 26.625 376.247 167.356 0.750 re f 26.625 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 366.392 Td /F1 9.8 Tf [(N \(f/m\))] TJ ET 0.267 0.267 0.267 rg 193.231 376.247 84.796 0.750 re f 193.231 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 366.392 Td /F1 9.8 Tf [(30 \(15/15\))] TJ ET 0.267 0.267 0.267 rg 277.277 376.247 78.856 0.750 re f 277.277 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 366.392 Td /F1 9.8 Tf [(29 \(16/13\))] TJ ET 0.267 0.267 0.267 rg 355.383 376.247 83.167 0.750 re f 355.383 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 366.392 Td /F1 9.8 Tf [(22 \(11/11\))] TJ ET 0.267 0.267 0.267 rg 437.800 376.247 74.623 0.750 re f 437.800 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 366.392 Td /F1 9.8 Tf [(23 \(11/12\))] TJ ET 0.267 0.267 0.267 rg 511.673 376.247 69.202 0.750 re f 511.673 360.365 0.750 16.631 re f 580.125 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 366.392 Td /F1 9.8 Tf [(18 \(10/8\))] TJ ET 0.267 0.267 0.267 rg 26.625 360.365 167.356 0.750 re f 26.625 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 350.510 Td /F1 9.8 Tf [(Mean Age \(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 360.365 84.796 0.750 re f 193.231 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 350.510 Td /F1 9.8 Tf [(37.2 \(10.0\))] TJ ET 0.267 0.267 0.267 rg 277.277 360.365 78.856 0.750 re f 277.277 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 350.510 Td /F1 9.8 Tf [(40.5 \(8.7\))] TJ ET 0.267 0.267 0.267 rg 355.383 360.365 83.167 0.750 re f 355.383 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 350.510 Td /F1 9.8 Tf [(41.7 \(7.8\))] TJ ET 0.267 0.267 0.267 rg 437.800 360.365 74.623 0.750 re f 437.800 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 350.510 Td /F1 9.8 Tf [(41.6 \(7.7\)*)] TJ ET 0.267 0.267 0.267 rg 511.673 360.365 69.202 0.750 re f 511.673 344.484 0.750 16.631 re f 580.125 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 350.510 Td /F1 9.8 Tf [(48.8 \(8.8\)*)] TJ ET 0.267 0.267 0.267 rg 26.625 344.484 167.356 0.750 re f 26.625 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 334.629 Td /F1 9.8 Tf [(Median CAG \(Range\))] TJ ET 0.267 0.267 0.267 rg 193.231 344.484 84.796 0.750 re f 193.231 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 344.484 78.856 0.750 re f 277.277 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 334.629 Td /F1 9.8 Tf [(42 \(39-47\)**)] TJ ET 0.267 0.267 0.267 rg 355.383 344.484 83.167 0.750 re f 355.383 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 344.484 74.623 0.750 re f 437.800 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 334.629 Td /F1 9.8 Tf [(43 \(40-47\))] TJ ET 0.267 0.267 0.267 rg 511.673 344.484 69.202 0.750 re f 511.673 328.603 0.750 16.631 re f 580.125 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 26.625 328.603 167.356 0.750 re f 26.625 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 31.875 318.748 Td /F1 9.8 Tf [(Mean years to onset/ disease )] TJ ET BT 31.875 311.116 Td /F1 9.8 Tf [(duration \(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 328.603 84.796 0.750 re f 193.231 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 198.481 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 328.603 78.856 0.750 re f 277.277 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 282.527 318.748 Td /F1 9.8 Tf [(16.1 \(8.4\)**)] TJ ET 0.267 0.267 0.267 rg 355.383 328.603 83.167 0.750 re f 355.383 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 360.633 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 328.603 74.623 0.750 re f 437.800 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 443.050 318.748 Td /F1 9.8 Tf [(12 \(4.0\))] TJ ET 0.267 0.267 0.267 rg 511.673 328.603 69.202 0.750 re f 511.673 305.090 0.750 24.263 re f 580.125 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 516.923 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 26.625 305.090 167.356 0.750 re f 26.625 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 295.235 Td /F1 9.8 Tf [(Median UHDRS motor \(range\))] TJ ET 0.267 0.267 0.267 rg 193.231 305.090 84.796 0.750 re f 193.231 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 295.235 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 305.090 78.856 0.750 re f 277.277 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 295.235 Td /F1 9.8 Tf [(4 \(0-17\))] TJ ET 0.267 0.267 0.267 rg 355.383 305.090 83.167 0.750 re f 355.383 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 295.235 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 305.090 74.623 0.750 re f 437.800 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 295.235 Td /F1 9.8 Tf [(4.5 \(0-10\))] TJ ET 0.267 0.267 0.267 rg 511.673 305.090 69.202 0.750 re f 511.673 289.209 0.750 16.631 re f 580.125 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 295.235 Td /F1 9.8 Tf [(33 \(10-48\))] TJ ET 0.267 0.267 0.267 rg 26.625 289.209 167.356 0.750 re f 26.625 265.696 167.356 0.750 re f 26.625 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 31.875 279.354 Td /F1 9.8 Tf [(Mean duration of disease \(months, )] TJ ET BT 31.875 271.723 Td /F1 9.8 Tf [(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 289.209 84.796 0.750 re f 193.231 265.696 84.796 0.750 re f 193.231 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 198.481 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 289.209 78.856 0.750 re f 277.277 265.696 78.856 0.750 re f 277.277 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 282.527 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 355.383 289.209 83.167 0.750 re f 355.383 265.696 83.167 0.750 re f 355.383 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 360.633 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 289.209 74.623 0.750 re f 437.800 265.696 74.623 0.750 re f 437.800 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 443.050 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 511.673 289.209 69.202 0.750 re f 511.673 265.696 69.202 0.750 re f 511.673 265.696 0.750 24.263 re f 580.125 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 516.923 279.354 Td /F1 9.8 Tf [(42 \(30.0\))] TJ ET BT 26.250 182.860 Td /F1 9.8 Tf [(*Significant age difference **exact CAG length missing from two subjects)] TJ ET BT 26.250 163.455 Td /F4 9.8 Tf [(3 Tesla data)] TJ ET BT 26.250 144.051 Td /F1 9.8 Tf [(The second group included 22 premanifest, 18 early affected subjects, and 23 controls. All data were acquired on the same )] TJ ET BT 26.250 132.146 Td /F1 9.8 Tf [(Siemens TRIO 3 Tesla scanner. The sequence consisted of 72 diffusion-weighted scans, each with dimensions of 96 pixels x )] TJ ET BT 26.250 120.241 Td /F1 9.8 Tf [(96 pixels x 55 slices per volume with a 2.3 mm isotropic voxel size; 64 unique diffusion gradient directions \(b = 1000 s/mm)] TJ ET BT 552.145 124.129 Td /F1 8.7 Tf [(2)] TJ ET BT 556.964 120.241 Td /F1 9.8 Tf [(\) )] TJ ET BT 26.250 108.336 Td /F1 9.8 Tf [(and eight b = 100 s/mm)] TJ ET BT 128.411 112.225 Td /F1 8.7 Tf [(2)] TJ ET BT 133.229 108.336 Td /F1 9.8 Tf [( images; TE was 90 ms. A T1-weighted image was acquired using a 3D MPRAGE acquisition )] TJ ET BT 26.250 96.432 Td /F1 9.8 Tf [(sequence with the following imaging parameters: TR = 2200 ms, TE=2.2 ms \(S\)/3.5ms \(P\), FA=10\(S\)/8\(P\), FOV=280 x 280 )] TJ ET BT 26.250 84.527 Td /F1 9.8 Tf [(mm)] TJ ET BT 42.493 88.415 Td /F1 8.7 Tf [(2)] TJ ET BT 47.312 84.527 Td /F1 9.8 Tf [(, matrix = 256256 with 208 sagittal slices to cover the entire brain with a slice thickness of 1.0 mm with no gap. The 3T )] TJ ET BT 26.250 72.622 Td /F1 9.8 Tf [(MRI scans were acquired as part of the London site TRACK-HD cohort \(see also acknowledgment\).)] TJ ET BT 26.250 53.217 Td /F4 9.8 Tf [(2-D artifact correction \(QC\))] TJ ET Q q 15.000 43.336 577.500 733.664 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(signal dropouts \(cf. Figure 1\).)] TJ ET BT 26.250 748.071 Td /F1 9.8 Tf [(Using DWI data from different stages of HD, we explored a weighted average approach to detect artifacts in two dimensions )] TJ ET BT 26.250 736.167 Td /F1 9.8 Tf [(\(slicewise approach\): For each gradient direction, the weighted variance was computed from all remaining directions in the )] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(sequence by weighting with the angle in which they differ from the index gradient direction. This novel approach was applied to )] TJ ET BT 26.250 712.357 Td /F1 9.8 Tf [(data acquired with different field strengths \(i.e., 1.5 and 3 Tesla\).)] TJ ET BT 26.250 675.755 Td /F4 12.0 Tf [(Material and Methods)] TJ ET BT 26.250 655.800 Td /F1 9.8 Tf [(Data from two scanners were used. Table 1 provides demographic details and the motor scale of the Unified Huntingtons )] TJ ET BT 26.250 643.896 Td /F1 9.8 Tf [(Disease Rating Scale \(UHDRS\) for the subjects. It also provides the estimated years to the onset of typical motor signs, based )] TJ ET BT 26.250 631.991 Td /F1 9.8 Tf [(on CAG repeat length and age at a 60% certainty level )] TJ ET 0.267 0.267 0.267 rg BT 264.716 631.991 Td /F1 9.8 Tf [([9])] TJ ET 0.271 0.267 0.267 rg BT 275.558 631.991 Td /F1 9.8 Tf [(. Given the purpose of this study, we ignored the outcome of a visual )] TJ ET BT 26.250 620.086 Td /F1 9.8 Tf [(data inspection step which would have led to the exclusion of subjects with extensive artifacts. The study was approved by the )] TJ ET BT 26.250 608.181 Td /F1 9.8 Tf [(local ethics committees, and written informed consent was obtained from each subject.)] TJ ET BT 26.250 588.777 Td /F4 9.8 Tf [(1.5 Tesla Data)] TJ ET BT 26.250 569.372 Td /F1 9.8 Tf [(Twenty-nine premanifest HD patients and 30 controls were scanned on the same Siemens Sonata 1.5 Tesla scanner \(a )] TJ ET BT 26.250 557.467 Td /F1 9.8 Tf [(subgroup of this cohort has been reported in our earlier work )] TJ ET 0.267 0.267 0.267 rg BT 290.163 557.467 Td /F1 9.8 Tf [([6])] TJ ET 0.271 0.267 0.267 rg BT 301.005 557.467 Td /F1 9.8 Tf [(\). DWI was performed with an echo planar sequence with a )] TJ ET BT 26.250 545.562 Td /F1 9.8 Tf [(double spin-echo module to reduce the effect of eddy currents )] TJ ET 0.267 0.267 0.267 rg BT 296.686 545.562 Td /F1 9.8 Tf [([10])] TJ ET 0.271 0.267 0.267 rg BT 312.949 545.562 Td /F1 9.8 Tf [(. Each data volume consisted of 40 axial slices of 2.3 mm )] TJ ET BT 26.250 533.658 Td /F1 9.8 Tf [(thickness, with no inter-slice gaps, and an acquisition matrix of 96 x 96 in a FOV of 220 x 220 mm)] TJ ET BT 446.767 537.546 Td /F1 8.7 Tf [(2)] TJ ET BT 451.586 533.658 Td /F1 9.8 Tf [(, resulting in 2.3 mm)] TJ ET BT 539.365 537.546 Td /F1 8.7 Tf [(3)] TJ ET BT 26.250 521.753 Td /F1 9.8 Tf [(isotropic voxels \(inter-slice temporal separation = 155 ms, TE=90 ms, flip angle 90, fat saturation, bandwidth 2003 Hz/pixel\). )] TJ ET BT 26.250 509.848 Td /F1 9.8 Tf [(Each DWI data set consisted of 61 high diffusion-weighted images \(b = 1000 s/mm)] TJ ET BT 383.100 513.736 Td /F1 8.7 Tf [(2)] TJ ET BT 387.919 509.848 Td /F1 9.8 Tf [(\), with diffusion gradients applied along 61 )] TJ ET BT 26.250 497.943 Td /F1 9.8 Tf [(diffusion directions and 7 additional images with minimal diffusion-weighting \(b = 100 s/mm)] TJ ET BT 417.752 501.832 Td /F1 8.7 Tf [(2)] TJ ET BT 422.570 497.943 Td /F1 9.8 Tf [(\). We fit the diffusion tensor using )] TJ ET BT 26.250 486.039 Td /F1 9.8 Tf [(the standard linear least squares fit to the log measurements )] TJ ET 0.267 0.267 0.267 rg BT 290.709 486.039 Td /F1 9.8 Tf [([11])] TJ ET 0.271 0.267 0.267 rg BT 306.972 486.039 Td /F1 9.8 Tf [( which also provides an effective b = 0 image. Data acquisition )] TJ ET BT 26.250 474.134 Td /F1 9.8 Tf [(was cardiac-gated to reduce motion artifacts caused by pulsation of the cerebrospinal fluid )] TJ ET 0.267 0.267 0.267 rg BT 418.054 474.134 Td /F1 9.8 Tf [([12])] TJ ET 0.271 0.267 0.267 rg BT 434.317 474.134 Td /F1 9.8 Tf [(. Diffusion data acquisition time )] TJ ET BT 26.250 462.229 Td /F1 9.8 Tf [(was 22 min on average, depending on heart rate. An additional T1 weighted MDEFT sequence was acquired \(176 slices, 1 mm )] TJ ET BT 26.250 450.324 Td /F1 9.8 Tf [(thickness, sagittal, phase encoding in anterior/posterior, FOV 224 x 256 mm)] TJ ET BT 354.103 454.213 Td /F1 8.7 Tf [(2)] TJ ET BT 358.922 450.324 Td /F1 9.8 Tf [(, matrix 224 x 256, TR=20.66 ms, TE=8.42 ms, )] TJ ET BT 26.250 438.420 Td /F1 9.8 Tf [(TI=640 ms, flip angle 25, fat saturation, bandwidth 178 Hz/pixel\) )] TJ ET 0.267 0.267 0.267 rg BT 308.435 438.420 Td /F1 9.8 Tf [([13])] TJ ET 0.271 0.267 0.267 rg BT 324.697 438.420 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 419.015 Td /F4 9.8 Tf [(Table 1:)] TJ ET BT 63.095 419.015 Td /F1 9.8 Tf [( demographic details for the subjects.)] TJ ET 1.000 1.000 1.000 rg 26.250 229.884 555.000 179.250 re f 0.267 0.267 0.267 rg 26.625 408.009 167.356 0.750 re f 26.625 392.128 0.750 16.631 re f 193.231 408.009 84.796 0.750 re f 193.231 392.128 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 398.154 Td /F4 9.8 Tf [(1.5 T)] TJ ET 0.267 0.267 0.267 rg 277.277 408.009 78.856 0.750 re f 277.277 392.128 0.750 16.631 re f 355.383 408.009 83.167 0.750 re f 355.383 392.128 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 398.154 Td /F4 9.8 Tf [(3.0 T)] TJ ET 0.267 0.267 0.267 rg 437.800 408.009 74.623 0.750 re f 437.800 392.128 0.750 16.631 re f 511.673 408.009 69.202 0.750 re f 511.673 392.128 0.750 16.631 re f 580.125 392.128 0.750 16.631 re f 26.625 392.128 167.356 0.750 re f 26.625 376.247 0.750 16.631 re f 193.231 392.128 84.796 0.750 re f 193.231 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 382.273 Td /F4 9.8 Tf [(Controls)] TJ ET 0.267 0.267 0.267 rg 277.277 392.128 78.856 0.750 re f 277.277 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 382.273 Td /F4 9.8 Tf [(PM)] TJ ET 0.267 0.267 0.267 rg 355.383 392.128 83.167 0.750 re f 355.383 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 382.273 Td /F4 9.8 Tf [(Controls)] TJ ET 0.267 0.267 0.267 rg 437.800 392.128 74.623 0.750 re f 437.800 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 382.273 Td /F4 9.8 Tf [(PM)] TJ ET 0.267 0.267 0.267 rg 511.673 392.128 69.202 0.750 re f 511.673 376.247 0.750 16.631 re f 580.125 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 382.273 Td /F4 9.8 Tf [(HD)] TJ ET 0.267 0.267 0.267 rg 26.625 376.247 167.356 0.750 re f 26.625 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 366.392 Td /F1 9.8 Tf [(N \(f/m\))] TJ ET 0.267 0.267 0.267 rg 193.231 376.247 84.796 0.750 re f 193.231 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 366.392 Td /F1 9.8 Tf [(30 \(15/15\))] TJ ET 0.267 0.267 0.267 rg 277.277 376.247 78.856 0.750 re f 277.277 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 366.392 Td /F1 9.8 Tf [(29 \(16/13\))] TJ ET 0.267 0.267 0.267 rg 355.383 376.247 83.167 0.750 re f 355.383 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 366.392 Td /F1 9.8 Tf [(22 \(11/11\))] TJ ET 0.267 0.267 0.267 rg 437.800 376.247 74.623 0.750 re f 437.800 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 366.392 Td /F1 9.8 Tf [(23 \(11/12\))] TJ ET 0.267 0.267 0.267 rg 511.673 376.247 69.202 0.750 re f 511.673 360.365 0.750 16.631 re f 580.125 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 366.392 Td /F1 9.8 Tf [(18 \(10/8\))] TJ ET 0.267 0.267 0.267 rg 26.625 360.365 167.356 0.750 re f 26.625 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 350.510 Td /F1 9.8 Tf [(Mean Age \(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 360.365 84.796 0.750 re f 193.231 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 350.510 Td /F1 9.8 Tf [(37.2 \(10.0\))] TJ ET 0.267 0.267 0.267 rg 277.277 360.365 78.856 0.750 re f 277.277 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 350.510 Td /F1 9.8 Tf [(40.5 \(8.7\))] TJ ET 0.267 0.267 0.267 rg 355.383 360.365 83.167 0.750 re f 355.383 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 350.510 Td /F1 9.8 Tf [(41.7 \(7.8\))] TJ ET 0.267 0.267 0.267 rg 437.800 360.365 74.623 0.750 re f 437.800 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 350.510 Td /F1 9.8 Tf [(41.6 \(7.7\)*)] TJ ET 0.267 0.267 0.267 rg 511.673 360.365 69.202 0.750 re f 511.673 344.484 0.750 16.631 re f 580.125 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 350.510 Td /F1 9.8 Tf [(48.8 \(8.8\)*)] TJ ET 0.267 0.267 0.267 rg 26.625 344.484 167.356 0.750 re f 26.625 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 334.629 Td /F1 9.8 Tf [(Median CAG \(Range\))] TJ ET 0.267 0.267 0.267 rg 193.231 344.484 84.796 0.750 re f 193.231 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 344.484 78.856 0.750 re f 277.277 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 334.629 Td /F1 9.8 Tf [(42 \(39-47\)**)] TJ ET 0.267 0.267 0.267 rg 355.383 344.484 83.167 0.750 re f 355.383 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 344.484 74.623 0.750 re f 437.800 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 334.629 Td /F1 9.8 Tf [(43 \(40-47\))] TJ ET 0.267 0.267 0.267 rg 511.673 344.484 69.202 0.750 re f 511.673 328.603 0.750 16.631 re f 580.125 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 26.625 328.603 167.356 0.750 re f 26.625 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 31.875 318.748 Td /F1 9.8 Tf [(Mean years to onset/ disease )] TJ ET BT 31.875 311.116 Td /F1 9.8 Tf [(duration \(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 328.603 84.796 0.750 re f 193.231 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 198.481 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 328.603 78.856 0.750 re f 277.277 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 282.527 318.748 Td /F1 9.8 Tf [(16.1 \(8.4\)**)] TJ ET 0.267 0.267 0.267 rg 355.383 328.603 83.167 0.750 re f 355.383 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 360.633 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 328.603 74.623 0.750 re f 437.800 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 443.050 318.748 Td /F1 9.8 Tf [(12 \(4.0\))] TJ ET 0.267 0.267 0.267 rg 511.673 328.603 69.202 0.750 re f 511.673 305.090 0.750 24.263 re f 580.125 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 516.923 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 26.625 305.090 167.356 0.750 re f 26.625 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 295.235 Td /F1 9.8 Tf [(Median UHDRS motor \(range\))] TJ ET 0.267 0.267 0.267 rg 193.231 305.090 84.796 0.750 re f 193.231 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 295.235 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 305.090 78.856 0.750 re f 277.277 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 295.235 Td /F1 9.8 Tf [(4 \(0-17\))] TJ ET 0.267 0.267 0.267 rg 355.383 305.090 83.167 0.750 re f 355.383 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 295.235 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 305.090 74.623 0.750 re f 437.800 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 295.235 Td /F1 9.8 Tf [(4.5 \(0-10\))] TJ ET 0.267 0.267 0.267 rg 511.673 305.090 69.202 0.750 re f 511.673 289.209 0.750 16.631 re f 580.125 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 295.235 Td /F1 9.8 Tf [(33 \(10-48\))] TJ ET 0.267 0.267 0.267 rg 26.625 289.209 167.356 0.750 re f 26.625 265.696 167.356 0.750 re f 26.625 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 31.875 279.354 Td /F1 9.8 Tf [(Mean duration of disease \(months, )] TJ ET BT 31.875 271.723 Td /F1 9.8 Tf [(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 289.209 84.796 0.750 re f 193.231 265.696 84.796 0.750 re f 193.231 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 198.481 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 289.209 78.856 0.750 re f 277.277 265.696 78.856 0.750 re f 277.277 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 282.527 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 355.383 289.209 83.167 0.750 re f 355.383 265.696 83.167 0.750 re f 355.383 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 360.633 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 289.209 74.623 0.750 re f 437.800 265.696 74.623 0.750 re f 437.800 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 443.050 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 511.673 289.209 69.202 0.750 re f 511.673 265.696 69.202 0.750 re f 511.673 265.696 0.750 24.263 re f 580.125 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 516.923 279.354 Td /F1 9.8 Tf [(42 \(30.0\))] TJ ET BT 26.250 182.860 Td /F1 9.8 Tf [(*Significant age difference **exact CAG length missing from two subjects)] TJ ET BT 26.250 163.455 Td /F4 9.8 Tf [(3 Tesla data)] TJ ET BT 26.250 144.051 Td /F1 9.8 Tf [(The second group included 22 premanifest, 18 early affected subjects, and 23 controls. All data were acquired on the same )] TJ ET BT 26.250 132.146 Td /F1 9.8 Tf [(Siemens TRIO 3 Tesla scanner. The sequence consisted of 72 diffusion-weighted scans, each with dimensions of 96 pixels x )] TJ ET BT 26.250 120.241 Td /F1 9.8 Tf [(96 pixels x 55 slices per volume with a 2.3 mm isotropic voxel size; 64 unique diffusion gradient directions \(b = 1000 s/mm)] TJ ET BT 552.145 124.129 Td /F1 8.7 Tf [(2)] TJ ET BT 556.964 120.241 Td /F1 9.8 Tf [(\) )] TJ ET BT 26.250 108.336 Td /F1 9.8 Tf [(and eight b = 100 s/mm)] TJ ET BT 128.411 112.225 Td /F1 8.7 Tf [(2)] TJ ET BT 133.229 108.336 Td /F1 9.8 Tf [( images; TE was 90 ms. A T1-weighted image was acquired using a 3D MPRAGE acquisition )] TJ ET BT 26.250 96.432 Td /F1 9.8 Tf [(sequence with the following imaging parameters: TR = 2200 ms, TE=2.2 ms \(S\)/3.5ms \(P\), FA=10\(S\)/8\(P\), FOV=280 x 280 )] TJ ET BT 26.250 84.527 Td /F1 9.8 Tf [(mm)] TJ ET BT 42.493 88.415 Td /F1 8.7 Tf [(2)] TJ ET BT 47.312 84.527 Td /F1 9.8 Tf [(, matrix = 256256 with 208 sagittal slices to cover the entire brain with a slice thickness of 1.0 mm with no gap. The 3T )] TJ ET BT 26.250 72.622 Td /F1 9.8 Tf [(MRI scans were acquired as part of the London site TRACK-HD cohort \(see also acknowledgment\).)] TJ ET BT 26.250 53.217 Td /F4 9.8 Tf [(2-D artifact correction \(QC\))] TJ ET Q q 15.000 43.336 577.500 733.664 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(signal dropouts \(cf. Figure 1\).)] TJ ET BT 26.250 748.071 Td /F1 9.8 Tf [(Using DWI data from different stages of HD, we explored a weighted average approach to detect artifacts in two dimensions )] TJ ET BT 26.250 736.167 Td /F1 9.8 Tf [(\(slicewise approach\): For each gradient direction, the weighted variance was computed from all remaining directions in the )] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(sequence by weighting with the angle in which they differ from the index gradient direction. This novel approach was applied to )] TJ ET BT 26.250 712.357 Td /F1 9.8 Tf [(data acquired with different field strengths \(i.e., 1.5 and 3 Tesla\).)] TJ ET BT 26.250 675.755 Td /F4 12.0 Tf [(Material and Methods)] TJ ET BT 26.250 655.800 Td /F1 9.8 Tf [(Data from two scanners were used. Table 1 provides demographic details and the motor scale of the Unified Huntingtons )] TJ ET BT 26.250 643.896 Td /F1 9.8 Tf [(Disease Rating Scale \(UHDRS\) for the subjects. It also provides the estimated years to the onset of typical motor signs, based )] TJ ET BT 26.250 631.991 Td /F1 9.8 Tf [(on CAG repeat length and age at a 60% certainty level )] TJ ET 0.267 0.267 0.267 rg BT 264.716 631.991 Td /F1 9.8 Tf [([9])] TJ ET 0.271 0.267 0.267 rg BT 275.558 631.991 Td /F1 9.8 Tf [(. Given the purpose of this study, we ignored the outcome of a visual )] TJ ET BT 26.250 620.086 Td /F1 9.8 Tf [(data inspection step which would have led to the exclusion of subjects with extensive artifacts. The study was approved by the )] TJ ET BT 26.250 608.181 Td /F1 9.8 Tf [(local ethics committees, and written informed consent was obtained from each subject.)] TJ ET BT 26.250 588.777 Td /F4 9.8 Tf [(1.5 Tesla Data)] TJ ET BT 26.250 569.372 Td /F1 9.8 Tf [(Twenty-nine premanifest HD patients and 30 controls were scanned on the same Siemens Sonata 1.5 Tesla scanner \(a )] TJ ET BT 26.250 557.467 Td /F1 9.8 Tf [(subgroup of this cohort has been reported in our earlier work )] TJ ET 0.267 0.267 0.267 rg BT 290.163 557.467 Td /F1 9.8 Tf [([6])] TJ ET 0.271 0.267 0.267 rg BT 301.005 557.467 Td /F1 9.8 Tf [(\). DWI was performed with an echo planar sequence with a )] TJ ET BT 26.250 545.562 Td /F1 9.8 Tf [(double spin-echo module to reduce the effect of eddy currents )] TJ ET 0.267 0.267 0.267 rg BT 296.686 545.562 Td /F1 9.8 Tf [([10])] TJ ET 0.271 0.267 0.267 rg BT 312.949 545.562 Td /F1 9.8 Tf [(. Each data volume consisted of 40 axial slices of 2.3 mm )] TJ ET BT 26.250 533.658 Td /F1 9.8 Tf [(thickness, with no inter-slice gaps, and an acquisition matrix of 96 x 96 in a FOV of 220 x 220 mm)] TJ ET BT 446.767 537.546 Td /F1 8.7 Tf [(2)] TJ ET BT 451.586 533.658 Td /F1 9.8 Tf [(, resulting in 2.3 mm)] TJ ET BT 539.365 537.546 Td /F1 8.7 Tf [(3)] TJ ET BT 26.250 521.753 Td /F1 9.8 Tf [(isotropic voxels \(inter-slice temporal separation = 155 ms, TE=90 ms, flip angle 90, fat saturation, bandwidth 2003 Hz/pixel\). )] TJ ET BT 26.250 509.848 Td /F1 9.8 Tf [(Each DWI data set consisted of 61 high diffusion-weighted images \(b = 1000 s/mm)] TJ ET BT 383.100 513.736 Td /F1 8.7 Tf [(2)] TJ ET BT 387.919 509.848 Td /F1 9.8 Tf [(\), with diffusion gradients applied along 61 )] TJ ET BT 26.250 497.943 Td /F1 9.8 Tf [(diffusion directions and 7 additional images with minimal diffusion-weighting \(b = 100 s/mm)] TJ ET BT 417.752 501.832 Td /F1 8.7 Tf [(2)] TJ ET BT 422.570 497.943 Td /F1 9.8 Tf [(\). We fit the diffusion tensor using )] TJ ET BT 26.250 486.039 Td /F1 9.8 Tf [(the standard linear least squares fit to the log measurements )] TJ ET 0.267 0.267 0.267 rg BT 290.709 486.039 Td /F1 9.8 Tf [([11])] TJ ET 0.271 0.267 0.267 rg BT 306.972 486.039 Td /F1 9.8 Tf [( which also provides an effective b = 0 image. Data acquisition )] TJ ET BT 26.250 474.134 Td /F1 9.8 Tf [(was cardiac-gated to reduce motion artifacts caused by pulsation of the cerebrospinal fluid )] TJ ET 0.267 0.267 0.267 rg BT 418.054 474.134 Td /F1 9.8 Tf [([12])] TJ ET 0.271 0.267 0.267 rg BT 434.317 474.134 Td /F1 9.8 Tf [(. Diffusion data acquisition time )] TJ ET BT 26.250 462.229 Td /F1 9.8 Tf [(was 22 min on average, depending on heart rate. An additional T1 weighted MDEFT sequence was acquired \(176 slices, 1 mm )] TJ ET BT 26.250 450.324 Td /F1 9.8 Tf [(thickness, sagittal, phase encoding in anterior/posterior, FOV 224 x 256 mm)] TJ ET BT 354.103 454.213 Td /F1 8.7 Tf [(2)] TJ ET BT 358.922 450.324 Td /F1 9.8 Tf [(, matrix 224 x 256, TR=20.66 ms, TE=8.42 ms, )] TJ ET BT 26.250 438.420 Td /F1 9.8 Tf [(TI=640 ms, flip angle 25, fat saturation, bandwidth 178 Hz/pixel\) )] TJ ET 0.267 0.267 0.267 rg BT 308.435 438.420 Td /F1 9.8 Tf [([13])] TJ ET 0.271 0.267 0.267 rg BT 324.697 438.420 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 419.015 Td /F4 9.8 Tf [(Table 1:)] TJ ET BT 63.095 419.015 Td /F1 9.8 Tf [( demographic details for the subjects.)] TJ ET 1.000 1.000 1.000 rg 26.250 229.884 555.000 179.250 re f 0.267 0.267 0.267 rg 26.625 408.009 167.356 0.750 re f 26.625 392.128 0.750 16.631 re f 193.231 408.009 84.796 0.750 re f 193.231 392.128 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 398.154 Td /F4 9.8 Tf [(1.5 T)] TJ ET 0.267 0.267 0.267 rg 277.277 408.009 78.856 0.750 re f 277.277 392.128 0.750 16.631 re f 355.383 408.009 83.167 0.750 re f 355.383 392.128 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 398.154 Td /F4 9.8 Tf [(3.0 T)] TJ ET 0.267 0.267 0.267 rg 437.800 408.009 74.623 0.750 re f 437.800 392.128 0.750 16.631 re f 511.673 408.009 69.202 0.750 re f 511.673 392.128 0.750 16.631 re f 580.125 392.128 0.750 16.631 re f 26.625 392.128 167.356 0.750 re f 26.625 376.247 0.750 16.631 re f 193.231 392.128 84.796 0.750 re f 193.231 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 382.273 Td /F4 9.8 Tf [(Controls)] TJ ET 0.267 0.267 0.267 rg 277.277 392.128 78.856 0.750 re f 277.277 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 382.273 Td /F4 9.8 Tf [(PM)] TJ ET 0.267 0.267 0.267 rg 355.383 392.128 83.167 0.750 re f 355.383 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 382.273 Td /F4 9.8 Tf [(Controls)] TJ ET 0.267 0.267 0.267 rg 437.800 392.128 74.623 0.750 re f 437.800 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 382.273 Td /F4 9.8 Tf [(PM)] TJ ET 0.267 0.267 0.267 rg 511.673 392.128 69.202 0.750 re f 511.673 376.247 0.750 16.631 re f 580.125 376.247 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 382.273 Td /F4 9.8 Tf [(HD)] TJ ET 0.267 0.267 0.267 rg 26.625 376.247 167.356 0.750 re f 26.625 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 366.392 Td /F1 9.8 Tf [(N \(f/m\))] TJ ET 0.267 0.267 0.267 rg 193.231 376.247 84.796 0.750 re f 193.231 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 366.392 Td /F1 9.8 Tf [(30 \(15/15\))] TJ ET 0.267 0.267 0.267 rg 277.277 376.247 78.856 0.750 re f 277.277 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 366.392 Td /F1 9.8 Tf [(29 \(16/13\))] TJ ET 0.267 0.267 0.267 rg 355.383 376.247 83.167 0.750 re f 355.383 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 366.392 Td /F1 9.8 Tf [(22 \(11/11\))] TJ ET 0.267 0.267 0.267 rg 437.800 376.247 74.623 0.750 re f 437.800 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 366.392 Td /F1 9.8 Tf [(23 \(11/12\))] TJ ET 0.267 0.267 0.267 rg 511.673 376.247 69.202 0.750 re f 511.673 360.365 0.750 16.631 re f 580.125 360.365 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 366.392 Td /F1 9.8 Tf [(18 \(10/8\))] TJ ET 0.267 0.267 0.267 rg 26.625 360.365 167.356 0.750 re f 26.625 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 350.510 Td /F1 9.8 Tf [(Mean Age \(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 360.365 84.796 0.750 re f 193.231 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 350.510 Td /F1 9.8 Tf [(37.2 \(10.0\))] TJ ET 0.267 0.267 0.267 rg 277.277 360.365 78.856 0.750 re f 277.277 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 350.510 Td /F1 9.8 Tf [(40.5 \(8.7\))] TJ ET 0.267 0.267 0.267 rg 355.383 360.365 83.167 0.750 re f 355.383 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 350.510 Td /F1 9.8 Tf [(41.7 \(7.8\))] TJ ET 0.267 0.267 0.267 rg 437.800 360.365 74.623 0.750 re f 437.800 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 350.510 Td /F1 9.8 Tf [(41.6 \(7.7\)*)] TJ ET 0.267 0.267 0.267 rg 511.673 360.365 69.202 0.750 re f 511.673 344.484 0.750 16.631 re f 580.125 344.484 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 350.510 Td /F1 9.8 Tf [(48.8 \(8.8\)*)] TJ ET 0.267 0.267 0.267 rg 26.625 344.484 167.356 0.750 re f 26.625 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 334.629 Td /F1 9.8 Tf [(Median CAG \(Range\))] TJ ET 0.267 0.267 0.267 rg 193.231 344.484 84.796 0.750 re f 193.231 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 344.484 78.856 0.750 re f 277.277 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 334.629 Td /F1 9.8 Tf [(42 \(39-47\)**)] TJ ET 0.267 0.267 0.267 rg 355.383 344.484 83.167 0.750 re f 355.383 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 344.484 74.623 0.750 re f 437.800 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 334.629 Td /F1 9.8 Tf [(43 \(40-47\))] TJ ET 0.267 0.267 0.267 rg 511.673 344.484 69.202 0.750 re f 511.673 328.603 0.750 16.631 re f 580.125 328.603 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 334.629 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 26.625 328.603 167.356 0.750 re f 26.625 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 31.875 318.748 Td /F1 9.8 Tf [(Mean years to onset/ disease )] TJ ET BT 31.875 311.116 Td /F1 9.8 Tf [(duration \(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 328.603 84.796 0.750 re f 193.231 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 198.481 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 328.603 78.856 0.750 re f 277.277 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 282.527 318.748 Td /F1 9.8 Tf [(16.1 \(8.4\)**)] TJ ET 0.267 0.267 0.267 rg 355.383 328.603 83.167 0.750 re f 355.383 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 360.633 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 328.603 74.623 0.750 re f 437.800 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 443.050 318.748 Td /F1 9.8 Tf [(12 \(4.0\))] TJ ET 0.267 0.267 0.267 rg 511.673 328.603 69.202 0.750 re f 511.673 305.090 0.750 24.263 re f 580.125 305.090 0.750 24.263 re f 0.271 0.267 0.267 rg BT 516.923 318.748 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 26.625 305.090 167.356 0.750 re f 26.625 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 31.875 295.235 Td /F1 9.8 Tf [(Median UHDRS motor \(range\))] TJ ET 0.267 0.267 0.267 rg 193.231 305.090 84.796 0.750 re f 193.231 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 198.481 295.235 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 305.090 78.856 0.750 re f 277.277 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 282.527 295.235 Td /F1 9.8 Tf [(4 \(0-17\))] TJ ET 0.267 0.267 0.267 rg 355.383 305.090 83.167 0.750 re f 355.383 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 360.633 295.235 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 305.090 74.623 0.750 re f 437.800 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 443.050 295.235 Td /F1 9.8 Tf [(4.5 \(0-10\))] TJ ET 0.267 0.267 0.267 rg 511.673 305.090 69.202 0.750 re f 511.673 289.209 0.750 16.631 re f 580.125 289.209 0.750 16.631 re f 0.271 0.267 0.267 rg BT 516.923 295.235 Td /F1 9.8 Tf [(33 \(10-48\))] TJ ET 0.267 0.267 0.267 rg 26.625 289.209 167.356 0.750 re f 26.625 265.696 167.356 0.750 re f 26.625 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 31.875 279.354 Td /F1 9.8 Tf [(Mean duration of disease \(months, )] TJ ET BT 31.875 271.723 Td /F1 9.8 Tf [(SD\))] TJ ET 0.267 0.267 0.267 rg 193.231 289.209 84.796 0.750 re f 193.231 265.696 84.796 0.750 re f 193.231 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 198.481 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 277.277 289.209 78.856 0.750 re f 277.277 265.696 78.856 0.750 re f 277.277 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 282.527 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 355.383 289.209 83.167 0.750 re f 355.383 265.696 83.167 0.750 re f 355.383 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 360.633 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 437.800 289.209 74.623 0.750 re f 437.800 265.696 74.623 0.750 re f 437.800 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 443.050 279.354 Td /F1 9.8 Tf [(NA)] TJ ET 0.267 0.267 0.267 rg 511.673 289.209 69.202 0.750 re f 511.673 265.696 69.202 0.750 re f 511.673 265.696 0.750 24.263 re f 580.125 265.696 0.750 24.263 re f 0.271 0.267 0.267 rg BT 516.923 279.354 Td /F1 9.8 Tf [(42 \(30.0\))] TJ ET BT 26.250 182.860 Td /F1 9.8 Tf [(*Significant age difference **exact CAG length missing from two subjects)] TJ ET BT 26.250 163.455 Td /F4 9.8 Tf [(3 Tesla data)] TJ ET BT 26.250 144.051 Td /F1 9.8 Tf [(The second group included 22 premanifest, 18 early affected subjects, and 23 controls. All data were acquired on the same )] TJ ET BT 26.250 132.146 Td /F1 9.8 Tf [(Siemens TRIO 3 Tesla scanner. The sequence consisted of 72 diffusion-weighted scans, each with dimensions of 96 pixels x )] TJ ET BT 26.250 120.241 Td /F1 9.8 Tf [(96 pixels x 55 slices per volume with a 2.3 mm isotropic voxel size; 64 unique diffusion gradient directions \(b = 1000 s/mm)] TJ ET BT 552.145 124.129 Td /F1 8.7 Tf [(2)] TJ ET BT 556.964 120.241 Td /F1 9.8 Tf [(\) )] TJ ET BT 26.250 108.336 Td /F1 9.8 Tf [(and eight b = 100 s/mm)] TJ ET BT 128.411 112.225 Td /F1 8.7 Tf [(2)] TJ ET BT 133.229 108.336 Td /F1 9.8 Tf [( images; TE was 90 ms. A T1-weighted image was acquired using a 3D MPRAGE acquisition )] TJ ET BT 26.250 96.432 Td /F1 9.8 Tf [(sequence with the following imaging parameters: TR = 2200 ms, TE=2.2 ms \(S\)/3.5ms \(P\), FA=10\(S\)/8\(P\), FOV=280 x 280 )] TJ ET BT 26.250 84.527 Td /F1 9.8 Tf [(mm)] TJ ET BT 42.493 88.415 Td /F1 8.7 Tf [(2)] TJ ET BT 47.312 84.527 Td /F1 9.8 Tf [(, matrix = 256256 with 208 sagittal slices to cover the entire brain with a slice thickness of 1.0 mm with no gap. The 3T )] TJ ET BT 26.250 72.622 Td /F1 9.8 Tf [(MRI scans were acquired as part of the London site TRACK-HD cohort \(see also acknowledgment\).)] TJ ET BT 26.250 53.217 Td /F4 9.8 Tf [(2-D artifact correction \(QC\))] TJ ET Q q 0.000 0.000 0.000 rg BT 291.710 19.825 Td /F1 11.0 Tf [(2)] TJ ET BT 25.000 19.825 Td /F1 11.0 Tf [(PLOS Currents Huntington Disease)] TJ ET Q endstream endobj 160 0 obj << /Type /Annot /Subtype /Link /A 161 0 R /Border [0 0 0] /H /I /Rect [ 264.7155 631.0891 275.5575 641.0097 ] >> endobj 161 0 obj << /Type /Action >> endobj 162 0 obj << /Type /Annot /Subtype /Link /A 163 0 R /Border [0 0 0] /H /I /Rect [ 290.1630 556.5653 301.0050 566.4860 ] >> endobj 163 0 obj << /Type /Action >> endobj 164 0 obj << /Type /Annot /Subtype /Link /A 165 0 R /Border [0 0 0] /H /I /Rect [ 296.6857 544.6606 312.9487 554.5812 ] >> endobj 165 0 obj << /Type /Action >> endobj 166 0 obj << /Type /Annot /Subtype /Link /A 167 0 R /Border [0 0 0] /H /I /Rect [ 290.7090 485.1368 306.9720 495.0575 ] >> endobj 167 0 obj << /Type /Action >> endobj 168 0 obj << /Type /Annot /Subtype /Link /A 169 0 R /Border [0 0 0] /H /I /Rect [ 418.0537 473.2321 434.3167 483.1527 ] >> endobj 169 0 obj << /Type /Action >> endobj 170 0 obj << /Type /Annot /Subtype /Link /A 171 0 R /Border [0 0 0] /H /I /Rect [ 308.4345 437.5178 324.6975 447.4385 ] >> endobj 171 0 obj << /Type /Action >> endobj 172 0 obj << /Type /Annot /Subtype /Link /A 173 0 R /Border [0 0 0] /H /I /Rect [ 264.7155 631.0891 275.5575 641.0097 ] >> endobj 173 0 obj << /Type /Action >> endobj 174 0 obj << /Type /Annot /Subtype /Link /A 175 0 R /Border [0 0 0] /H /I /Rect [ 290.1630 556.5653 301.0050 566.4860 ] >> endobj 175 0 obj << /Type /Action >> endobj 176 0 obj << /Type /Annot /Subtype /Link /A 177 0 R /Border [0 0 0] /H /I /Rect [ 296.6857 544.6606 312.9487 554.5812 ] >> endobj 177 0 obj << /Type /Action >> endobj 178 0 obj << /Type /Annot /Subtype /Link /A 179 0 R /Border [0 0 0] /H /I /Rect [ 290.7090 485.1368 306.9720 495.0575 ] >> endobj 179 0 obj << /Type /Action >> endobj 180 0 obj << /Type /Annot /Subtype /Link /A 181 0 R /Border [0 0 0] /H /I /Rect [ 418.0537 473.2321 434.3167 483.1527 ] >> endobj 181 0 obj << /Type /Action >> endobj 182 0 obj << /Type /Annot /Subtype /Link /A 183 0 R /Border [0 0 0] /H /I /Rect [ 308.4345 437.5178 324.6975 447.4385 ] >> endobj 183 0 obj << /Type /Action >> endobj 184 0 obj << /Type /Annot /Subtype /Link /A 185 0 R /Border [0 0 0] /H /I /Rect [ 264.7155 631.0891 275.5575 641.0097 ] >> endobj 185 0 obj << /Type /Action >> endobj 186 0 obj << /Type /Annot /Subtype /Link /A 187 0 R /Border [0 0 0] /H /I /Rect [ 290.1630 556.5653 301.0050 566.4860 ] >> endobj 187 0 obj << /Type /Action >> endobj 188 0 obj << /Type /Annot /Subtype /Link /A 189 0 R /Border [0 0 0] /H /I /Rect [ 296.6857 544.6606 312.9487 554.5812 ] >> endobj 189 0 obj << /Type /Action >> endobj 190 0 obj << /Type /Annot /Subtype /Link /A 191 0 R /Border [0 0 0] /H /I /Rect [ 290.7090 485.1368 306.9720 495.0575 ] >> endobj 191 0 obj << /Type /Action >> endobj 192 0 obj << /Type /Annot /Subtype /Link /A 193 0 R /Border [0 0 0] /H /I /Rect [ 418.0537 473.2321 434.3167 483.1527 ] >> endobj 193 0 obj << /Type /Action >> endobj 194 0 obj << /Type /Annot /Subtype /Link /A 195 0 R /Border [0 0 0] /H /I /Rect [ 308.4345 437.5178 324.6975 447.4385 ] >> endobj 195 0 obj << /Type /Action >> endobj 196 0 obj << /Type /Page /Parent 3 0 R /Annots [ 212 0 R 214 0 R 216 0 R 218 0 R 234 0 R 236 0 R 238 0 R 240 0 R 256 0 R 258 0 R 260 0 R 262 0 R ] /Contents 197 0 R >> endobj 197 0 obj << /Length 24379 >> stream 0.271 0.267 0.267 rg q 15.000 26.098 577.500 750.902 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(We aimed to detect volumes \(i.e. gradient directions\) with at least one slice showing decreased intensity, i.e. motion artifacts )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(caused by spontaneous subject movement \(Figure 1\). For each diffusion weighted volume, we first computed the mean intensity )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(for each slice and compared this intensity to the same slice in all other volumes by using a weighted average approach. The )] TJ ET BT 26.250 731.762 Td /F1 9.8 Tf [(contribution to this weighted average was the greater the more similar a given direction was to the index direction. Similarity was )] TJ ET BT 26.250 719.857 Td /F1 9.8 Tf [(defined by computing the dot product between two gradient directions \(i.e., a value near 1 reflects great similarity\) which we )] TJ ET BT 26.250 707.952 Td /F1 9.8 Tf [(used as a weighting factor. We employed the following scaling procedure separately for each slice)] TJ ET q 85.500 0 0 37.500 26.250 660.572 cm /I4 Do Q BT 111.750 668.072 Td /F1 9.8 Tf [( \(1\))] TJ ET BT 26.250 639.871 Td /F1 9.8 Tf [(Here, )] TJ ET q 14.250 0 0 16.500 52.799 636.572 cm /I6 Do Q BT 67.049 639.871 Td /F1 9.8 Tf [( denotes the arithmetic average intensity of the slice under observation and )] TJ ET q 12.750 0 0 15.000 393.840 638.072 cm /I8 Do Q BT 406.590 639.871 Td /F1 9.8 Tf [( a slice for comparison. The relative )] TJ ET BT 26.250 623.371 Td /F1 9.8 Tf [(average intensity deviation )] TJ ET q 27.750 0 0 13.500 144.391 623.072 cm /I10 Do Q BT 172.141 623.371 Td /F1 9.8 Tf [( was weighted by the dot product of the gradient direction )] TJ ET q 34.500 0 0 16.500 421.985 620.072 cm /I12 Do Q BT 456.485 623.371 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 603.048 Td /F1 9.8 Tf [(If, for one slice of the volume under observation, the average intensity deviation to all other slices exceeded a certain threshold, )] TJ ET BT 26.250 591.143 Td /F1 9.8 Tf [(the whole volume \(i.e., gradient direction\) from this subject was eliminated.)] TJ ET q 150.000 0 0 24.750 26.250 556.512 cm /I14 Do Q BT 176.250 561.462 Td /F1 9.8 Tf [( \(2\))] TJ ET BT 26.250 538.212 Td /F1 9.8 Tf [(Slices which were not corrupted by subject movement showed values for )] TJ ET q 24.000 0 0 13.500 342.706 535.512 cm /I16 Do Q BT 366.706 538.212 Td /F1 9.8 Tf [( \(average intensity deviation for one slice of a )] TJ ET BT 26.250 525.988 Td /F1 9.8 Tf [(volume compared to other slices at the same position in other volumes\) below 0.2. This threshold was found from a visual )] TJ ET BT 26.250 514.083 Td /F1 9.8 Tf [(inspection of the data and ensured that obvious artifacts were removed. This approach was applied separately to the \(b = 1000 )] TJ ET BT 26.250 502.179 Td /F1 9.8 Tf [(s/mm)] TJ ET BT 50.079 506.067 Td /F1 8.7 Tf [(2)] TJ ET BT 54.898 502.179 Td /F1 9.8 Tf [(\) and \(b = 100 s/mm)] TJ ET BT 142.414 506.067 Td /F1 8.7 Tf [(2)] TJ ET BT 147.232 502.179 Td /F1 9.8 Tf [(\) images in subject-specific native space for each subject. Figure 2 shows an example of this )] TJ ET BT 26.250 490.274 Td /F1 9.8 Tf [(concept for the same subject as depicted in Figure 1.)] TJ ET BT 26.250 470.869 Td /F4 9.8 Tf [(Spatial normalization and computation of FA-maps)] TJ ET BT 26.250 451.464 Td /F1 9.8 Tf [(Subject specific T1 images were first co-registered to the first b=100 s/mm)] TJ ET BT 346.216 455.353 Td /F1 8.7 Tf [(2)] TJ ET BT 351.034 451.464 Td /F1 9.8 Tf [( image given that its contrast is higher compared to )] TJ ET BT 26.250 439.560 Td /F1 9.8 Tf [(those with higher diffusion weighting. A study-specific template was generated separately for the T1 weighted images at both )] TJ ET BT 26.250 427.655 Td /F1 9.8 Tf [(field strengths \(i.e. 1.5T and 3.0T, respectively\) using a high dimensional non-linear approach \(Diffeomorphic Anatomical )] TJ ET BT 26.250 415.750 Td /F1 9.8 Tf [(Registration Through Exponentiated Lie Algebra, DARTEL\) as implemented in the SPM8 software package )] TJ ET 0.267 0.267 0.267 rg BT 490.662 415.750 Td /F1 9.8 Tf [([14])] TJ ET 0.271 0.267 0.267 rg BT 506.925 415.750 Td /F1 9.8 Tf [(. We then )] TJ ET BT 26.250 403.845 Td /F1 9.8 Tf [(applied normalization parameters to all DWI from the corresponding subject. Individual FA-maps were computed from each )] TJ ET BT 26.250 391.941 Td /F1 9.8 Tf [(subject with and without volumes with artifacts removed )] TJ ET 0.267 0.267 0.267 rg BT 269.005 391.941 Td /F1 9.8 Tf [([11])] TJ ET 0.271 0.267 0.267 rg BT 285.269 391.941 Td /F1 9.8 Tf [(. A Gaussian smoothing kernel of 8x8x8 mm was applied before )] TJ ET BT 26.250 380.036 Td /F1 9.8 Tf [(entering subjects into the statistical analyses.)] TJ ET BT 26.250 360.631 Td /F4 9.8 Tf [(Whole brain-based statistical analyses)] TJ ET BT 26.250 341.226 Td /F1 9.8 Tf [(As we were primarily interested in the effect of image artifacts on the detection of HD specific WM changes, the interaction )] TJ ET BT 26.250 329.322 Td /F1 9.8 Tf [(between group \(premanifest HD, early HD, and healthy controls\) and QC \(FA-maps with and without artifacts removed\) was the )] TJ ET BT 26.250 317.417 Td /F1 9.8 Tf [(analysis of interest. Given that substantially less than 1% of volumes had to be excluded from the control groups both at 1.5T )] TJ ET BT 26.250 305.512 Td /F1 9.8 Tf [(and at 3T \(Figure 3\), the difference between controls with and without QC was negligible. The interaction is therefore reduced to )] TJ ET BT 26.250 293.607 Td /F1 9.8 Tf [(a paired t-test separately for each group of HD subjects with and without QC. To be most sensitive, this analysis was repeated )] TJ ET BT 26.250 281.703 Td /F1 9.8 Tf [(after excluding all cases for which QC did not detect any problems. A lenient threshold of p<0.05 \(uncorrected for multiple )] TJ ET BT 26.250 269.798 Td /F1 9.8 Tf [(comparisons\) was chosen to ensure a high sensitivity to differences caused by movement artifact. For comparison with previous )] TJ ET BT 26.250 257.893 Td /F1 9.8 Tf [(studies, we also calculated differences between each group of patients and the respective group of healthy controls at a )] TJ ET BT 26.250 245.988 Td /F1 9.8 Tf [(significance level of p<0.001 \(uncorrected\).)] TJ ET BT 26.250 209.386 Td /F4 12.0 Tf [(Results)] TJ ET BT 26.250 189.432 Td /F1 9.8 Tf [(Figures 1 and 2 show typical scans with movement artifacts and how they are detected in a single subject. Figure 3 displays the )] TJ ET BT 26.250 177.527 Td /F1 9.8 Tf [(frequencies of removed volumes separately for each field strength, diagnostic group, and direction. In the 3T data, more slices )] TJ ET BT 26.250 165.622 Td /F1 9.8 Tf [(were removed from the group of subjects already affected from HD than from either the premanifest or control group. In the 1.5T )] TJ ET BT 26.250 153.717 Td /F1 9.8 Tf [(data, there were more exclusions from the premanifest group than from the controls.)] TJ ET BT 26.250 134.313 Td /F4 9.8 Tf [(Effect of QC)] TJ ET BT 26.250 114.908 Td /F1 9.8 Tf [(Paired-t-tests of premanifest and early patients with and without QC did not show significant differences even at a lenient )] TJ ET BT 26.250 103.003 Td /F1 9.8 Tf [(threshold of uncorrected p<0.05. The effect of QC for FA maps of single subjects \(Figure 1, bottom section\) is usually < 0.1 \(see )] TJ ET BT 26.250 91.098 Td /F1 9.8 Tf [(also Discussion\).)] TJ ET BT 26.250 71.694 Td /F4 9.8 Tf [(Group comparison)] TJ ET BT 26.250 52.289 Td /F1 9.8 Tf [(The findings of the between-groups comparison mirror those reported in previous studies )] TJ ET 0.267 0.267 0.267 rg BT 412.077 52.289 Td /F1 9.8 Tf [([15])] TJ ET BT 428.340 52.289 Td /F1 9.8 Tf [([16])] TJ ET 0.271 0.267 0.267 rg BT 444.603 52.289 Td /F1 9.8 Tf [( . Premanifest subjects show )] TJ ET BT 26.250 40.384 Td /F1 9.8 Tf [(increased FA values in the striatum while FA values in control subjects are higher at white matter/CSF boundaries \(Figure 4\). )] TJ ET Q q 15.000 26.098 577.500 750.902 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(We aimed to detect volumes \(i.e. gradient directions\) with at least one slice showing decreased intensity, i.e. motion artifacts )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(caused by spontaneous subject movement \(Figure 1\). For each diffusion weighted volume, we first computed the mean intensity )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(for each slice and compared this intensity to the same slice in all other volumes by using a weighted average approach. The )] TJ ET BT 26.250 731.762 Td /F1 9.8 Tf [(contribution to this weighted average was the greater the more similar a given direction was to the index direction. Similarity was )] TJ ET BT 26.250 719.857 Td /F1 9.8 Tf [(defined by computing the dot product between two gradient directions \(i.e., a value near 1 reflects great similarity\) which we )] TJ ET BT 26.250 707.952 Td /F1 9.8 Tf [(used as a weighting factor. We employed the following scaling procedure separately for each slice)] TJ ET q 85.500 0 0 37.500 26.250 660.572 cm /I18 Do Q BT 111.750 668.072 Td /F1 9.8 Tf [( \(1\))] TJ ET BT 26.250 639.871 Td /F1 9.8 Tf [(Here, )] TJ ET q 14.250 0 0 16.500 52.799 636.572 cm /I20 Do Q BT 67.049 639.871 Td /F1 9.8 Tf [( denotes the arithmetic average intensity of the slice under observation and )] TJ ET q 12.750 0 0 15.000 393.840 638.072 cm /I22 Do Q BT 406.590 639.871 Td /F1 9.8 Tf [( a slice for comparison. The relative )] TJ ET BT 26.250 623.371 Td /F1 9.8 Tf [(average intensity deviation )] TJ ET q 27.750 0 0 13.500 144.391 623.072 cm /I24 Do Q BT 172.141 623.371 Td /F1 9.8 Tf [( was weighted by the dot product of the gradient direction )] TJ ET q 34.500 0 0 16.500 421.985 620.072 cm /I26 Do Q BT 456.485 623.371 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 603.048 Td /F1 9.8 Tf [(If, for one slice of the volume under observation, the average intensity deviation to all other slices exceeded a certain threshold, )] TJ ET BT 26.250 591.143 Td /F1 9.8 Tf [(the whole volume \(i.e., gradient direction\) from this subject was eliminated.)] TJ ET q 150.000 0 0 24.750 26.250 556.512 cm /I28 Do Q BT 176.250 561.462 Td /F1 9.8 Tf [( \(2\))] TJ ET BT 26.250 538.212 Td /F1 9.8 Tf [(Slices which were not corrupted by subject movement showed values for )] TJ ET q 24.000 0 0 13.500 342.706 535.512 cm /I30 Do Q BT 366.706 538.212 Td /F1 9.8 Tf [( \(average intensity deviation for one slice of a )] TJ ET BT 26.250 525.988 Td /F1 9.8 Tf [(volume compared to other slices at the same position in other volumes\) below 0.2. This threshold was found from a visual )] TJ ET BT 26.250 514.083 Td /F1 9.8 Tf [(inspection of the data and ensured that obvious artifacts were removed. This approach was applied separately to the \(b = 1000 )] TJ ET BT 26.250 502.179 Td /F1 9.8 Tf [(s/mm)] TJ ET BT 50.079 506.067 Td /F1 8.7 Tf [(2)] TJ ET BT 54.898 502.179 Td /F1 9.8 Tf [(\) and \(b = 100 s/mm)] TJ ET BT 142.414 506.067 Td /F1 8.7 Tf [(2)] TJ ET BT 147.232 502.179 Td /F1 9.8 Tf [(\) images in subject-specific native space for each subject. Figure 2 shows an example of this )] TJ ET BT 26.250 490.274 Td /F1 9.8 Tf [(concept for the same subject as depicted in Figure 1.)] TJ ET BT 26.250 470.869 Td /F4 9.8 Tf [(Spatial normalization and computation of FA-maps)] TJ ET BT 26.250 451.464 Td /F1 9.8 Tf [(Subject specific T1 images were first co-registered to the first b=100 s/mm)] TJ ET BT 346.216 455.353 Td /F1 8.7 Tf [(2)] TJ ET BT 351.034 451.464 Td /F1 9.8 Tf [( image given that its contrast is higher compared to )] TJ ET BT 26.250 439.560 Td /F1 9.8 Tf [(those with higher diffusion weighting. A study-specific template was generated separately for the T1 weighted images at both )] TJ ET BT 26.250 427.655 Td /F1 9.8 Tf [(field strengths \(i.e. 1.5T and 3.0T, respectively\) using a high dimensional non-linear approach \(Diffeomorphic Anatomical )] TJ ET BT 26.250 415.750 Td /F1 9.8 Tf [(Registration Through Exponentiated Lie Algebra, DARTEL\) as implemented in the SPM8 software package )] TJ ET 0.267 0.267 0.267 rg BT 490.662 415.750 Td /F1 9.8 Tf [([14])] TJ ET 0.271 0.267 0.267 rg BT 506.925 415.750 Td /F1 9.8 Tf [(. We then )] TJ ET BT 26.250 403.845 Td /F1 9.8 Tf [(applied normalization parameters to all DWI from the corresponding subject. Individual FA-maps were computed from each )] TJ ET BT 26.250 391.941 Td /F1 9.8 Tf [(subject with and without volumes with artifacts removed )] TJ ET 0.267 0.267 0.267 rg BT 269.005 391.941 Td /F1 9.8 Tf [([11])] TJ ET 0.271 0.267 0.267 rg BT 285.269 391.941 Td /F1 9.8 Tf [(. A Gaussian smoothing kernel of 8x8x8 mm was applied before )] TJ ET BT 26.250 380.036 Td /F1 9.8 Tf [(entering subjects into the statistical analyses.)] TJ ET BT 26.250 360.631 Td /F4 9.8 Tf [(Whole brain-based statistical analyses)] TJ ET BT 26.250 341.226 Td /F1 9.8 Tf [(As we were primarily interested in the effect of image artifacts on the detection of HD specific WM changes, the interaction )] TJ ET BT 26.250 329.322 Td /F1 9.8 Tf [(between group \(premanifest HD, early HD, and healthy controls\) and QC \(FA-maps with and without artifacts removed\) was the )] TJ ET BT 26.250 317.417 Td /F1 9.8 Tf [(analysis of interest. Given that substantially less than 1% of volumes had to be excluded from the control groups both at 1.5T )] TJ ET BT 26.250 305.512 Td /F1 9.8 Tf [(and at 3T \(Figure 3\), the difference between controls with and without QC was negligible. The interaction is therefore reduced to )] TJ ET BT 26.250 293.607 Td /F1 9.8 Tf [(a paired t-test separately for each group of HD subjects with and without QC. To be most sensitive, this analysis was repeated )] TJ ET BT 26.250 281.703 Td /F1 9.8 Tf [(after excluding all cases for which QC did not detect any problems. A lenient threshold of p<0.05 \(uncorrected for multiple )] TJ ET BT 26.250 269.798 Td /F1 9.8 Tf [(comparisons\) was chosen to ensure a high sensitivity to differences caused by movement artifact. For comparison with previous )] TJ ET BT 26.250 257.893 Td /F1 9.8 Tf [(studies, we also calculated differences between each group of patients and the respective group of healthy controls at a )] TJ ET BT 26.250 245.988 Td /F1 9.8 Tf [(significance level of p<0.001 \(uncorrected\).)] TJ ET BT 26.250 209.386 Td /F4 12.0 Tf [(Results)] TJ ET BT 26.250 189.432 Td /F1 9.8 Tf [(Figures 1 and 2 show typical scans with movement artifacts and how they are detected in a single subject. Figure 3 displays the )] TJ ET BT 26.250 177.527 Td /F1 9.8 Tf [(frequencies of removed volumes separately for each field strength, diagnostic group, and direction. In the 3T data, more slices )] TJ ET BT 26.250 165.622 Td /F1 9.8 Tf [(were removed from the group of subjects already affected from HD than from either the premanifest or control group. In the 1.5T )] TJ ET BT 26.250 153.717 Td /F1 9.8 Tf [(data, there were more exclusions from the premanifest group than from the controls.)] TJ ET BT 26.250 134.313 Td /F4 9.8 Tf [(Effect of QC)] TJ ET BT 26.250 114.908 Td /F1 9.8 Tf [(Paired-t-tests of premanifest and early patients with and without QC did not show significant differences even at a lenient )] TJ ET BT 26.250 103.003 Td /F1 9.8 Tf [(threshold of uncorrected p<0.05. The effect of QC for FA maps of single subjects \(Figure 1, bottom section\) is usually < 0.1 \(see )] TJ ET BT 26.250 91.098 Td /F1 9.8 Tf [(also Discussion\).)] TJ ET BT 26.250 71.694 Td /F4 9.8 Tf [(Group comparison)] TJ ET BT 26.250 52.289 Td /F1 9.8 Tf [(The findings of the between-groups comparison mirror those reported in previous studies )] TJ ET 0.267 0.267 0.267 rg BT 412.077 52.289 Td /F1 9.8 Tf [([15])] TJ ET BT 428.340 52.289 Td /F1 9.8 Tf [([16])] TJ ET 0.271 0.267 0.267 rg BT 444.603 52.289 Td /F1 9.8 Tf [( . Premanifest subjects show )] TJ ET BT 26.250 40.384 Td /F1 9.8 Tf [(increased FA values in the striatum while FA values in control subjects are higher at white matter/CSF boundaries \(Figure 4\). )] TJ ET Q q 15.000 26.098 577.500 750.902 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(We aimed to detect volumes \(i.e. gradient directions\) with at least one slice showing decreased intensity, i.e. motion artifacts )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(caused by spontaneous subject movement \(Figure 1\). For each diffusion weighted volume, we first computed the mean intensity )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(for each slice and compared this intensity to the same slice in all other volumes by using a weighted average approach. The )] TJ ET BT 26.250 731.762 Td /F1 9.8 Tf [(contribution to this weighted average was the greater the more similar a given direction was to the index direction. Similarity was )] TJ ET BT 26.250 719.857 Td /F1 9.8 Tf [(defined by computing the dot product between two gradient directions \(i.e., a value near 1 reflects great similarity\) which we )] TJ ET BT 26.250 707.952 Td /F1 9.8 Tf [(used as a weighting factor. We employed the following scaling procedure separately for each slice)] TJ ET q 85.500 0 0 37.500 26.250 660.572 cm /I32 Do Q BT 111.750 668.072 Td /F1 9.8 Tf [( \(1\))] TJ ET BT 26.250 639.871 Td /F1 9.8 Tf [(Here, )] TJ ET q 14.250 0 0 16.500 52.799 636.572 cm /I34 Do Q BT 67.049 639.871 Td /F1 9.8 Tf [( denotes the arithmetic average intensity of the slice under observation and )] TJ ET q 12.750 0 0 15.000 393.840 638.072 cm /I36 Do Q BT 406.590 639.871 Td /F1 9.8 Tf [( a slice for comparison. The relative )] TJ ET BT 26.250 623.371 Td /F1 9.8 Tf [(average intensity deviation )] TJ ET q 27.750 0 0 13.500 144.391 623.072 cm /I38 Do Q BT 172.141 623.371 Td /F1 9.8 Tf [( was weighted by the dot product of the gradient direction )] TJ ET q 34.500 0 0 16.500 421.985 620.072 cm /I40 Do Q BT 456.485 623.371 Td /F1 9.8 Tf [(.)] TJ ET BT 26.250 603.048 Td /F1 9.8 Tf [(If, for one slice of the volume under observation, the average intensity deviation to all other slices exceeded a certain threshold, )] TJ ET BT 26.250 591.143 Td /F1 9.8 Tf [(the whole volume \(i.e., gradient direction\) from this subject was eliminated.)] TJ ET q 150.000 0 0 24.750 26.250 556.512 cm /I42 Do Q BT 176.250 561.462 Td /F1 9.8 Tf [( \(2\))] TJ ET BT 26.250 538.212 Td /F1 9.8 Tf [(Slices which were not corrupted by subject movement showed values for )] TJ ET q 24.000 0 0 13.500 342.706 535.512 cm /I44 Do Q BT 366.706 538.212 Td /F1 9.8 Tf [( \(average intensity deviation for one slice of a )] TJ ET BT 26.250 525.988 Td /F1 9.8 Tf [(volume compared to other slices at the same position in other volumes\) below 0.2. This threshold was found from a visual )] TJ ET BT 26.250 514.083 Td /F1 9.8 Tf [(inspection of the data and ensured that obvious artifacts were removed. This approach was applied separately to the \(b = 1000 )] TJ ET BT 26.250 502.179 Td /F1 9.8 Tf [(s/mm)] TJ ET BT 50.079 506.067 Td /F1 8.7 Tf [(2)] TJ ET BT 54.898 502.179 Td /F1 9.8 Tf [(\) and \(b = 100 s/mm)] TJ ET BT 142.414 506.067 Td /F1 8.7 Tf [(2)] TJ ET BT 147.232 502.179 Td /F1 9.8 Tf [(\) images in subject-specific native space for each subject. Figure 2 shows an example of this )] TJ ET BT 26.250 490.274 Td /F1 9.8 Tf [(concept for the same subject as depicted in Figure 1.)] TJ ET BT 26.250 470.869 Td /F4 9.8 Tf [(Spatial normalization and computation of FA-maps)] TJ ET BT 26.250 451.464 Td /F1 9.8 Tf [(Subject specific T1 images were first co-registered to the first b=100 s/mm)] TJ ET BT 346.216 455.353 Td /F1 8.7 Tf [(2)] TJ ET BT 351.034 451.464 Td /F1 9.8 Tf [( image given that its contrast is higher compared to )] TJ ET BT 26.250 439.560 Td /F1 9.8 Tf [(those with higher diffusion weighting. A study-specific template was generated separately for the T1 weighted images at both )] TJ ET BT 26.250 427.655 Td /F1 9.8 Tf [(field strengths \(i.e. 1.5T and 3.0T, respectively\) using a high dimensional non-linear approach \(Diffeomorphic Anatomical )] TJ ET BT 26.250 415.750 Td /F1 9.8 Tf [(Registration Through Exponentiated Lie Algebra, DARTEL\) as implemented in the SPM8 software package )] TJ ET 0.267 0.267 0.267 rg BT 490.662 415.750 Td /F1 9.8 Tf [([14])] TJ ET 0.271 0.267 0.267 rg BT 506.925 415.750 Td /F1 9.8 Tf [(. We then )] TJ ET BT 26.250 403.845 Td /F1 9.8 Tf [(applied normalization parameters to all DWI from the corresponding subject. Individual FA-maps were computed from each )] TJ ET BT 26.250 391.941 Td /F1 9.8 Tf [(subject with and without volumes with artifacts removed )] TJ ET 0.267 0.267 0.267 rg BT 269.005 391.941 Td /F1 9.8 Tf [([11])] TJ ET 0.271 0.267 0.267 rg BT 285.269 391.941 Td /F1 9.8 Tf [(. A Gaussian smoothing kernel of 8x8x8 mm was applied before )] TJ ET BT 26.250 380.036 Td /F1 9.8 Tf [(entering subjects into the statistical analyses.)] TJ ET BT 26.250 360.631 Td /F4 9.8 Tf [(Whole brain-based statistical analyses)] TJ ET BT 26.250 341.226 Td /F1 9.8 Tf [(As we were primarily interested in the effect of image artifacts on the detection of HD specific WM changes, the interaction )] TJ ET BT 26.250 329.322 Td /F1 9.8 Tf [(between group \(premanifest HD, early HD, and healthy controls\) and QC \(FA-maps with and without artifacts removed\) was the )] TJ ET BT 26.250 317.417 Td /F1 9.8 Tf [(analysis of interest. Given that substantially less than 1% of volumes had to be excluded from the control groups both at 1.5T )] TJ ET BT 26.250 305.512 Td /F1 9.8 Tf [(and at 3T \(Figure 3\), the difference between controls with and without QC was negligible. The interaction is therefore reduced to )] TJ ET BT 26.250 293.607 Td /F1 9.8 Tf [(a paired t-test separately for each group of HD subjects with and without QC. To be most sensitive, this analysis was repeated )] TJ ET BT 26.250 281.703 Td /F1 9.8 Tf [(after excluding all cases for which QC did not detect any problems. A lenient threshold of p<0.05 \(uncorrected for multiple )] TJ ET BT 26.250 269.798 Td /F1 9.8 Tf [(comparisons\) was chosen to ensure a high sensitivity to differences caused by movement artifact. For comparison with previous )] TJ ET BT 26.250 257.893 Td /F1 9.8 Tf [(studies, we also calculated differences between each group of patients and the respective group of healthy controls at a )] TJ ET BT 26.250 245.988 Td /F1 9.8 Tf [(significance level of p<0.001 \(uncorrected\).)] TJ ET BT 26.250 209.386 Td /F4 12.0 Tf [(Results)] TJ ET BT 26.250 189.432 Td /F1 9.8 Tf [(Figures 1 and 2 show typical scans with movement artifacts and how they are detected in a single subject. Figure 3 displays the )] TJ ET BT 26.250 177.527 Td /F1 9.8 Tf [(frequencies of removed volumes separately for each field strength, diagnostic group, and direction. In the 3T data, more slices )] TJ ET BT 26.250 165.622 Td /F1 9.8 Tf [(were removed from the group of subjects already affected from HD than from either the premanifest or control group. In the 1.5T )] TJ ET BT 26.250 153.717 Td /F1 9.8 Tf [(data, there were more exclusions from the premanifest group than from the controls.)] TJ ET BT 26.250 134.313 Td /F4 9.8 Tf [(Effect of QC)] TJ ET BT 26.250 114.908 Td /F1 9.8 Tf [(Paired-t-tests of premanifest and early patients with and without QC did not show significant differences even at a lenient )] TJ ET BT 26.250 103.003 Td /F1 9.8 Tf [(threshold of uncorrected p<0.05. The effect of QC for FA maps of single subjects \(Figure 1, bottom section\) is usually < 0.1 \(see )] TJ ET BT 26.250 91.098 Td /F1 9.8 Tf [(also Discussion\).)] TJ ET BT 26.250 71.694 Td /F4 9.8 Tf [(Group comparison)] TJ ET BT 26.250 52.289 Td /F1 9.8 Tf [(The findings of the between-groups comparison mirror those reported in previous studies )] TJ ET 0.267 0.267 0.267 rg BT 412.077 52.289 Td /F1 9.8 Tf [([15])] TJ ET BT 428.340 52.289 Td /F1 9.8 Tf [([16])] TJ ET 0.271 0.267 0.267 rg BT 444.603 52.289 Td /F1 9.8 Tf [( . Premanifest subjects show )] TJ ET BT 26.250 40.384 Td /F1 9.8 Tf [(increased FA values in the striatum while FA values in control subjects are higher at white matter/CSF boundaries \(Figure 4\). )] TJ ET Q q 0.000 0.000 0.000 rg BT 291.710 19.825 Td /F1 11.0 Tf [(3)] TJ ET BT 25.000 19.825 Td /F1 11.0 Tf [(PLOS Currents Huntington Disease)] TJ ET Q endstream endobj 198 0 obj << /Type /XObject /Subtype /Image /Width 114 /Height 50 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 114 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 1000>> stream XXg#AkX+VTĪsTUUQ"*NTDQQ'DEDDUUUDUOdgl/}~y3y޾7Y 10ExYjeZ(k(Q+P2(*k DXc%1g2)l&"RehR\c$Sotb1e+v lH hb6@o{k)E_g(e6 yŠXD}M;$I b5'fKhGU`wRIxW6rwQ% ogBQU sqDXw,MxsIX%ɇUV1+QZKYrFh,RXe{7wQ|$c^L ~$~9YT:Qi@ev_yп{z=E-:HQH"7G^ˮmR/61RJ kPڎSQ5D?X${W`|XR 7 Ef<(-%5\W%|xN VI*T2s` h`Qυ!}L[I?כ3d288.]hOiHׇe|llFWT}-_\ݣPh$= pu}`c9|q͏FR F;R), c5 J2umjIE6! ,8>cPN]x׈#pM[Ԣb5#yut2VWND.Z4l:LKO$g>|,S0Td-oLR*;ජԥUy]'"L`ܙAr``).ue4$ׄ٘[sf9&C3!sZ::/dÂ6 endstream endobj 199 0 obj << /Type /XObject /Subtype /Image /Width 114 /Height 50 /SMask 198 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 114 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 39>> stream x1 Om eB endstream endobj 200 0 obj << /Type /XObject /Subtype /Image /Width 19 /Height 22 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 19 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream c`6ق RV,h*y,SA[1P]Pؔmĺ Pa@BT۩(> 8VpNټm z5{5ńf5H̘ddB C"L.)8`!iC4"T֕a. endstream endobj 201 0 obj << /Type /XObject /Subtype /Image /Width 19 /Height 22 /SMask 200 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 19 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 18>> stream 8c`` endstream endobj 202 0 obj << /Type /XObject /Subtype /Image /Width 17 /Height 20 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 17 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream c`ڂ fxxx$x ,nIߤ<7$}U۸b.T ,00]0C,;P"2& c+` wnHa&H A1`mm5j&01( ))0pd1 jC3+TM|1"&3bbb`1- endstream endobj 203 0 obj << /Type /XObject /Subtype /Image /Width 17 /Height 20 /SMask 202 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 17 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 18>> stream 8c`` endstream endobj 204 0 obj << /Type /XObject /Subtype /Image /Width 37 /Height 18 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 37 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 292>> stream (c`6"-8+䰨j87 fs0M SDǴ3n9-L5 -.*!X@B  ΨÑ1K10ȝPyˁ$1j\7,&& aH ]҈'bsM9!q)xLhq Nυ,NHc̩:!dC&As`C萴$Bm> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 23>> stream 8c``Q0 Fp endstream endobj 206 0 obj << /Type /XObject /Subtype /Image /Width 46 /Height 22 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 46 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 333>> stream 8c`@L\ /Ԁ(-H`)$Qdlvl A4-cCP әBU&L)33MXTcQ8v)PpS|@Haw S޵ Hلdt`\&hژt! I >za!  H=M+NaK.H2r `Aqz CS ` f6fq\#ɀ3 [3k8Y|!I̎A,hLBt$uJ% ]  NGQ ZI ǔ0D tp3X$ 4u endstream endobj 207 0 obj << /Type /XObject /Subtype /Image /Width 46 /Height 22 /SMask 206 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 46 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 25>> stream H  Omk  endstream endobj 208 0 obj << /Type /XObject /Subtype /Image /Width 200 /Height 33 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 200 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 1141>> stream XXk"I-PBdd }B  "2aeaYCC"A 졑DA?iUw׌lwTW]y}_%y MbCO4OJʨ%>ߌ7rУv+dA!Q9p;l:B^U|.=xAܓ7M!9}yQ, ^@S,j2$_9A6֒W#waL*K= L؛VB"NHdCD23m!P#TY&dqeDx=N쵟 R%82{% xe?IW+g>6#ՑhSa|DS5WPwBtXX)vi.PUlHC`|\s#^h}l.m,zu_Ty,~P_@ő,'B4=hcgx| {fm@|S/4/J2h1нRY"1g(UnBXF9L#4ߵdB$ D 3xQ:0 sUdSvPE,2] j4Ɂ>? eNb&‰ǽb*M8Y 6aaVc5z[|#7Ӥm*d Djx 1b?U$S.I AKvVD(˾INd70,n#K"PvH?+'mEfωAKkR.,sjZFlk0VFM J8]_gP%Nu 3}"L> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 42>> stream x  OmMy endstream endobj 210 0 obj << /Type /XObject /Subtype /Image /Width 32 /Height 18 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 32 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 243>> stream (c`6@͕r ͂.LrCvFm;ŀ Z\TMCp78$ .X LT<djrc`pBu.n؀E r ܈TtЅy" Opל8 LI Btt L\Ȃ:O`.ZuD !ۀDִ"(r$ == ,!6 laK^ vLtIP gtUf}K+ endstream endobj 211 0 obj << /Type /XObject /Subtype /Image /Width 32 /Height 18 /SMask 210 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 32 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 22>> stream 8c``Q0  endstream endobj 212 0 obj << /Type /Annot /Subtype /Link /A 213 0 R /Border [0 0 0] /H /I /Rect [ 490.6620 414.8483 506.9250 424.7690 ] >> endobj 213 0 obj << /Type /Action >> endobj 214 0 obj << /Type /Annot /Subtype /Link /A 215 0 R /Border [0 0 0] /H /I /Rect [ 269.0055 391.0388 285.2685 400.9595 ] >> endobj 215 0 obj << /Type /Action >> endobj 216 0 obj << /Type /Annot /Subtype /Link /A 217 0 R /Border [0 0 0] /H /I /Rect [ 412.0770 51.3871 428.3400 61.3077 ] >> endobj 217 0 obj << /Type /Action >> endobj 218 0 obj << /Type /Annot /Subtype /Link /A 219 0 R /Border [0 0 0] /H /I /Rect [ 428.3400 51.3871 444.6030 61.3077 ] >> endobj 219 0 obj << /Type /Action >> endobj 220 0 obj << /Type /XObject /Subtype /Image /Width 114 /Height 50 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 114 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 1000>> stream XXg#AkX+VTĪsTUUQ"*NTDQQ'DEDDUUUDUOdgl/}~y3y޾7Y 10ExYjeZ(k(Q+P2(*k DXc%1g2)l&"RehR\c$Sotb1e+v lH hb6@o{k)E_g(e6 yŠXD}M;$I b5'fKhGU`wRIxW6rwQ% ogBQU sqDXw,MxsIX%ɇUV1+QZKYrFh,RXe{7wQ|$c^L ~$~9YT:Qi@ev_yп{z=E-:HQH"7G^ˮmR/61RJ kPڎSQ5D?X${W`|XR 7 Ef<(-%5\W%|xN VI*T2s` h`Qυ!}L[I?כ3d288.]hOiHׇe|llFWT}-_\ݣPh$= pu}`c9|q͏FR F;R), c5 J2umjIE6! ,8>cPN]x׈#pM[Ԣb5#yut2VWND.Z4l:LKO$g>|,S0Td-oLR*;ජԥUy]'"L`ܙAr``).ue4$ׄ٘[sf9&C3!sZ::/dÂ6 endstream endobj 221 0 obj << /Type /XObject /Subtype /Image /Width 114 /Height 50 /SMask 220 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 114 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 39>> stream x1 Om eB endstream endobj 222 0 obj << /Type /XObject /Subtype /Image /Width 19 /Height 22 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 19 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream c`6ق RV,h*y,SA[1P]Pؔmĺ Pa@BT۩(> 8VpNټm z5{5ńf5H̘ddB C"L.)8`!iC4"T֕a. endstream endobj 223 0 obj << /Type /XObject /Subtype /Image /Width 19 /Height 22 /SMask 222 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 19 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 18>> stream 8c`` endstream endobj 224 0 obj << /Type /XObject /Subtype /Image /Width 17 /Height 20 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 17 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream c`ڂ fxxx$x ,nIߤ<7$}U۸b.T ,00]0C,;P"2& c+` wnHa&H A1`mm5j&01( ))0pd1 jC3+TM|1"&3bbb`1- endstream endobj 225 0 obj << /Type /XObject /Subtype /Image /Width 17 /Height 20 /SMask 224 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 17 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 18>> stream 8c`` endstream endobj 226 0 obj << /Type /XObject /Subtype /Image /Width 37 /Height 18 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 37 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 292>> stream (c`6"-8+䰨j87 fs0M SDǴ3n9-L5 -.*!X@B  ΨÑ1K10ȝPyˁ$1j\7,&& aH ]҈'bsM9!q)xLhq Nυ,NHc̩:!dC&As`C萴$Bm> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 23>> stream 8c``Q0 Fp endstream endobj 228 0 obj << /Type /XObject /Subtype /Image /Width 46 /Height 22 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 46 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 333>> stream 8c`@L\ /Ԁ(-H`)$Qdlvl A4-cCP әBU&L)33MXTcQ8v)PpS|@Haw S޵ Hلdt`\&hژt! I >za!  H=M+NaK.H2r `Aqz CS ` f6fq\#ɀ3 [3k8Y|!I̎A,hLBt$uJ% ]  NGQ ZI ǔ0D tp3X$ 4u endstream endobj 229 0 obj << /Type /XObject /Subtype /Image /Width 46 /Height 22 /SMask 228 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 46 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 25>> stream H  Omk  endstream endobj 230 0 obj << /Type /XObject /Subtype /Image /Width 200 /Height 33 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 200 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 1141>> stream XXk"I-PBdd }B  "2aeaYCC"A 졑DA?iUw׌lwTW]y}_%y MbCO4OJʨ%>ߌ7rУv+dA!Q9p;l:B^U|.=xAܓ7M!9}yQ, ^@S,j2$_9A6֒W#waL*K= L؛VB"NHdCD23m!P#TY&dqeDx=N쵟 R%82{% xe?IW+g>6#ՑhSa|DS5WPwBtXX)vi.PUlHC`|\s#^h}l.m,zu_Ty,~P_@ő,'B4=hcgx| {fm@|S/4/J2h1нRY"1g(UnBXF9L#4ߵdB$ D 3xQ:0 sUdSvPE,2] j4Ɂ>? eNb&‰ǽb*M8Y 6aaVc5z[|#7Ӥm*d Djx 1b?U$S.I AKvVD(˾INd70,n#K"PvH?+'mEfωAKkR.,sjZFlk0VFM J8]_gP%Nu 3}"L> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 42>> stream x  OmMy endstream endobj 232 0 obj << /Type /XObject /Subtype /Image /Width 32 /Height 18 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 32 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 243>> stream (c`6@͕r ͂.LrCvFm;ŀ Z\TMCp78$ .X LT<djrc`pBu.n؀E r ܈TtЅy" Opל8 LI Btt L\Ȃ:O`.ZuD !ۀDִ"(r$ == ,!6 laK^ vLtIP gtUf}K+ endstream endobj 233 0 obj << /Type /XObject /Subtype /Image /Width 32 /Height 18 /SMask 232 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 32 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 22>> stream 8c``Q0  endstream endobj 234 0 obj << /Type /Annot /Subtype /Link /A 235 0 R /Border [0 0 0] /H /I /Rect [ 490.6620 414.8483 506.9250 424.7690 ] >> endobj 235 0 obj << /Type /Action >> endobj 236 0 obj << /Type /Annot /Subtype /Link /A 237 0 R /Border [0 0 0] /H /I /Rect [ 269.0055 391.0388 285.2685 400.9595 ] >> endobj 237 0 obj << /Type /Action >> endobj 238 0 obj << /Type /Annot /Subtype /Link /A 239 0 R /Border [0 0 0] /H /I /Rect [ 412.0770 51.3871 428.3400 61.3077 ] >> endobj 239 0 obj << /Type /Action >> endobj 240 0 obj << /Type /Annot /Subtype /Link /A 241 0 R /Border [0 0 0] /H /I /Rect [ 428.3400 51.3871 444.6030 61.3077 ] >> endobj 241 0 obj << /Type /Action >> endobj 242 0 obj << /Type /XObject /Subtype /Image /Width 114 /Height 50 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 114 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 1000>> stream XXg#AkX+VTĪsTUUQ"*NTDQQ'DEDDUUUDUOdgl/}~y3y޾7Y 10ExYjeZ(k(Q+P2(*k DXc%1g2)l&"RehR\c$Sotb1e+v lH hb6@o{k)E_g(e6 yŠXD}M;$I b5'fKhGU`wRIxW6rwQ% ogBQU sqDXw,MxsIX%ɇUV1+QZKYrFh,RXe{7wQ|$c^L ~$~9YT:Qi@ev_yп{z=E-:HQH"7G^ˮmR/61RJ kPڎSQ5D?X${W`|XR 7 Ef<(-%5\W%|xN VI*T2s` h`Qυ!}L[I?כ3d288.]hOiHׇe|llFWT}-_\ݣPh$= pu}`c9|q͏FR F;R), c5 J2umjIE6! ,8>cPN]x׈#pM[Ԣb5#yut2VWND.Z4l:LKO$g>|,S0Td-oLR*;ජԥUy]'"L`ܙAr``).ue4$ׄ٘[sf9&C3!sZ::/dÂ6 endstream endobj 243 0 obj << /Type /XObject /Subtype /Image /Width 114 /Height 50 /SMask 242 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 114 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 39>> stream x1 Om eB endstream endobj 244 0 obj << /Type /XObject /Subtype /Image /Width 19 /Height 22 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 19 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream c`6ق RV,h*y,SA[1P]Pؔmĺ Pa@BT۩(> 8VpNټm z5{5ńf5H̘ddB C"L.)8`!iC4"T֕a. endstream endobj 245 0 obj << /Type /XObject /Subtype /Image /Width 19 /Height 22 /SMask 244 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 19 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 18>> stream 8c`` endstream endobj 246 0 obj << /Type /XObject /Subtype /Image /Width 17 /Height 20 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 17 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream c`ڂ fxxx$x ,nIߤ<7$}U۸b.T ,00]0C,;P"2& c+` wnHa&H A1`mm5j&01( ))0pd1 jC3+TM|1"&3bbb`1- endstream endobj 247 0 obj << /Type /XObject /Subtype /Image /Width 17 /Height 20 /SMask 246 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 17 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 18>> stream 8c`` endstream endobj 248 0 obj << /Type /XObject /Subtype /Image /Width 37 /Height 18 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 37 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 292>> stream (c`6"-8+䰨j87 fs0M SDǴ3n9-L5 -.*!X@B  ΨÑ1K10ȝPyˁ$1j\7,&& aH ]҈'bsM9!q)xLhq Nυ,NHc̩:!dC&As`C萴$Bm> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 23>> stream 8c``Q0 Fp endstream endobj 250 0 obj << /Type /XObject /Subtype /Image /Width 46 /Height 22 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 46 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 333>> stream 8c`@L\ /Ԁ(-H`)$Qdlvl A4-cCP әBU&L)33MXTcQ8v)PpS|@Haw S޵ Hلdt`\&hژt! I >za!  H=M+NaK.H2r `Aqz CS ` f6fq\#ɀ3 [3k8Y|!I̎A,hLBt$uJ% ]  NGQ ZI ǔ0D tp3X$ 4u endstream endobj 251 0 obj << /Type /XObject /Subtype /Image /Width 46 /Height 22 /SMask 250 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 46 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 25>> stream H  Omk  endstream endobj 252 0 obj << /Type /XObject /Subtype /Image /Width 200 /Height 33 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 200 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 1141>> stream XXk"I-PBdd }B  "2aeaYCC"A 졑DA?iUw׌lwTW]y}_%y MbCO4OJʨ%>ߌ7rУv+dA!Q9p;l:B^U|.=xAܓ7M!9}yQ, ^@S,j2$_9A6֒W#waL*K= L؛VB"NHdCD23m!P#TY&dqeDx=N쵟 R%82{% xe?IW+g>6#ՑhSa|DS5WPwBtXX)vi.PUlHC`|\s#^h}l.m,zu_Ty,~P_@ő,'B4=hcgx| {fm@|S/4/J2h1нRY"1g(UnBXF9L#4ߵdB$ D 3xQ:0 sUdSvPE,2] j4Ɂ>? eNb&‰ǽb*M8Y 6aaVc5z[|#7Ӥm*d Djx 1b?U$S.I AKvVD(˾INd70,n#K"PvH?+'mEfωAKkR.,sjZFlk0VFM J8]_gP%Nu 3}"L> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 42>> stream x  OmMy endstream endobj 254 0 obj << /Type /XObject /Subtype /Image /Width 32 /Height 18 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 32 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 243>> stream (c`6@͕r ͂.LrCvFm;ŀ Z\TMCp78$ .X LT<djrc`pBu.n؀E r ܈TtЅy" Opל8 LI Btt L\Ȃ:O`.ZuD !ۀDִ"(r$ == ,!6 laK^ vLtIP gtUf}K+ endstream endobj 255 0 obj << /Type /XObject /Subtype /Image /Width 32 /Height 18 /SMask 254 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 32 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 22>> stream 8c``Q0  endstream endobj 256 0 obj << /Type /Annot /Subtype /Link /A 257 0 R /Border [0 0 0] /H /I /Rect [ 490.6620 414.8483 506.9250 424.7690 ] >> endobj 257 0 obj << /Type /Action >> endobj 258 0 obj << /Type /Annot /Subtype /Link /A 259 0 R /Border [0 0 0] /H /I /Rect [ 269.0055 391.0388 285.2685 400.9595 ] >> endobj 259 0 obj << /Type /Action >> endobj 260 0 obj << /Type /Annot /Subtype /Link /A 261 0 R /Border [0 0 0] /H /I /Rect [ 412.0770 51.3871 428.3400 61.3077 ] >> endobj 261 0 obj << /Type /Action >> endobj 262 0 obj << /Type /Annot /Subtype /Link /A 263 0 R /Border [0 0 0] /H /I /Rect [ 428.3400 51.3871 444.6030 61.3077 ] >> endobj 263 0 obj << /Type /Action >> endobj 264 0 obj << /Type /Page /Parent 3 0 R /Annots [ 266 0 R 269 0 R 273 0 R 276 0 R 278 0 R 280 0 R 282 0 R 286 0 R 288 0 R 290 0 R 292 0 R 294 0 R 298 0 R 300 0 R 302 0 R ] /Contents 265 0 R >> endobj 265 0 obj << /Length 12735 >> stream 0.271 0.267 0.267 rg q 15.000 33.073 577.500 743.927 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(We also observed increased FA values in the corpus callosum of control subjects when compared separately to premanifest )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(and early HD subjects scanned at 3T.)] TJ ET 0.965 0.965 0.965 rg 26.250 539.577 555.000 206.114 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 745.690 m 581.250 745.690 l 581.250 744.940 l 26.250 744.940 l f 26.250 539.577 m 581.250 539.577 l 581.250 540.327 l 26.250 540.327 l f q 112.500 0 0 112.500 35.250 623.440 cm /I45 Do Q q 35.250 550.827 537.000 66.614 re W n 0.271 0.267 0.267 rg BT 35.250 607.917 Td /F4 9.8 Tf [(Fig. 1: Schematic flowchart of quality check \(QC\) data processing for an example subject \(HD patient at 3T\).)] TJ ET BT 35.250 588.547 Td /F4 9.8 Tf [(Upper panel)] TJ ET BT 91.595 588.547 Td /F1 9.8 Tf [(: series of sagittal slices with and without motion artifacts. The QC algorithm eliminates the respective volumes )] TJ ET BT 35.250 574.810 Td /F1 9.8 Tf [(\(i.e., vol. no. 26 and twelve further volumes for this data set\). Differences in FA maps calculated without and with QC \()] TJ ET BT 35.250 561.074 Td /F4 9.8 Tf [(central panel)] TJ ET BT 95.398 561.074 Td /F1 9.8 Tf [(\) could be visualized \()] TJ ET BT 189.680 561.074 Td /F4 9.8 Tf [(lower panel)] TJ ET BT 243.325 561.074 Td /F1 9.8 Tf [(\).)] TJ ET Q 0.965 0.965 0.965 rg 26.250 314.059 555.000 218.018 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 532.077 m 581.250 532.077 l 581.250 531.327 l 26.250 531.327 l f 26.250 314.059 m 581.250 314.059 l 581.250 314.809 l 26.250 314.809 l f q 112.500 0 0 112.500 35.250 409.827 cm /I47 Do Q q 35.250 325.309 537.000 78.518 re W n 0.271 0.267 0.267 rg BT 35.250 394.303 Td /F4 9.8 Tf [(Fig. 2: DTI QC review tool. Upper panel: For the same subject as in Figure 1, the difference to the weighted average )] TJ ET BT 35.250 382.398 Td /F4 9.8 Tf [(is shown for every volume \(x-axis\) and every slice \(y-axis\).)] TJ ET BT 35.250 363.028 Td /F1 9.8 Tf [(The color codes the number of voxels with more than 2 standard deviations from the average. )] TJ ET BT 441.688 363.028 Td /F4 9.8 Tf [(Lower panel)] TJ ET BT 498.580 363.028 Td /F1 9.8 Tf [(: A DWI with )] TJ ET BT 35.250 349.292 Td /F1 9.8 Tf [(substantial drop out artifacts is shown on the left. It can be detected automatically by comparing it to the weighted average \()] TJ ET BT 35.250 335.556 Td /F4 9.8 Tf [(low right panel)] TJ ET BT 104.056 335.556 Td /F1 9.8 Tf [(\).)] TJ ET Q 0.965 0.965 0.965 rg 26.250 125.344 555.000 181.214 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 306.559 m 581.250 306.559 l 581.250 305.809 l 26.250 305.809 l f 26.250 125.344 m 581.250 125.344 l 581.250 126.094 l 26.250 126.094 l f q 112.500 0 0 112.500 35.250 184.309 cm /I48 Do Q q 35.250 136.594 537.000 41.714 re W n 0.271 0.267 0.267 rg BT 35.250 168.785 Td /F4 9.8 Tf [(Fig. 3: The number of volumes excluded in the QC process are displayed separately for each subject and for each )] TJ ET BT 35.250 156.880 Td /F4 9.8 Tf [(of the diagnostic groups: HD early affected Huntington disease patients, PM premanifest HD patients, and )] TJ ET BT 35.250 144.975 Td /F4 9.8 Tf [(controls; the numbers 1 and 2 refer to the field strength \(1 = 1.5T; 2 = 3.0T\).)] TJ ET Q BT 26.250 91.123 Td /F4 12.0 Tf [(Discussion)] TJ ET BT 26.250 71.169 Td /F1 9.8 Tf [(In order to study the effect of DWI artifacts on HD specific WM changes, we developed a QC framework to detect and remove )] TJ ET BT 26.250 59.264 Td /F1 9.8 Tf [(motion artifacts in DWI. Many tools have previously been developed for QC in functional MRI \(e.g. TSDiffAna; )] TJ ET 0.267 0.267 0.267 rg BT 26.250 47.359 Td /F1 9.8 Tf [(https://cibsr.stanford.edu/tools/ArtRepair/ArtRepair.htm)] TJ ET 0.271 0.267 0.267 rg BT 258.173 47.359 Td /F1 9.8 Tf [( or ArtRepair Toolbox; )] TJ ET 0.267 0.267 0.267 rg BT 356.248 47.359 Td /F1 9.8 Tf [(https://sourceforge.net/apps/trac/spmtools/)] TJ ET 0.271 0.267 0.267 rg BT 535.629 47.359 Td /F1 9.8 Tf [(\). Also )] TJ ET Q q 15.000 33.073 577.500 743.927 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(We also observed increased FA values in the corpus callosum of control subjects when compared separately to premanifest )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(and early HD subjects scanned at 3T.)] TJ ET 0.965 0.965 0.965 rg 26.250 539.577 555.000 206.114 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 745.690 m 581.250 745.690 l 581.250 744.940 l 26.250 744.940 l f 26.250 539.577 m 581.250 539.577 l 581.250 540.327 l 26.250 540.327 l f q 112.500 0 0 112.500 35.250 623.440 cm /I45 Do Q q 35.250 550.827 537.000 66.614 re W n 0.271 0.267 0.267 rg BT 35.250 607.917 Td /F4 9.8 Tf [(Fig. 1: Schematic flowchart of quality check \(QC\) data processing for an example subject \(HD patient at 3T\).)] TJ ET BT 35.250 588.547 Td /F4 9.8 Tf [(Upper panel)] TJ ET BT 91.595 588.547 Td /F1 9.8 Tf [(: series of sagittal slices with and without motion artifacts. The QC algorithm eliminates the respective volumes )] TJ ET BT 35.250 574.810 Td /F1 9.8 Tf [(\(i.e., vol. no. 26 and twelve further volumes for this data set\). Differences in FA maps calculated without and with QC \()] TJ ET BT 35.250 561.074 Td /F4 9.8 Tf [(central panel)] TJ ET BT 95.398 561.074 Td /F1 9.8 Tf [(\) could be visualized \()] TJ ET BT 189.680 561.074 Td /F4 9.8 Tf [(lower panel)] TJ ET BT 243.325 561.074 Td /F1 9.8 Tf [(\).)] TJ ET Q 0.965 0.965 0.965 rg 26.250 314.059 555.000 218.018 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 532.077 m 581.250 532.077 l 581.250 531.327 l 26.250 531.327 l f 26.250 314.059 m 581.250 314.059 l 581.250 314.809 l 26.250 314.809 l f q 112.500 0 0 112.500 35.250 409.827 cm /I50 Do Q q 35.250 325.309 537.000 78.518 re W n 0.271 0.267 0.267 rg BT 35.250 394.303 Td /F4 9.8 Tf [(Fig. 2: DTI QC review tool. Upper panel: For the same subject as in Figure 1, the difference to the weighted average )] TJ ET BT 35.250 382.398 Td /F4 9.8 Tf [(is shown for every volume \(x-axis\) and every slice \(y-axis\).)] TJ ET BT 35.250 363.028 Td /F1 9.8 Tf [(The color codes the number of voxels with more than 2 standard deviations from the average. )] TJ ET BT 441.688 363.028 Td /F4 9.8 Tf [(Lower panel)] TJ ET BT 498.580 363.028 Td /F1 9.8 Tf [(: A DWI with )] TJ ET BT 35.250 349.292 Td /F1 9.8 Tf [(substantial drop out artifacts is shown on the left. It can be detected automatically by comparing it to the weighted average \()] TJ ET BT 35.250 335.556 Td /F4 9.8 Tf [(low right panel)] TJ ET BT 104.056 335.556 Td /F1 9.8 Tf [(\).)] TJ ET Q 0.965 0.965 0.965 rg 26.250 125.344 555.000 181.214 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 306.559 m 581.250 306.559 l 581.250 305.809 l 26.250 305.809 l f 26.250 125.344 m 581.250 125.344 l 581.250 126.094 l 26.250 126.094 l f q 112.500 0 0 112.500 35.250 184.309 cm /I48 Do Q q 35.250 136.594 537.000 41.714 re W n 0.271 0.267 0.267 rg BT 35.250 168.785 Td /F4 9.8 Tf [(Fig. 3: The number of volumes excluded in the QC process are displayed separately for each subject and for each )] TJ ET BT 35.250 156.880 Td /F4 9.8 Tf [(of the diagnostic groups: HD early affected Huntington disease patients, PM premanifest HD patients, and )] TJ ET BT 35.250 144.975 Td /F4 9.8 Tf [(controls; the numbers 1 and 2 refer to the field strength \(1 = 1.5T; 2 = 3.0T\).)] TJ ET Q BT 26.250 91.123 Td /F4 12.0 Tf [(Discussion)] TJ ET BT 26.250 71.169 Td /F1 9.8 Tf [(In order to study the effect of DWI artifacts on HD specific WM changes, we developed a QC framework to detect and remove )] TJ ET BT 26.250 59.264 Td /F1 9.8 Tf [(motion artifacts in DWI. Many tools have previously been developed for QC in functional MRI \(e.g. TSDiffAna; )] TJ ET 0.267 0.267 0.267 rg BT 26.250 47.359 Td /F1 9.8 Tf [(https://cibsr.stanford.edu/tools/ArtRepair/ArtRepair.htm)] TJ ET 0.271 0.267 0.267 rg BT 258.173 47.359 Td /F1 9.8 Tf [( or ArtRepair Toolbox; )] TJ ET 0.267 0.267 0.267 rg BT 356.248 47.359 Td /F1 9.8 Tf [(https://sourceforge.net/apps/trac/spmtools/)] TJ ET 0.271 0.267 0.267 rg BT 535.629 47.359 Td /F1 9.8 Tf [(\). Also )] TJ ET Q q 15.000 33.073 577.500 743.927 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(We also observed increased FA values in the corpus callosum of control subjects when compared separately to premanifest )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(and early HD subjects scanned at 3T.)] TJ ET 0.965 0.965 0.965 rg 26.250 539.577 555.000 206.114 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 745.690 m 581.250 745.690 l 581.250 744.940 l 26.250 744.940 l f 26.250 539.577 m 581.250 539.577 l 581.250 540.327 l 26.250 540.327 l f q 112.500 0 0 112.500 35.250 623.440 cm /I45 Do Q q 35.250 550.827 537.000 66.614 re W n 0.271 0.267 0.267 rg BT 35.250 607.917 Td /F4 9.8 Tf [(Fig. 1: Schematic flowchart of quality check \(QC\) data processing for an example subject \(HD patient at 3T\).)] TJ ET BT 35.250 588.547 Td /F4 9.8 Tf [(Upper panel)] TJ ET BT 91.595 588.547 Td /F1 9.8 Tf [(: series of sagittal slices with and without motion artifacts. The QC algorithm eliminates the respective volumes )] TJ ET BT 35.250 574.810 Td /F1 9.8 Tf [(\(i.e., vol. no. 26 and twelve further volumes for this data set\). Differences in FA maps calculated without and with QC \()] TJ ET BT 35.250 561.074 Td /F4 9.8 Tf [(central panel)] TJ ET BT 95.398 561.074 Td /F1 9.8 Tf [(\) could be visualized \()] TJ ET BT 189.680 561.074 Td /F4 9.8 Tf [(lower panel)] TJ ET BT 243.325 561.074 Td /F1 9.8 Tf [(\).)] TJ ET Q 0.965 0.965 0.965 rg 26.250 314.059 555.000 218.018 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 532.077 m 581.250 532.077 l 581.250 531.327 l 26.250 531.327 l f 26.250 314.059 m 581.250 314.059 l 581.250 314.809 l 26.250 314.809 l f q 112.500 0 0 112.500 35.250 409.827 cm /I52 Do Q q 35.250 325.309 537.000 78.518 re W n 0.271 0.267 0.267 rg BT 35.250 394.303 Td /F4 9.8 Tf [(Fig. 2: DTI QC review tool. Upper panel: For the same subject as in Figure 1, the difference to the weighted average )] TJ ET BT 35.250 382.398 Td /F4 9.8 Tf [(is shown for every volume \(x-axis\) and every slice \(y-axis\).)] TJ ET BT 35.250 363.028 Td /F1 9.8 Tf [(The color codes the number of voxels with more than 2 standard deviations from the average. )] TJ ET BT 441.688 363.028 Td /F4 9.8 Tf [(Lower panel)] TJ ET BT 498.580 363.028 Td /F1 9.8 Tf [(: A DWI with )] TJ ET BT 35.250 349.292 Td /F1 9.8 Tf [(substantial drop out artifacts is shown on the left. It can be detected automatically by comparing it to the weighted average \()] TJ ET BT 35.250 335.556 Td /F4 9.8 Tf [(low right panel)] TJ ET BT 104.056 335.556 Td /F1 9.8 Tf [(\).)] TJ ET Q 0.965 0.965 0.965 rg 26.250 125.344 555.000 181.214 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 306.559 m 581.250 306.559 l 581.250 305.809 l 26.250 305.809 l f 26.250 125.344 m 581.250 125.344 l 581.250 126.094 l 26.250 126.094 l f q 112.500 0 0 112.500 35.250 184.309 cm /I48 Do Q q 35.250 136.594 537.000 41.714 re W n 0.271 0.267 0.267 rg BT 35.250 168.785 Td /F4 9.8 Tf [(Fig. 3: The number of volumes excluded in the QC process are displayed separately for each subject and for each )] TJ ET BT 35.250 156.880 Td /F4 9.8 Tf [(of the diagnostic groups: HD early affected Huntington disease patients, PM premanifest HD patients, and )] TJ ET BT 35.250 144.975 Td /F4 9.8 Tf [(controls; the numbers 1 and 2 refer to the field strength \(1 = 1.5T; 2 = 3.0T\).)] TJ ET Q BT 26.250 91.123 Td /F4 12.0 Tf [(Discussion)] TJ ET BT 26.250 71.169 Td /F1 9.8 Tf [(In order to study the effect of DWI artifacts on HD specific WM changes, we developed a QC framework to detect and remove )] TJ ET BT 26.250 59.264 Td /F1 9.8 Tf [(motion artifacts in DWI. Many tools have previously been developed for QC in functional MRI \(e.g. TSDiffAna; )] TJ ET 0.267 0.267 0.267 rg BT 26.250 47.359 Td /F1 9.8 Tf [(https://cibsr.stanford.edu/tools/ArtRepair/ArtRepair.htm)] TJ ET 0.271 0.267 0.267 rg BT 258.173 47.359 Td /F1 9.8 Tf [( or ArtRepair Toolbox; )] TJ ET 0.267 0.267 0.267 rg BT 356.248 47.359 Td /F1 9.8 Tf [(https://sourceforge.net/apps/trac/spmtools/)] TJ ET 0.271 0.267 0.267 rg BT 535.629 47.359 Td /F1 9.8 Tf [(\). Also )] TJ ET Q q 112.500 0 0 112.500 35.250 623.440 cm /I45 Do Q q 112.500 0 0 112.500 35.250 409.827 cm /I54 Do Q q 112.500 0 0 112.500 35.250 184.309 cm /I48 Do Q q 0.000 0.000 0.000 rg BT 291.710 19.825 Td /F1 11.0 Tf [(4)] TJ ET BT 25.000 19.825 Td /F1 11.0 Tf [(PLOS Currents Huntington Disease)] TJ ET Q endstream endobj 266 0 obj << /Type /Annot /Subtype /Link /A 267 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 623.4405 147.7500 735.9405 ] >> endobj 267 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure1final.tif) >> endobj 268 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /ColorSpace /DeviceRGB /Filter /DCTDecode /BitsPerComponent 8 /Length 9183>> stream JFIF;CREATOR: gd-jpeg v1.0 (using IJG JPEG v62), quality = 90 C     C   " }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz w!1AQaq"2B #3Rbr $4%&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz ?ml/d1%Á!c\ տzhi.G?mF=e݋!aȍ; (G8ހ!ĸNg&C/c4}/ej炵O xR֭"IRK|lV >SʏucO3'HcTAWf3ݱpҢe[~Gl"Uy-?\miSH::]wMs!)`0I?([?t?xn:iwBL9$ۀA[y rKN6rW[=>ʍTA#=S^| -L.5O0. T 8`0qjVnpۗ?(ܸv[z$άuCFb>p$t/mep10L9E5}FwP|9X\ -lE 3*j?0~ xO'K7!qWʸXmAOr*5=͑\IrѾv*ӱU#U}GaZkK7 #F;#GS0A55MqbakQDL=rklΥ&%^%J^@cFW|a_Z/1oZv]2x턌"h1\o 7cWbwW9޽7[t;"e{a?6I|ƍÕ,u|KտtUy{P{[]\8wvh\W}+&!+ ; aOL /޺ x[&a5fG@!ػ SڰK8Qj6QA-reW 0T &>|oJF4GUXƗ1W#q\y`;VEt`~x=7V]O<&F91Q^q_|.[yZ^ R3HvFy 3zo\kAJS@P8#Q :ʰJ3;bP mRmj`bpc~? u})a6!0Mg +xB4,- +H#EP( 䀠f?.6eZ!g6bUT'[ms^(gB7 #^Mણd8k+i6un#>覞`# Px? |ʠgi1JcoyV)r瞆u߉0goַ J(<߼kȵńN'adKlHv>e iXķv97zlt!b|o|L2qʹU,>sOco{ Y6rC|~ K`>E|[w?wjeb8P,b=пhZo$oidΟCK1k`W]_^}̓H v'$ Vq@*޻> užgxqr-n򧣨:{WC%MYѼ _xquk^9 fmD b1O`H~9Դ|1,hS43+<)'+~xJth-#D.Fl_:au;[gKkZWc7JneA.A9'2|QMchZ?B_lM; sIS@kxޏyt綷y-%€W n@ndeS܎9^ŚM5ϱ[%P.Il '8OjZtKkg6%5e  +Ck3dr͞*`/W}dmT *DrWdyl"64([Ga\-4*y[gx-`~A*g1Eٸ*:irH_ʛ>VeEu4$XGSy+VwZGcrĪO??nZt1j"xVBbsg*vgrB4? rX?v~7V}Wœ<90$iwN-ߏҩne1?zj-R[)Q`A0Hs-:^Cy~)PzL"^7W Kd9uh@G^FHʡ;W]O^B~~ ƳCV1Ԅ, ߳ѻJ_H?(CV8OZSpڞwx~[9;c;G??п^:~d$l̢(wvO}sV>V>M37Zݰ3l~rVmiu)f->H i^IQɒ ;1ThrG*N[wwDP 9 zN^8կ'5XV{_,SzwsP7otYcoݏ1$mJLH'%~`|I5osrݙ_\)UJXy!Rvd 5W$7F$2gj+*x_Sլ׳^ۆB>´iYu{tE jzݍ ϩ 6ł=O;g:Z]OmZ^eyb_:i6H2Fyx4[Y_%GR9Y}0ߍhIUy5}wUOʭ'T ۤ A5R]E:m-:C$յ*x{b("3BH5;{&%Xo1!;{qK/  G$m,q-E(U<# xy85sA޷xDHS\2F("Rx%GQqTskh1[D\D=Ti[t}vtiʵ)ԳwOoeʬx猵ٴ-!kX,ZHHس(bOԚ$洵"\4Yr@'fאՙV&A({O[7RbbфeR{8S玸!c?*σ:o8[ H,޵Eb&|j]MOVp4dӮ[^ uméM%nTݤ 6 #yo]-V!DЫG V pX'I{ Wīskz,eB%XwaxwK;M:%Wc\zpt#F)5gmQu~g֍Z>IS{t]>PdX4@R1(QpycJo [i:u$ו(a384B!p,TP Džiw:5, 3yb6⫐2×Kzݽ6urw1Jvp.qGUm6ޚGXԟNlE!ga0! >j 9?¿j:}nHv H"drXFyۯ#|Cq5ے+!Yb;ҟ>,60Yjld`ќR4drkoq6wԤ+i,cTgQPr;08ڍג|](<@(^<ܫ~gTo{ߊ&?g5Yۧɥ^9zvV%x~~h=XChιIca=ȯ5/$u:|7#6wm-YҸQAzTb oYX9w?]9UaƦ"7ev*p: |B|=30+d#Au ڼ_[P3H7ROIX޳J<*g#*;NIknU~o$\Uv) CN.H6 W o6xOI:%|DÎ+ 7>%h6ڏt~DSPA/VNHqQӋ72إ=JҴhH "ݕ g@9oB4X,4[[)bY,I5H:2:֒/o~}YP[C4m8r4 h+`ⶳcBl'ViR@>ta*wcמRZA"PӰQcJO]u{tmZjOdK|D,q}/po>4LAPD{\X'r7 è9o_'Ѽ[$r0?uW,8YGt#牬Q-[w<"Cc?'| O i0@`.&)W{L%O|WxtnWC],=Fwzvv3__sfQx'ÑKuooB}ty? ?B^@ E'Z(h>b'߰uXLۼQ['Tv'1aW,-k xbhg*0!A\E}k eGRֿ+I}_ޫB~w%ZJ0>tv>CL{o}29%E@v /n޻ #ڇ9 ']3A&Hӭ A$>Ǐ *L`+fv~WPkfsqVM9E.rhWZO+u7|M&ݝyt]u?WηVHo!!@ߧJؓ\]\|tg^">0+]=Qy\[ in}'Ҫ0t <78]:'W m˖ =_MK;%Yi>׺㿙߷exhma7Yne 0r@_:xB:q=Զ{)x$duWq@xE<6:yB_.$F`t6TUm0w*}iB8l}z+vMkN .$Xa.;*I$o'wYm-|7׭6 7 lbr>S_7(aGe:nruO=#lt#2s (EPIE R P =|5ּ_:[w> endobj 270 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/test.png) >> endobj 271 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 150 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream x1 aK&> 2K:%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%j _9R endstream endobj 272 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /SMask 271 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 150 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 21275>> stream xydy'w}Ve=͞!9$3+QҒVK[jE,/axa$a 6lXZz!%:CDgLzʬ;?xG4 _/⋈Ǣ((19_~y0T?ӟ!X p(F^:>&*sjyn65鄢W.d  `ܪL(~ew0l uۍOQ9F ²Ɔ/^y_ &1 Q#@!0?r9qh{)?c^~VG\/1u~A???>r@G ~2 rc=7 8@%^`ccKX2^ܑM\C_!0 <#q[!R@U["` ؀ |!XE^.q\iSO=%#\aq%<G`=%vۍ./}@ #ÞBnhD^+ՑV.[" Z  @SI@4|ow2!b9ht 'fr^"WE{SX!Pvjޒ5.//}t:;Mk6"l]ɧ>ǂ+ .0MU*hD F"ҁ<`}>pc-b4B!ٝ;w;7+VYhw!WXS| Ѕ8UN Z)P{*H\ps*&Sр`;ez|.;/xS^ &“p̜!ХPg6]]?qVś1X'b-fшC"2j> S8PRIv֭&·+wL^Z,SFojtV5"q677+ PaT.c1T5l”.. ;SfpX@o0qCMPLVԛ6 p-m)Fva(g<"[N <n6#5993?WM>\b'?I/k!+`J Ύ_xRp ,%1  v<F@dva a3?  3oKeK]0MC= ^P^G RK]ggٴ|M  Si$ZC@H!C"V*~+ls~>>>.e֭F:ظ(Jtu\ %7J0oxpp8;xJ+1`n7BW{Omlfa@L7+u+̃#֡p⏟ƛ}Q>EfNrW䴇pvghzEwΎ>ϜLt7`3U\ 2coM@O}I(u( 54b?%)҅r7nJb nS`6ϯAt>B*v NNבֿYqĊRzdz۶WWWu]?#?RToS'8S)9k 4~|e,^\NhhWt蝎?}uf<3@e h@[̔Is4qxXX}6uǗEn-C۷ol'#)~'.KHWvZn cF Uȴm1%OO48"UQ!Il^yF#u0 - ci2aepKTEJ=QBI=4ƥ;؀W5BJ29+_eY7nMIݵEFQ~gBOBڹK3U4Oi0ޜK_ap$t9.qR0;]!@<'ѫ t S!Y&$bGdW4V +c[(yS!1 Jivxxd`yRB ?M [ q(^Bq!@ŷ߃oHt%F-:Tri}E߱8K̴?zVjjڿw-!b-GXd,>%"%OSu 9`颓;\ c QA/nEH@ŀ@,7"y^5Bw_T^i/t-%­_S<v{7hϐTKT `]+6@II>(cy{9I2)\ w=}OMX予#,9RA >P'2 W F{tT&Q-,Hk=Slf/Qww"3 8X@YO30TKA5*v}xxw3ĮURk]3:#`踑)O@(3E, $`Q[/8ȟ@CKYW>rl`>?e U 7 V!>!(s/66FBq1 c^@LAHgyf:W.9tAQ8P_,m1i*Lkwy1^*d- RҿB!U.l9Ih&N ~q_y`y5~y33Kai flSoAԻ6/ e+_PG(](q-VW~TcDWf6T( >=N=r&56sG/&CMh4::: @.+++@ 1e;\%g?xQ gp\U#TbլDxNQꈍdžBlq uXŮ_'+[D};aȕjiw䩙}U"}f33aB1'[oQ)c 8>*I"8=bn߸ AlfApv!ZhQ,r0>MŌ}?OgR={i@VM 5RTбJB и"$Ji|bK;M] D,-iH/wk 6C$&L,WYPdev~n s& xH]ݺu֭[ S%{U")z]vM-SUGphA,IJn>'!="wFOY]͛pdD m) 꾙\^O7^aY./C4*#07w1Il6siCUÿxS )gAM.K 銚(b8=jڒ=ѿhKaXA6e"2:yL./-劀³Gʉ һ]]ȨWHy#~ާDkӎ|^ TJzS:O$1' PKߒ 5OP*q%("DGxh%uٟf}Ռq~t!M6+J"AHּAb1M} ˅Wx;wjJx%#)/}K߽{m ҁ Or3vrB0-1cN*EYKnj{CH P%Ģ(h9giDٔbTNE qI'!H~qqё?]$%$ $ `_BYlT^gV-61^]YtXn[ W8ç(9v"N6@;@h36T^0}cu0~ @G9^  ,^OVss"U1oy. yוLE4y3tҬA^"&D fʳSPlh :qODyMR>,KӤ`uz?REΰtezQ*r*R'ӴFƨV80I0? Pnx`1zUUM%ɀ6ouUSɇsOoIS$`s)+[(bC"Z9Q,􅮋ZM;;K2{a.gVM7r$td̶\a6peMF.' w||ٜh%PNzUbBynB&z]k4ȹ+a C$2W0gz0+L%6Pu zdmz(X*Sc0SsE؜&RGBO9 cR+L<ΨV梣Лͪr`3`)L3PL0u5Q7,qxBuQ>M]k,^ء{"k[%y"D>bmZ,ߏz=ol?-Tty]tJ[F#u0Yd s S<{)zg$uz\RI:3)5T"9#uya%(Y`\4@5q:) :HYNkfC,0Xg>@=rLgwu|,m25yGr "IV}!|W^y _‹/oH9Z :xX``:]qm"|B1 `%Uۏ >0h ]B%DrwvwfY07o޼{:dM&c;+̺OY}JW=_r%蕁.{GLxJXr ~~Y|2{}s3i?g C,&!Ue̲TDe0M1Ɣ?.gTIPQ\I%] jwiIt뙞keE? "W";jUIa(H>猇qBڷ634Mnz`YTU,Ci6f^=N\gz`b>Jf&be%e(T(,%nJU/υ.PN>47 ef]`O9;YNi(b 쩐G@d LsrJo[s>ʮϕDܸb B%X \Ma[Nl2bb8wN0:P~g'=MWVtaI_?fwl, v&OJ|1H) wޅm;pt?/O4V~:H!-'#66tBaX"pV +GUCԷb=iF8. r2#{ [o򕯄al6/k/vQx"]w6d^̇Fa*W oWY!S`ud}0K)0\UZ-JOА{L +(<[(* ?5M& #["c>5(;eE p!Oг`KŧT[ItmjQWz@9Q9KBjTM{ x{{o{\+B ؼ|Fc!_(T-K!Q@U29fZ͘ⵚV>q;5"/D,^ِj<@uct aJOV+ >╋ +_xw-g*rl\kkzEމMa03uQ'LCo̔Xd^#.n:}<5Ykjrchh|Ħ_ *pe,e1w3=_ $b11;3*ƚc2pjCI`Y(ŝ5 L "8RH]$"PlA0k:}y2]!:ccb,Y4[jCe7>{-oiIgT% .2.'\œpĒpj>]߳K4}@>G$ta T=*5!*%D/tNR! wzpn9yJmvEh.p 3,ԙB M  7^3N &^PjON.χaRY]]؀^1777ܹԁ'/^"Q%gb"]!JP0`찬ʳ룣Pl05;8Ҍezd l0TIc W& X׻z1ϝsi{^$?dwrr9e<9C(58RYS><;a!P"T=tYW~+y333Od4saC9fEBaii qidRxŜLw7e~ak@q(1pNLerSBEƆԒ#u1G':՗#N/AJ%TQ~jJy-ҿ Fx|Gx/uI'iJCHO+7j0N)NPR|fsS.B grq\mub:0YD*)QمES-iꮛpRy7̚ u7Od &I:YPD%ee'M 9.Ҝ) ah/UP._ʓO>"6 I 0È(|³ȳI9<Ӟ8p`qZLZ)U~J"# nNK0r\j"/n7㓒KrA q1 bj0gl&eXOa61R˳kkO?48L-M1ׯ;;Q&X)X̀ wUa0ٌ7jS ݻF#zqm:Vq ذN C}ښyY?nh#*c Ɔqtd X;Ep (04 vzȖuu$ֲ|jX^֎#&(ilj1Y֖NQxBj9L B*666.<+F!oy~~s!U8o3i寻д_CR l  Ӥow޽Լ-˟'W{ @%8+??g?yQO-ws0$w<˲c';Ӑc|]9YaDQy^ k豖ж |rx>ms8G\6y"}ZE4 'ִըhat"MS.[]]h8G.ҴB&I\ιa4WEe.9nh oE۶ht/j#1 cQQӴB4 ÙN{t*h49%7'e$Ye&-8JT* p8tG4u*ˑT"P9@\.WTL,ˆQ״k!뺓$0$ɾ-%?-2 Ce BPkVE4y^Ð9i.\D!}mۥR4\.l6 "?99wX,JJޞyĎJd2Q,1}~N5M+J\P(h60VԸi6WWGą>|yvvv(r]Dawi\Z22ZV(e9 NNNqDz|>_T"(] I0~ErVylZkaxxxqqjVVVSOxiZ”>:N>/DVP(t0Rc ]ZZr2 nKβ,GnJ))H\m1V.s-*=ސhZVRy߯iI)0_9+d0>B䲾n8B뺮4f16Lrq0$ DP(uBZV({iUt]!riZ;ι!%'8Mleu9eRDt,r9۶ èP~z*U]V777>LjZV#m;LRaHzvvvݏ|#aQćBE&eY׮]#ebL$5Lt~B\.W(nPXYY pjAu\rQi8N\.tmmۄ:Thض}zzzro&BU-=6 xnPX__'N4-/Zb6R\.GQT,Q$0Τ$+p84MOJRI,ih4...1hVFJ%9ѽah.--XEu;GGGobN:(J($ضM]=ι Z-E]>|Ȼ44MX)8̒}R^n޼YV%7(Jd6TUMzT׋"0s܍76x iKh4岮~4Mc۶B0$/vP0 c82^bH~O"sNTRls^*nݺEF_(\ץ0uP(4AM&yQ [n~pp@ @V]Tt]Fj_t<-2LӼvZ.{}?P(<䓝Nt jdދd8Ni4M[[[+a`ȶ퍍jZ.B>'ۀ4:[\NʏRwk}}="BUVXT*1Jy]~ݲ|>_TVHo---jgy& `iZt<+؄4Ympnܸ1Lhf^NtqE߾}L`": y0z}o2IU#ldbmIw3N_^(O!(&\a.$>vZ|>MIȲ,ZE7oޤo ["R\9Ŝ-r^9q;۶'G\ж\.&Wk6J91`|DLZ"vmO&\]^^r9qVWWUyd2!igY*!RdT*hD*!>e'83Lm+J4m<`EV׮]$V#EE8H q<#i-IA~u_\\xL8J8MمƤbH.Mc>'%Z?66!$&I9G`0 n{{X,v]THR̩f|mm.Қdnw8ZmX4hkZ-RL&aDi4|ׯw:jJsQl۞Nv|1VU2;e Q#4vO?d2١DJ^gNHh8꫍FZ]*uƶm?|p}}cl:Kҵk߿OB0xbHtb6!7-\.gv  fY(O?~bsNrQI?L&`0NoZ'l~%E+!y~~]U,Qo߾ s{0 CRt5M\]}@8 yVWWǙNdhF#ʬɌc.4WM$Egtv+vz~s^T;9 ۷߿O"Fv8yZ=88 =Z ]ðhMEgiBSA"S^SAضM4ɉeYbNCM7w9կH -Nsyy>1mtJ" uEdw]nK1&iPNɄ($n^T*x:uχQv]B=Bzq&gs!eYBa<K~sA0^R& d(]Ҳ,Rל Ib,z=:=h4?"(~/--I=0|^d2I󵵵zC2t EZN a>_ZZrh4u]YY)D hD=c"4!k"1DH!2'pibd$ad2!K}Ca7o\^^~7!- )D*q,)E6Llu¶m([1ȴ_>&灦uM3r9f4)cƺGMZj>0[yii|xxyB^/!grctwyy iZQdi_Z*jV,Lv˕ ۶l@.W P-E(3F[JbZ׀0frQl{y׮ E8_i}0Ѐx<,RyK6ia4t)Jm/GѵFc00 ji\8biIq `u=$%]- pE-<# )Q'\n4$ [[($eݶ(K%鍤dV{b^x<.Wc.|_Z'Aj\.\]-1K/Z-]'tzo:6---1~ܪa]m;h40vs s|Mlfhx@u^/xޙqDM,m{I@Ӵj7+˭it2J}ƾ 0MNf٬Tr]͛|>_,ðZ@m=F}\.s޾8|zh`29v@Ԍ %o%suu7Mrɘܲl,<#s*L&zVil6KVC*RneR{gy]|z~~OJV q6~(;^iʰbQ;T\iPdؑ"&aGQn>ɋNCR*VVV=s/"}[\.\\^^ ggg$Sx<^ZZ";wPP=)nnF]%tF1Nzz#BA@ZR)ONN?T9'yan?N?O ||8{M`tZ' ق`шP@ rs2eZsh<zqh4^eYggg~_VFݾy&cփ(‰1떴^{Bdy=zdYm3Hu}4M$vJlY[o%4yq=<#/1276669^v׃NNNKHez4~/T4jZT(^FWjU"w:1La .GEzvBzPooc֖ȣB! Xp84z](uaZuqS[qwӫhZCșe 4U!=Xz\u]iTjZdN~mr^MRGzSIFVk4SOȶms@&mootd2N6!oEF%R^qpp@eR1qyyiEO}~|<h#apqqA.]2uD*Qa0LSMvwwOOO>ݻwTӴuvvvd HZ<:h=Ȭ. aQ͛\n<6 BrZwyyI * rsjJ|>G4q lll :H @X|7C"%4RDDr~꺾cCL'G.Y$u9aKK'.* C %S4i l  2Z zZn>j- ( rooƍt>=Sr\sYHÃ"Pe^wzzj&9ZQJ} *ߗ3E6RG%$jxD싂GFmۚm˔ "RWɑ5~"J߿,JN)&cn:QrNCH`FV92r8jJ="gU垻]BD"AܿhXV-΃zǐx !SM 8$ wsMJYu]E1i )Aå/ް(zS<ϻښeu|B*JdWVstz.G"KSA}۞ ~.rZmuu$-9AK]lj!T#4xN]J ,zݲ|+$qB $Dc7"6f#LҝtJOžY_T}޽{DCQ}[߂%&IR>&HU-M|(ڪHNOӗ^ziwwk_ZE$nu/\4}o/9ENևe?Ԓ>fk]/ʃMFUu_Yxh_[9ZݎſB2o/ @E3q~zigc(} Ȣ+5;w| _㔫( ÂC!K(x;/&n?@Ŏ{e.utz|K5Uj_rE"p f‘QhWס489Hd\D  ̢^m~ef$zbH,Z>ƴ(bQiߡP\NJie^ah*ϑV([}o0ܸqIٶ,k<Oӫ&}8J9= 9 ꝙiNȓda\׉"tb/&/sdDbi~ED1F9K>YMKE:0-dww2fEEY̱gD;P֕K䢒A#vmm@7IȲM,t_?>H $mY}8ք!%3$3g~poewͲ =KD܃SxZ/Z"[ nooᶅoq*qށ9,Ya}~O)-`4z0! gabPj).58 $5fYrF鋴_G:cLHyMH{Xay>~NlY#'$/AcR'm" gS|TYMJk=fݲ^7?E<|Yba^` ZWM 7ֶU 歧S<~p#QUP(Pt@DŽ&Bif؎ed@@[O,ŎpVU#c~{NI#zo߾Ym6NZMZͬMZ?AHB5Yqg`D&^fZkρq XMңL 2sJ?3[f0coM int8ׯ_i !+h5E+.40Nّ)Zh_<8NouepIZ₱n1~vZZya$RueZe\z//T,=瞷,c8Ͳ, 7X.Bo7M pTRjd2MKyu}}YwZq^%sEf,z?(q* endstream endobj 273 0 obj << /Type /Annot /Subtype /Link /A 274 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 184.3087 147.7500 296.8087 ] >> endobj 274 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure3final.tif) >> endobj 275 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /ColorSpace /DeviceRGB /Filter /DCTDecode /BitsPerComponent 8 /Length 7726>> stream JFIF;CREATOR: gd-jpeg v1.0 (using IJG JPEG v62), quality = 90 C     C   " }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz w!1AQaq"2B #3Rbr $4%&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz ?1ψu 7t<1$'r˅܎eܪ` ȧ>8t=uYR[wod5RIHvn2zrpk7FS7rx~{bfdxNqU? |, <+eh.\6j td (o;#W-=ztmnw%-4#YgEFbcw |?o ש&rgMw'7Hw~Ѣnu[K=:OOe@Kʕߒp[~>SmmdcQ֒ Eْ%H1VY>hYYw z4aR9X2#GlE^ g]hڄm_Kk sraqT-g? [6it֖Z%)+Kj,æ*ÿoj%j mʮڪ,+W +,۝?oë}P7pW \)n?!xcDm"Yf>t7EF@%lH*s߲׆l>5iob{$k1#fu*Wui蟳?6[ZX[B?f܃i %;i (QEVѴ?m?/?ƱtwK$%&MFP9-=y]fFzI-Ww$FRCٌm=s\δ{mB7.uNF~ahѴ𗗧xoN؁ fѻ,O\k~akhI*MY)4П6G~a?U'k?04oP|uk5Fw (c*Uoq0Y6ֿ'cv~zL?TjhZ?6Ui:=VvV| .H,H$5d_ڑ2F~ahѴ_?Q_ѵ?m?Ɨ}~ah?m?ƏO}oѵ)~k?0E'?(uF~"6(uoF~"6(}oF~"6(}oF~"6(}dZQCs~zѵY6F~>mc} #?Tywyl''?`f[BL?Wط~Ξ*T6bX emp?"nW_oh_ؤѵX O >i?0GE}> ,-m\wB$O;}hѾi?0G?+|:B\~2Iuy'?0DKwM.p WxcO}~+gka=ٔ&" N#\0:~a?m/Q@ #j2zWx#otia?6lqJ/93\nCZno|Y%Z鴓_X> mK ! LWyqh'-cR2n+jѡfU@$`^/MiYߵG/&dX,~KZo 0# ֋Y\MjTkF{«+*,B6%=Fz~ ?#J/?:>o=уz~ _T}O΀Bz~mo(O0lZo&DɏwnzOv-/atR䗲 a@׍~ط?YT{, d*?|(_ŗCBz}OΏTa?min?}{'^7Bg?ki}%OkxJ#**wb%.Usm6~F_lo Fz~_dB~#+|Yu}3C5\[B4>iYe8Es!ֺS[*qONiKؓB~#++>2Vko1`!t'RTTW^ 8"S3!еGG} Ȱ񥆡jZDPj)qb˧Oo)Ja2+QKt#qu<{E} ?-?U-Kvzfuy"O3Gkk$Ұ@I gn0A$i> E&% qm$R(ade A GPY6'Ϗc!Hjͷpb6=;{˵ԭ'mϵ-l[y?gO*L ~^κ+jn/>.O)4'\.͞*|8 1_]>*Դ_ M_ºΑ`׿Wvrs4WªP|ʪFIċ#:ՠ+Ӭq?W_{fܜ0}Ÿt gYy0;jV9W-<,69\qgoqx[쌺~y3zՌfոnТW12WvY.WhZУB~#`^zKLuX.Cn?m]q'Wϊs h$5OGmNk-YZ-yƙFg .B+͹v=GB~#my IP^V2^Fkjf\ 7o\{os+[,VͲw2F=N^!#Us8Q0 #tcM։w\I4&E(aA*+|>n=9=W>^].i\9t67ֺ #ȫ3YZFص]vT jL?UtA9na5&(N~g~dI4 ̿7UYE_I#-=FQ(_=s:Fr5wml/$iR}_O*)؛`ǕʢL?Ui}&DX6wMs@ȡmUq V~'OY:]̟:,cڤE&b< `3EE?o?O>iS .EE??O>iP1L7Ui}f2ϬߚTyϿ>(|Po?>/G?>i}fRϬߚTyϿ>(|P x#Kޒ]߭0 E 2#;7EdC~N GPE-0ng3vh-w^qcq/_?ַ?ҧ7RuO*u!Y4⫊4Ϗq_ϼ20>Νsiss{ܧ}_O*>~iRϿ>(|Ti}f.Og_OV?tγ-c1<#?Tk}_O*>~iW?ީuscX\uq"";xY~'E<3=c[XdDQ ?P@3T7U/eY4⪆8|K[jzrW|nٍF` ϟ} 2ϬߚTQ>0ZTմ6-[$J 85|sFOu|EMJb&x'bv47@oWWkn Xތwv ՊtHc9uVMs{s)Uy+Dݻ "U4Bux{+ 0>4mgM (>Ei8@w O$$u}`XXn v;7~B9Ս+फ़ iX]] KDW (WT G:mqc{\VFjٸب,66L1~kJρPO\(OOƀ2|3<1?7?Ʋ|3q(dEy=[2Ϥ%OW?|{v%d̳̿-ـΝsk|n6(:;y='egO[HxgN G]?ٿG'fOƏ>K5lh}YZ\l?͟6?kW3Ϥdwl?y/KGiz~?}>7I}/OƀO>}(L'EOj2}*#pw89? S3GJ>gکkv`GȐ5|.>Myۜg5ԙ9K;yi-wm6S2oLLki͜]۸&ãs+˾!?4{[?瓏.e!p;dqWxC_>cö]MY x 0w=E{rUR>e'f3t&|w^0<>Z[j:LV^s3Djl¨,*X `g?ᏆA y7\vuB 0a]xf⫙{.^-|rv/2c]KJҮ/-̫GqҺ_KhmyFPN?: ~77n6:7d`G7LOh~{Ft-TA`mɚ5@+tlH9 ''Ȼr}Sϵeidl_?;FXӎx?fi,|~k:c?TlgڌVd sQ3 #!q?<3?.y;qjMzeC V"I07fU,$v*y>0#i:'==qנ 3E@R*-c##9l~P=hPFq (rzPNP_c1i3ZEa@14QLEhF ,dkEq]QES (( endstream endobj 276 0 obj << /Type /Annot /Subtype /Link /A 277 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 46.4573 258.1732 56.3779 ] >> endobj 277 0 obj << /Type /Action /S /URI /URI (https://cibsr.stanford.edu/tools/ArtRepair/ArtRepair.htm) >> endobj 278 0 obj << /Type /Annot /Subtype /Link /A 279 0 R /Border [0 0 0] /H /I /Rect [ 356.2485 46.4573 535.6290 56.3779 ] >> endobj 279 0 obj << /Type /Action /S /URI /URI (https://sourceforge.net/apps/trac/spmtools/) >> endobj 280 0 obj << /Type /Annot /Subtype /Link /A 281 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 623.4405 147.7500 735.9405 ] >> endobj 281 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure1final.tif) >> endobj 282 0 obj << /Type /Annot /Subtype /Link /A 283 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 409.8270 147.7500 522.3270 ] >> endobj 283 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/test.png) >> endobj 284 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 150 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream x1 aK&> 2K:%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%j _9R endstream endobj 285 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /SMask 284 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 150 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 21275>> stream xydy'w}Ve=͞!9$3+QҒVK[jE,/axa$a 6lXZz!%:CDgLzʬ;?xG4 _/⋈Ǣ((19_~y0T?ӟ!X p(F^:>&*sjyn65鄢W.d  `ܪL(~ew0l uۍOQ9F ²Ɔ/^y_ &1 Q#@!0?r9qh{)?c^~VG\/1u~A???>r@G ~2 rc=7 8@%^`ccKX2^ܑM\C_!0 <#q[!R@U["` ؀ |!XE^.q\iSO=%#\aq%<G`=%vۍ./}@ #ÞBnhD^+ՑV.[" Z  @SI@4|ow2!b9ht 'fr^"WE{SX!Pvjޒ5.//}t:;Mk6"l]ɧ>ǂ+ .0MU*hD F"ҁ<`}>pc-b4B!ٝ;w;7+VYhw!WXS| Ѕ8UN Z)P{*H\ps*&Sр`;ez|.;/xS^ &“p̜!ХPg6]]?qVś1X'b-fшC"2j> S8PRIv֭&·+wL^Z,SFojtV5"q677+ PaT.c1T5l”.. ;SfpX@o0qCMPLVԛ6 p-m)Fva(g<"[N <n6#5993?WM>\b'?I/k!+`J Ύ_xRp ,%1  v<F@dva a3?  3oKeK]0MC= ^P^G RK]ggٴ|M  Si$ZC@H!C"V*~+ls~>>>.e֭F:ظ(Jtu\ %7J0oxpp8;xJ+1`n7BW{Omlfa@L7+u+̃#֡p⏟ƛ}Q>EfNrW䴇pvghzEwΎ>ϜLt7`3U\ 2coM@O}I(u( 54b?%)҅r7nJb nS`6ϯAt>B*v NNבֿYqĊRzdz۶WWWu]?#?RToS'8S)9k 4~|e,^\NhhWt蝎?}uf<3@e h@[̔Is4qxXX}6uǗEn-C۷ol'#)~'.KHWvZn cF Uȴm1%OO48"UQ!Il^yF#u0 - ci2aepKTEJ=QBI=4ƥ;؀W5BJ29+_eY7nMIݵEFQ~gBOBڹK3U4Oi0ޜK_ap$t9.qR0;]!@<'ѫ t S!Y&$bGdW4V +c[(yS!1 Jivxxd`yRB ?M [ q(^Bq!@ŷ߃oHt%F-:Tri}E߱8K̴?zVjjڿw-!b-GXd,>%"%OSu 9`颓;\ c QA/nEH@ŀ@,7"y^5Bw_T^i/t-%­_S<v{7hϐTKT `]+6@II>(cy{9I2)\ w=}OMX予#,9RA >P'2 W F{tT&Q-,Hk=Slf/Qww"3 8X@YO30TKA5*v}xxw3ĮURk]3:#`踑)O@(3E, $`Q[/8ȟ@CKYW>rl`>?e U 7 V!>!(s/66FBq1 c^@LAHgyf:W.9tAQ8P_,m1i*Lkwy1^*d- RҿB!U.l9Ih&N ~q_y`y5~y33Kai flSoAԻ6/ e+_PG(](q-VW~TcDWf6T( >=N=r&56sG/&CMh4::: @.+++@ 1e;\%g?xQ gp\U#TbլDxNQꈍdžBlq uXŮ_'+[D};aȕjiw䩙}U"}f33aB1'[oQ)c 8>*I"8=bn߸ AlfApv!ZhQ,r0>MŌ}?OgR={i@VM 5RTбJB и"$Ji|bK;M] D,-iH/wk 6C$&L,WYPdev~n s& xH]ݺu֭[ S%{U")z]vM-SUGphA,IJn>'!="wFOY]͛pdD m) 꾙\^O7^aY./C4*#07w1Il6siCUÿxS )gAM.K 銚(b8=jڒ=ѿhKaXA6e"2:yL./-劀³Gʉ һ]]ȨWHy#~ާDkӎ|^ TJzS:O$1' PKߒ 5OP*q%("DGxh%uٟf}Ռq~t!M6+J"AHּAb1M} ˅Wx;wjJx%#)/}K߽{m ҁ Or3vrB0-1cN*EYKnj{CH P%Ģ(h9giDٔbTNE qI'!H~qqё?]$%$ $ `_BYlT^gV-61^]YtXn[ W8ç(9v"N6@;@h36T^0}cu0~ @G9^  ,^OVss"U1oy. yוLE4y3tҬA^"&D fʳSPlh :qODyMR>,KӤ`uz?REΰtezQ*r*R'ӴFƨV80I0? Pnx`1zUUM%ɀ6ouUSɇsOoIS$`s)+[(bC"Z9Q,􅮋ZM;;K2{a.gVM7r$td̶\a6peMF.' w||ٜh%PNzUbBynB&z]k4ȹ+a C$2W0gz0+L%6Pu zdmz(X*Sc0SsE؜&RGBO9 cR+L<ΨV梣Лͪr`3`)L3PL0u5Q7,qxBuQ>M]k,^ء{"k[%y"D>bmZ,ߏz=ol?-Tty]tJ[F#u0Yd s S<{)zg$uz\RI:3)5T"9#uya%(Y`\4@5q:) :HYNkfC,0Xg>@=rLgwu|,m25yGr "IV}!|W^y _‹/oH9Z :xX``:]qm"|B1 `%Uۏ >0h ]B%DrwvwfY07o޼{:dM&c;+̺OY}JW=_r%蕁.{GLxJXr ~~Y|2{}s3i?g C,&!Ue̲TDe0M1Ɣ?.gTIPQ\I%] jwiIt뙞keE? "W";jUIa(H>猇qBڷ634Mnz`YTU,Ci6f^=N\gz`b>Jf&be%e(T(,%nJU/υ.PN>47 ef]`O9;YNi(b 쩐G@d LsrJo[s>ʮϕDܸb B%X \Ma[Nl2bb8wN0:P~g'=MWVtaI_?fwl, v&OJ|1H) wޅm;pt?/O4V~:H!-'#66tBaX"pV +GUCԷb=iF8. r2#{ [o򕯄al6/k/vQx"]w6d^̇Fa*W oWY!S`ud}0K)0\UZ-JOА{L +(<[(* ?5M& #["c>5(;eE p!Oг`KŧT[ItmjQWz@9Q9KBjTM{ x{{o{\+B ؼ|Fc!_(T-K!Q@U29fZ͘ⵚV>q;5"/D,^ِj<@uct aJOV+ >╋ +_xw-g*rl\kkzEމMa03uQ'LCo̔Xd^#.n:}<5Ykjrchh|Ħ_ *pe,e1w3=_ $b11;3*ƚc2pjCI`Y(ŝ5 L "8RH]$"PlA0k:}y2]!:ccb,Y4[jCe7>{-oiIgT% .2.'\œpĒpj>]߳K4}@>G$ta T=*5!*%D/tNR! wzpn9yJmvEh.p 3,ԙB M  7^3N &^PjON.χaRY]]؀^1777ܹԁ'/^"Q%gb"]!JP0`찬ʳ룣Pl05;8Ҍezd l0TIc W& X׻z1ϝsi{^$?dwrr9e<9C(58RYS><;a!P"T=tYW~+y333Od4saC9fEBaii qidRxŜLw7e~ak@q(1pNLerSBEƆԒ#u1G':՗#N/AJ%TQ~jJy-ҿ Fx|Gx/uI'iJCHO+7j0N)NPR|fsS.B grq\mub:0YD*)QمES-iꮛpRy7̚ u7Od &I:YPD%ee'M 9.Ҝ) ah/UP._ʓO>"6 I 0È(|³ȳI9<Ӟ8p`qZLZ)U~J"# nNK0r\j"/n7㓒KrA q1 bj0gl&eXOa61R˳kkO?48L-M1ׯ;;Q&X)X̀ wUa0ٌ7jS ݻF#zqm:Vq ذN C}ښyY?nh#*c Ɔqtd X;Ep (04 vzȖuu$ֲ|jX^֎#&(ilj1Y֖NQxBj9L B*666.<+F!oy~~s!U8o3i寻д_CR l  Ӥow޽Լ-˟'W{ @%8+??g?yQO-ws0$w<˲c';Ӑc|]9YaDQy^ k豖ж |rx>ms8G\6y"}ZE4 'ִըhat"MS.[]]h8G.ҴB&I\ιa4WEe.9nh oE۶ht/j#1 cQQӴB4 ÙN{t*h49%7'e$Ye&-8JT* p8tG4u*ˑT"P9@\.WTL,ˆQ״k!뺓$0$ɾ-%?-2 Ce BPkVE4y^Ð9i.\D!}mۥR4\.l6 "?99wX,JJޞyĎJd2Q,1}~N5M+J\P(h60VԸi6WWGą>|yvvv(r]Dawi\Z22ZV(e9 NNNqDz|>_T"(] I0~ErVylZkaxxxqqjVVVSOxiZ”>:N>/DVP(t0Rc ]ZZr2 nKβ,GnJ))H\m1V.s-*=ސhZVRy߯iI)0_9+d0>B䲾n8B뺮4f16Lrq0$ DP(uBZV({iUt]!riZ;ι!%'8Mleu9eRDt,r9۶ èP~z*U]V777>LjZV#m;LRaHzvvvݏ|#aQćBE&eY׮]#ebL$5Lt~B\.W(nPXYY pjAu\rQi8N\.tmmۄ:Thض}zzzro&BU-=6 xnPX__'N4-/Zb6R\.GQT,Q$0Τ$+p84MOJRI,ih4...1hVFJ%9ѽah.--XEu;GGGobN:(J($ضM]=ι Z-E]>|Ȼ44MX)8̒}R^n޼YV%7(Jd6TUMzT׋"0s܍76x iKh4岮~4Mc۶B0$/vP0 c82^bH~O"sNTRls^*nݺEF_(\ץ0uP(4AM&yQ [n~pp@ @V]Tt]Fj_t<-2LӼvZ.{}?P(<䓝Nt jdދd8Ni4M[[[+a`ȶ퍍jZ.B>'ۀ4:[\NʏRwk}}="BUVXT*1Jy]~ݲ|>_TVHo---jgy& `iZt<+؄4Ympnܸ1Lhf^NtqE߾}L`": y0z}o2IU#ldbmIw3N_^(O!(&\a.$>vZ|>MIȲ,ZE7oޤo ["R\9Ŝ-r^9q;۶'G\ж\.&Wk6J91`|DLZ"vmO&\]^^r9qVWWUyd2!igY*!RdT*hD*!>e'83Lm+J4m<`EV׮]$V#EE8H q<#i-IA~u_\\xL8J8MمƤbH.Mc>'%Z?66!$&I9G`0 n{{X,v]THR̩f|mm.Қdnw8ZmX4hkZ-RL&aDi4|ׯw:jJsQl۞Nv|1VU2;e Q#4vO?d2١DJ^gNHh8꫍FZ]*uƶm?|p}}cl:Kҵk߿OB0xbHtb6!7-\.gv  fY(O?~bsNrQI?L&`0NoZ'l~%E+!y~~]U,Qo߾ s{0 CRt5M\]}@8 yVWWǙNdhF#ʬɌc.4WM$Egtv+vz~s^T;9 ۷߿O"Fv8yZ=88 =Z ]ðhMEgiBSA"S^SAضM4ɉeYbNCM7w9կH -Nsyy>1mtJ" uEdw]nK1&iPNɄ($n^T*x:uχQv]B=Bzq&gs!eYBa<K~sA0^R& d(]Ҳ,Rל Ib,z=:=h4?"(~/--I=0|^d2I󵵵zC2t EZN a>_ZZrh4u]YY)D hD=c"4!k"1DH!2'pibd$ad2!K}Ca7o\^^~7!- )D*q,)E6Llu¶m([1ȴ_>&灦uM3r9f4)cƺGMZj>0[yii|xxyB^/!grctwyy iZQdi_Z*jV,Lv˕ ۶l@.W P-E(3F[JbZ׀0frQl{y׮ E8_i}0Ѐx<,RyK6ia4t)Jm/GѵFc00 ji\8biIq `u=$%]- pE-<# )Q'\n4$ [[($eݶ(K%鍤dV{b^x<.Wc.|_Z'Aj\.\]-1K/Z-]'tzo:6---1~ܪa]m;h40vs s|Mlfhx@u^/xޙqDM,m{I@Ӵj7+˭it2J}ƾ 0MNf٬Tr]͛|>_,ðZ@m=F}\.s޾8|zh`29v@Ԍ %o%suu7Mrɘܲl,<#s*L&zVil6KVC*RneR{gy]|z~~OJV q6~(;^iʰbQ;T\iPdؑ"&aGQn>ɋNCR*VVV=s/"}[\.\\^^ ggg$Sx<^ZZ";wPP=)nnF]%tF1Nzz#BA@ZR)ONN?T9'yan?N?O ||8{M`tZ' ق`шP@ rs2eZsh<zqh4^eYggg~_VFݾy&cփ(‰1떴^{Bdy=zdYm3Hu}4M$vJlY[o%4yq=<#/1276669^v׃NNNKHez4~/T4jZT(^FWjU"w:1La .GEzvBzPooc֖ȣB! Xp84z](uaZuqS[qwӫhZCșe 4U!=Xz\u]iTjZdN~mr^MRGzSIFVk4SOȶms@&mootd2N6!oEF%R^qpp@eR1qyyiEO}~|<h#apqqA.]2uD*Qa0LSMvwwOOO>ݻwTӴuvvvd HZ<:h=Ȭ. aQ͛\n<6 BrZwyyI * rsjJ|>G4q lll :H @X|7C"%4RDDr~꺾cCL'G.Y$u9aKK'.* C %S4i l  2Z zZn>j- ( rooƍt>=Sr\sYHÃ"Pe^wzzj&9ZQJ} *ߗ3E6RG%$jxD싂GFmۚm˔ "RWɑ5~"J߿,JN)&cn:QrNCH`FV92r8jJ="gU垻]BD"AܿhXV-΃zǐx !SM 8$ wsMJYu]E1i )Aå/ް(zS<ϻښeu|B*JdWVstz.G"KSA}۞ ~.rZmuu$-9AK]lj!T#4xN]J ,zݲ|+$qB $Dc7"6f#LҝtJOžY_T}޽{DCQ}[߂%&IR>&HU-M|(ڪHNOӗ^ziwwk_ZE$nu/\4}o/9ENևe?Ԓ>fk]/ʃMFUu_Yxh_[9ZݎſB2o/ @E3q~zigc(} Ȣ+5;w| _㔫( ÂC!K(x;/&n?@Ŏ{e.utz|K5Uj_rE"p f‘QhWס489Hd\D  ̢^m~ef$zbH,Z>ƴ(bQiߡP\NJie^ah*ϑV([}o0ܸqIٶ,k<Oӫ&}8J9= 9 ꝙiNȓda\׉"tb/&/sdDbi~ED1F9K>YMKE:0-dww2fEEY̱gD;P֕K䢒A#vmm@7IȲM,t_?>H $mY}8ք!%3$3g~poewͲ =KD܃SxZ/Z"[ nooᶅoq*qށ9,Ya}~O)-`4z0! gabPj).58 $5fYrF鋴_G:cLHyMH{Xay>~NlY#'$/AcR'm" gS|TYMJk=fݲ^7?E<|Yba^` ZWM 7ֶU 歧S<~p#QUP(Pt@DŽ&Bif؎ed@@[O,ŎpVU#c~{NI#zo߾Ym6NZMZͬMZ?AHB5Yqg`D&^fZkρq XMңL 2sJ?3[f0coM int8ׯ_i !+h5E+.40Nّ)Zh_<8NouepIZ₱n1~vZZya$RueZe\z//T,=瞷,c8Ͳ, 7X.Bo7M pTRjd2MKyu}}YwZq^%sEf,z?(q* endstream endobj 286 0 obj << /Type /Annot /Subtype /Link /A 287 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 184.3087 147.7500 296.8087 ] >> endobj 287 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure3final.tif) >> endobj 288 0 obj << /Type /Annot /Subtype /Link /A 289 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 46.4573 258.1732 56.3779 ] >> endobj 289 0 obj << /Type /Action /S /URI /URI (https://cibsr.stanford.edu/tools/ArtRepair/ArtRepair.htm) >> endobj 290 0 obj << /Type /Annot /Subtype /Link /A 291 0 R /Border [0 0 0] /H /I /Rect [ 356.2485 46.4573 535.6290 56.3779 ] >> endobj 291 0 obj << /Type /Action /S /URI /URI (https://sourceforge.net/apps/trac/spmtools/) >> endobj 292 0 obj << /Type /Annot /Subtype /Link /A 293 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 623.4405 147.7500 735.9405 ] >> endobj 293 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure1final.tif) >> endobj 294 0 obj << /Type /Annot /Subtype /Link /A 295 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 409.8270 147.7500 522.3270 ] >> endobj 295 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/test.png) >> endobj 296 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 150 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream x1 aK&> 2K:%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%j _9R endstream endobj 297 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /SMask 296 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 150 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 21275>> stream xydy'w}Ve=͞!9$3+QҒVK[jE,/axa$a 6lXZz!%:CDgLzʬ;?xG4 _/⋈Ǣ((19_~y0T?ӟ!X p(F^:>&*sjyn65鄢W.d  `ܪL(~ew0l uۍOQ9F ²Ɔ/^y_ &1 Q#@!0?r9qh{)?c^~VG\/1u~A???>r@G ~2 rc=7 8@%^`ccKX2^ܑM\C_!0 <#q[!R@U["` ؀ |!XE^.q\iSO=%#\aq%<G`=%vۍ./}@ #ÞBnhD^+ՑV.[" Z  @SI@4|ow2!b9ht 'fr^"WE{SX!Pvjޒ5.//}t:;Mk6"l]ɧ>ǂ+ .0MU*hD F"ҁ<`}>pc-b4B!ٝ;w;7+VYhw!WXS| Ѕ8UN Z)P{*H\ps*&Sр`;ez|.;/xS^ &“p̜!ХPg6]]?qVś1X'b-fшC"2j> S8PRIv֭&·+wL^Z,SFojtV5"q677+ PaT.c1T5l”.. ;SfpX@o0qCMPLVԛ6 p-m)Fva(g<"[N <n6#5993?WM>\b'?I/k!+`J Ύ_xRp ,%1  v<F@dva a3?  3oKeK]0MC= ^P^G RK]ggٴ|M  Si$ZC@H!C"V*~+ls~>>>.e֭F:ظ(Jtu\ %7J0oxpp8;xJ+1`n7BW{Omlfa@L7+u+̃#֡p⏟ƛ}Q>EfNrW䴇pvghzEwΎ>ϜLt7`3U\ 2coM@O}I(u( 54b?%)҅r7nJb nS`6ϯAt>B*v NNבֿYqĊRzdz۶WWWu]?#?RToS'8S)9k 4~|e,^\NhhWt蝎?}uf<3@e h@[̔Is4qxXX}6uǗEn-C۷ol'#)~'.KHWvZn cF Uȴm1%OO48"UQ!Il^yF#u0 - ci2aepKTEJ=QBI=4ƥ;؀W5BJ29+_eY7nMIݵEFQ~gBOBڹK3U4Oi0ޜK_ap$t9.qR0;]!@<'ѫ t S!Y&$bGdW4V +c[(yS!1 Jivxxd`yRB ?M [ q(^Bq!@ŷ߃oHt%F-:Tri}E߱8K̴?zVjjڿw-!b-GXd,>%"%OSu 9`颓;\ c QA/nEH@ŀ@,7"y^5Bw_T^i/t-%­_S<v{7hϐTKT `]+6@II>(cy{9I2)\ w=}OMX予#,9RA >P'2 W F{tT&Q-,Hk=Slf/Qww"3 8X@YO30TKA5*v}xxw3ĮURk]3:#`踑)O@(3E, $`Q[/8ȟ@CKYW>rl`>?e U 7 V!>!(s/66FBq1 c^@LAHgyf:W.9tAQ8P_,m1i*Lkwy1^*d- RҿB!U.l9Ih&N ~q_y`y5~y33Kai flSoAԻ6/ e+_PG(](q-VW~TcDWf6T( >=N=r&56sG/&CMh4::: @.+++@ 1e;\%g?xQ gp\U#TbլDxNQꈍdžBlq uXŮ_'+[D};aȕjiw䩙}U"}f33aB1'[oQ)c 8>*I"8=bn߸ AlfApv!ZhQ,r0>MŌ}?OgR={i@VM 5RTбJB и"$Ji|bK;M] D,-iH/wk 6C$&L,WYPdev~n s& xH]ݺu֭[ S%{U")z]vM-SUGphA,IJn>'!="wFOY]͛pdD m) 꾙\^O7^aY./C4*#07w1Il6siCUÿxS )gAM.K 銚(b8=jڒ=ѿhKaXA6e"2:yL./-劀³Gʉ һ]]ȨWHy#~ާDkӎ|^ TJzS:O$1' PKߒ 5OP*q%("DGxh%uٟf}Ռq~t!M6+J"AHּAb1M} ˅Wx;wjJx%#)/}K߽{m ҁ Or3vrB0-1cN*EYKnj{CH P%Ģ(h9giDٔbTNE qI'!H~qqё?]$%$ $ `_BYlT^gV-61^]YtXn[ W8ç(9v"N6@;@h36T^0}cu0~ @G9^  ,^OVss"U1oy. yוLE4y3tҬA^"&D fʳSPlh :qODyMR>,KӤ`uz?REΰtezQ*r*R'ӴFƨV80I0? Pnx`1zUUM%ɀ6ouUSɇsOoIS$`s)+[(bC"Z9Q,􅮋ZM;;K2{a.gVM7r$td̶\a6peMF.' w||ٜh%PNzUbBynB&z]k4ȹ+a C$2W0gz0+L%6Pu zdmz(X*Sc0SsE؜&RGBO9 cR+L<ΨV梣Лͪr`3`)L3PL0u5Q7,qxBuQ>M]k,^ء{"k[%y"D>bmZ,ߏz=ol?-Tty]tJ[F#u0Yd s S<{)zg$uz\RI:3)5T"9#uya%(Y`\4@5q:) :HYNkfC,0Xg>@=rLgwu|,m25yGr "IV}!|W^y _‹/oH9Z :xX``:]qm"|B1 `%Uۏ >0h ]B%DrwvwfY07o޼{:dM&c;+̺OY}JW=_r%蕁.{GLxJXr ~~Y|2{}s3i?g C,&!Ue̲TDe0M1Ɣ?.gTIPQ\I%] jwiIt뙞keE? "W";jUIa(H>猇qBڷ634Mnz`YTU,Ci6f^=N\gz`b>Jf&be%e(T(,%nJU/υ.PN>47 ef]`O9;YNi(b 쩐G@d LsrJo[s>ʮϕDܸb B%X \Ma[Nl2bb8wN0:P~g'=MWVtaI_?fwl, v&OJ|1H) wޅm;pt?/O4V~:H!-'#66tBaX"pV +GUCԷb=iF8. r2#{ [o򕯄al6/k/vQx"]w6d^̇Fa*W oWY!S`ud}0K)0\UZ-JOА{L +(<[(* ?5M& #["c>5(;eE p!Oг`KŧT[ItmjQWz@9Q9KBjTM{ x{{o{\+B ؼ|Fc!_(T-K!Q@U29fZ͘ⵚV>q;5"/D,^ِj<@uct aJOV+ >╋ +_xw-g*rl\kkzEމMa03uQ'LCo̔Xd^#.n:}<5Ykjrchh|Ħ_ *pe,e1w3=_ $b11;3*ƚc2pjCI`Y(ŝ5 L "8RH]$"PlA0k:}y2]!:ccb,Y4[jCe7>{-oiIgT% .2.'\œpĒpj>]߳K4}@>G$ta T=*5!*%D/tNR! wzpn9yJmvEh.p 3,ԙB M  7^3N &^PjON.χaRY]]؀^1777ܹԁ'/^"Q%gb"]!JP0`찬ʳ룣Pl05;8Ҍezd l0TIc W& X׻z1ϝsi{^$?dwrr9e<9C(58RYS><;a!P"T=tYW~+y333Od4saC9fEBaii qidRxŜLw7e~ak@q(1pNLerSBEƆԒ#u1G':՗#N/AJ%TQ~jJy-ҿ Fx|Gx/uI'iJCHO+7j0N)NPR|fsS.B grq\mub:0YD*)QمES-iꮛpRy7̚ u7Od &I:YPD%ee'M 9.Ҝ) ah/UP._ʓO>"6 I 0È(|³ȳI9<Ӟ8p`qZLZ)U~J"# nNK0r\j"/n7㓒KrA q1 bj0gl&eXOa61R˳kkO?48L-M1ׯ;;Q&X)X̀ wUa0ٌ7jS ݻF#zqm:Vq ذN C}ښyY?nh#*c Ɔqtd X;Ep (04 vzȖuu$ֲ|jX^֎#&(ilj1Y֖NQxBj9L B*666.<+F!oy~~s!U8o3i寻д_CR l  Ӥow޽Լ-˟'W{ @%8+??g?yQO-ws0$w<˲c';Ӑc|]9YaDQy^ k豖ж |rx>ms8G\6y"}ZE4 'ִըhat"MS.[]]h8G.ҴB&I\ιa4WEe.9nh oE۶ht/j#1 cQQӴB4 ÙN{t*h49%7'e$Ye&-8JT* p8tG4u*ˑT"P9@\.WTL,ˆQ״k!뺓$0$ɾ-%?-2 Ce BPkVE4y^Ð9i.\D!}mۥR4\.l6 "?99wX,JJޞyĎJd2Q,1}~N5M+J\P(h60VԸi6WWGą>|yvvv(r]Dawi\Z22ZV(e9 NNNqDz|>_T"(] I0~ErVylZkaxxxqqjVVVSOxiZ”>:N>/DVP(t0Rc ]ZZr2 nKβ,GnJ))H\m1V.s-*=ސhZVRy߯iI)0_9+d0>B䲾n8B뺮4f16Lrq0$ DP(uBZV({iUt]!riZ;ι!%'8Mleu9eRDt,r9۶ èP~z*U]V777>LjZV#m;LRaHzvvvݏ|#aQćBE&eY׮]#ebL$5Lt~B\.W(nPXYY pjAu\rQi8N\.tmmۄ:Thض}zzzro&BU-=6 xnPX__'N4-/Zb6R\.GQT,Q$0Τ$+p84MOJRI,ih4...1hVFJ%9ѽah.--XEu;GGGobN:(J($ضM]=ι Z-E]>|Ȼ44MX)8̒}R^n޼YV%7(Jd6TUMzT׋"0s܍76x iKh4岮~4Mc۶B0$/vP0 c82^bH~O"sNTRls^*nݺEF_(\ץ0uP(4AM&yQ [n~pp@ @V]Tt]Fj_t<-2LӼvZ.{}?P(<䓝Nt jdދd8Ni4M[[[+a`ȶ퍍jZ.B>'ۀ4:[\NʏRwk}}="BUVXT*1Jy]~ݲ|>_TVHo---jgy& `iZt<+؄4Ympnܸ1Lhf^NtqE߾}L`": y0z}o2IU#ldbmIw3N_^(O!(&\a.$>vZ|>MIȲ,ZE7oޤo ["R\9Ŝ-r^9q;۶'G\ж\.&Wk6J91`|DLZ"vmO&\]^^r9qVWWUyd2!igY*!RdT*hD*!>e'83Lm+J4m<`EV׮]$V#EE8H q<#i-IA~u_\\xL8J8MمƤbH.Mc>'%Z?66!$&I9G`0 n{{X,v]THR̩f|mm.Қdnw8ZmX4hkZ-RL&aDi4|ׯw:jJsQl۞Nv|1VU2;e Q#4vO?d2١DJ^gNHh8꫍FZ]*uƶm?|p}}cl:Kҵk߿OB0xbHtb6!7-\.gv  fY(O?~bsNrQI?L&`0NoZ'l~%E+!y~~]U,Qo߾ s{0 CRt5M\]}@8 yVWWǙNdhF#ʬɌc.4WM$Egtv+vz~s^T;9 ۷߿O"Fv8yZ=88 =Z ]ðhMEgiBSA"S^SAضM4ɉeYbNCM7w9կH -Nsyy>1mtJ" uEdw]nK1&iPNɄ($n^T*x:uχQv]B=Bzq&gs!eYBa<K~sA0^R& d(]Ҳ,Rל Ib,z=:=h4?"(~/--I=0|^d2I󵵵zC2t EZN a>_ZZrh4u]YY)D hD=c"4!k"1DH!2'pibd$ad2!K}Ca7o\^^~7!- )D*q,)E6Llu¶m([1ȴ_>&灦uM3r9f4)cƺGMZj>0[yii|xxyB^/!grctwyy iZQdi_Z*jV,Lv˕ ۶l@.W P-E(3F[JbZ׀0frQl{y׮ E8_i}0Ѐx<,RyK6ia4t)Jm/GѵFc00 ji\8biIq `u=$%]- pE-<# )Q'\n4$ [[($eݶ(K%鍤dV{b^x<.Wc.|_Z'Aj\.\]-1K/Z-]'tzo:6---1~ܪa]m;h40vs s|Mlfhx@u^/xޙqDM,m{I@Ӵj7+˭it2J}ƾ 0MNf٬Tr]͛|>_,ðZ@m=F}\.s޾8|zh`29v@Ԍ %o%suu7Mrɘܲl,<#s*L&zVil6KVC*RneR{gy]|z~~OJV q6~(;^iʰbQ;T\iPdؑ"&aGQn>ɋNCR*VVV=s/"}[\.\\^^ ggg$Sx<^ZZ";wPP=)nnF]%tF1Nzz#BA@ZR)ONN?T9'yan?N?O ||8{M`tZ' ق`шP@ rs2eZsh<zqh4^eYggg~_VFݾy&cփ(‰1떴^{Bdy=zdYm3Hu}4M$vJlY[o%4yq=<#/1276669^v׃NNNKHez4~/T4jZT(^FWjU"w:1La .GEzvBzPooc֖ȣB! Xp84z](uaZuqS[qwӫhZCșe 4U!=Xz\u]iTjZdN~mr^MRGzSIFVk4SOȶms@&mootd2N6!oEF%R^qpp@eR1qyyiEO}~|<h#apqqA.]2uD*Qa0LSMvwwOOO>ݻwTӴuvvvd HZ<:h=Ȭ. aQ͛\n<6 BrZwyyI * rsjJ|>G4q lll :H @X|7C"%4RDDr~꺾cCL'G.Y$u9aKK'.* C %S4i l  2Z zZn>j- ( rooƍt>=Sr\sYHÃ"Pe^wzzj&9ZQJ} *ߗ3E6RG%$jxD싂GFmۚm˔ "RWɑ5~"J߿,JN)&cn:QrNCH`FV92r8jJ="gU垻]BD"AܿhXV-΃zǐx !SM 8$ wsMJYu]E1i )Aå/ް(zS<ϻښeu|B*JdWVstz.G"KSA}۞ ~.rZmuu$-9AK]lj!T#4xN]J ,zݲ|+$qB $Dc7"6f#LҝtJOžY_T}޽{DCQ}[߂%&IR>&HU-M|(ڪHNOӗ^ziwwk_ZE$nu/\4}o/9ENևe?Ԓ>fk]/ʃMFUu_Yxh_[9ZݎſB2o/ @E3q~zigc(} Ȣ+5;w| _㔫( ÂC!K(x;/&n?@Ŏ{e.utz|K5Uj_rE"p f‘QhWס489Hd\D  ̢^m~ef$zbH,Z>ƴ(bQiߡP\NJie^ah*ϑV([}o0ܸqIٶ,k<Oӫ&}8J9= 9 ꝙiNȓda\׉"tb/&/sdDbi~ED1F9K>YMKE:0-dww2fEEY̱gD;P֕K䢒A#vmm@7IȲM,t_?>H $mY}8ք!%3$3g~poewͲ =KD܃SxZ/Z"[ nooᶅoq*qށ9,Ya}~O)-`4z0! gabPj).58 $5fYrF鋴_G:cLHyMH{Xay>~NlY#'$/AcR'm" gS|TYMJk=fݲ^7?E<|Yba^` ZWM 7ֶU 歧S<~p#QUP(Pt@DŽ&Bif؎ed@@[O,ŎpVU#c~{NI#zo߾Ym6NZMZͬMZ?AHB5Yqg`D&^fZkρq XMңL 2sJ?3[f0coM int8ׯ_i !+h5E+.40Nّ)Zh_<8NouepIZ₱n1~vZZya$RueZe\z//T,=瞷,c8Ͳ, 7X.Bo7M pTRjd2MKyu}}YwZq^%sEf,z?(q* endstream endobj 298 0 obj << /Type /Annot /Subtype /Link /A 299 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 184.3087 147.7500 296.8087 ] >> endobj 299 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure3final.tif) >> endobj 300 0 obj << /Type /Annot /Subtype /Link /A 301 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 46.4573 258.1732 56.3779 ] >> endobj 301 0 obj << /Type /Action /S /URI /URI (https://cibsr.stanford.edu/tools/ArtRepair/ArtRepair.htm) >> endobj 302 0 obj << /Type /Annot /Subtype /Link /A 303 0 R /Border [0 0 0] /H /I /Rect [ 356.2485 46.4573 535.6290 56.3779 ] >> endobj 303 0 obj << /Type /Action /S /URI /URI (https://sourceforge.net/apps/trac/spmtools/) >> endobj 304 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 1 /Columns 150 /BitsPerComponent 8>> /ColorSpace /DeviceGray /BitsPerComponent 8 /Length 162>> stream x1 aK&> 2K:%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%jZ%j _9R endstream endobj 305 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /SMask 304 0 R /Filter /FlateDecode /DecodeParms << /Predictor 15 /Colors 3 /Columns 150 /BitsPerComponent 8>> /ColorSpace /DeviceRGB /BitsPerComponent 8 /Length 21275>> stream xydy'w}Ve=͞!9$3+QҒVK[jE,/axa$a 6lXZz!%:CDgLzʬ;?xG4 _/⋈Ǣ((19_~y0T?ӟ!X p(F^:>&*sjyn65鄢W.d  `ܪL(~ew0l uۍOQ9F ²Ɔ/^y_ &1 Q#@!0?r9qh{)?c^~VG\/1u~A???>r@G ~2 rc=7 8@%^`ccKX2^ܑM\C_!0 <#q[!R@U["` ؀ |!XE^.q\iSO=%#\aq%<G`=%vۍ./}@ #ÞBnhD^+ՑV.[" Z  @SI@4|ow2!b9ht 'fr^"WE{SX!Pvjޒ5.//}t:;Mk6"l]ɧ>ǂ+ .0MU*hD F"ҁ<`}>pc-b4B!ٝ;w;7+VYhw!WXS| Ѕ8UN Z)P{*H\ps*&Sр`;ez|.;/xS^ &“p̜!ХPg6]]?qVś1X'b-fшC"2j> S8PRIv֭&·+wL^Z,SFojtV5"q677+ PaT.c1T5l”.. ;SfpX@o0qCMPLVԛ6 p-m)Fva(g<"[N <n6#5993?WM>\b'?I/k!+`J Ύ_xRp ,%1  v<F@dva a3?  3oKeK]0MC= ^P^G RK]ggٴ|M  Si$ZC@H!C"V*~+ls~>>>.e֭F:ظ(Jtu\ %7J0oxpp8;xJ+1`n7BW{Omlfa@L7+u+̃#֡p⏟ƛ}Q>EfNrW䴇pvghzEwΎ>ϜLt7`3U\ 2coM@O}I(u( 54b?%)҅r7nJb nS`6ϯAt>B*v NNבֿYqĊRzdz۶WWWu]?#?RToS'8S)9k 4~|e,^\NhhWt蝎?}uf<3@e h@[̔Is4qxXX}6uǗEn-C۷ol'#)~'.KHWvZn cF Uȴm1%OO48"UQ!Il^yF#u0 - ci2aepKTEJ=QBI=4ƥ;؀W5BJ29+_eY7nMIݵEFQ~gBOBڹK3U4Oi0ޜK_ap$t9.qR0;]!@<'ѫ t S!Y&$bGdW4V +c[(yS!1 Jivxxd`yRB ?M [ q(^Bq!@ŷ߃oHt%F-:Tri}E߱8K̴?zVjjڿw-!b-GXd,>%"%OSu 9`颓;\ c QA/nEH@ŀ@,7"y^5Bw_T^i/t-%­_S<v{7hϐTKT `]+6@II>(cy{9I2)\ w=}OMX予#,9RA >P'2 W F{tT&Q-,Hk=Slf/Qww"3 8X@YO30TKA5*v}xxw3ĮURk]3:#`踑)O@(3E, $`Q[/8ȟ@CKYW>rl`>?e U 7 V!>!(s/66FBq1 c^@LAHgyf:W.9tAQ8P_,m1i*Lkwy1^*d- RҿB!U.l9Ih&N ~q_y`y5~y33Kai flSoAԻ6/ e+_PG(](q-VW~TcDWf6T( >=N=r&56sG/&CMh4::: @.+++@ 1e;\%g?xQ gp\U#TbլDxNQꈍdžBlq uXŮ_'+[D};aȕjiw䩙}U"}f33aB1'[oQ)c 8>*I"8=bn߸ AlfApv!ZhQ,r0>MŌ}?OgR={i@VM 5RTбJB и"$Ji|bK;M] D,-iH/wk 6C$&L,WYPdev~n s& xH]ݺu֭[ S%{U")z]vM-SUGphA,IJn>'!="wFOY]͛pdD m) 꾙\^O7^aY./C4*#07w1Il6siCUÿxS )gAM.K 銚(b8=jڒ=ѿhKaXA6e"2:yL./-劀³Gʉ һ]]ȨWHy#~ާDkӎ|^ TJzS:O$1' PKߒ 5OP*q%("DGxh%uٟf}Ռq~t!M6+J"AHּAb1M} ˅Wx;wjJx%#)/}K߽{m ҁ Or3vrB0-1cN*EYKnj{CH P%Ģ(h9giDٔbTNE qI'!H~qqё?]$%$ $ `_BYlT^gV-61^]YtXn[ W8ç(9v"N6@;@h36T^0}cu0~ @G9^  ,^OVss"U1oy. yוLE4y3tҬA^"&D fʳSPlh :qODyMR>,KӤ`uz?REΰtezQ*r*R'ӴFƨV80I0? Pnx`1zUUM%ɀ6ouUSɇsOoIS$`s)+[(bC"Z9Q,􅮋ZM;;K2{a.gVM7r$td̶\a6peMF.' w||ٜh%PNzUbBynB&z]k4ȹ+a C$2W0gz0+L%6Pu zdmz(X*Sc0SsE؜&RGBO9 cR+L<ΨV梣Лͪr`3`)L3PL0u5Q7,qxBuQ>M]k,^ء{"k[%y"D>bmZ,ߏz=ol?-Tty]tJ[F#u0Yd s S<{)zg$uz\RI:3)5T"9#uya%(Y`\4@5q:) :HYNkfC,0Xg>@=rLgwu|,m25yGr "IV}!|W^y _‹/oH9Z :xX``:]qm"|B1 `%Uۏ >0h ]B%DrwvwfY07o޼{:dM&c;+̺OY}JW=_r%蕁.{GLxJXr ~~Y|2{}s3i?g C,&!Ue̲TDe0M1Ɣ?.gTIPQ\I%] jwiIt뙞keE? "W";jUIa(H>猇qBڷ634Mnz`YTU,Ci6f^=N\gz`b>Jf&be%e(T(,%nJU/υ.PN>47 ef]`O9;YNi(b 쩐G@d LsrJo[s>ʮϕDܸb B%X \Ma[Nl2bb8wN0:P~g'=MWVtaI_?fwl, v&OJ|1H) wޅm;pt?/O4V~:H!-'#66tBaX"pV +GUCԷb=iF8. r2#{ [o򕯄al6/k/vQx"]w6d^̇Fa*W oWY!S`ud}0K)0\UZ-JOА{L +(<[(* ?5M& #["c>5(;eE p!Oг`KŧT[ItmjQWz@9Q9KBjTM{ x{{o{\+B ؼ|Fc!_(T-K!Q@U29fZ͘ⵚV>q;5"/D,^ِj<@uct aJOV+ >╋ +_xw-g*rl\kkzEމMa03uQ'LCo̔Xd^#.n:}<5Ykjrchh|Ħ_ *pe,e1w3=_ $b11;3*ƚc2pjCI`Y(ŝ5 L "8RH]$"PlA0k:}y2]!:ccb,Y4[jCe7>{-oiIgT% .2.'\œpĒpj>]߳K4}@>G$ta T=*5!*%D/tNR! wzpn9yJmvEh.p 3,ԙB M  7^3N &^PjON.χaRY]]؀^1777ܹԁ'/^"Q%gb"]!JP0`찬ʳ룣Pl05;8Ҍezd l0TIc W& X׻z1ϝsi{^$?dwrr9e<9C(58RYS><;a!P"T=tYW~+y333Od4saC9fEBaii qidRxŜLw7e~ak@q(1pNLerSBEƆԒ#u1G':՗#N/AJ%TQ~jJy-ҿ Fx|Gx/uI'iJCHO+7j0N)NPR|fsS.B grq\mub:0YD*)QمES-iꮛpRy7̚ u7Od &I:YPD%ee'M 9.Ҝ) ah/UP._ʓO>"6 I 0È(|³ȳI9<Ӟ8p`qZLZ)U~J"# nNK0r\j"/n7㓒KrA q1 bj0gl&eXOa61R˳kkO?48L-M1ׯ;;Q&X)X̀ wUa0ٌ7jS ݻF#zqm:Vq ذN C}ښyY?nh#*c Ɔqtd X;Ep (04 vzȖuu$ֲ|jX^֎#&(ilj1Y֖NQxBj9L B*666.<+F!oy~~s!U8o3i寻д_CR l  Ӥow޽Լ-˟'W{ @%8+??g?yQO-ws0$w<˲c';Ӑc|]9YaDQy^ k豖ж |rx>ms8G\6y"}ZE4 'ִըhat"MS.[]]h8G.ҴB&I\ιa4WEe.9nh oE۶ht/j#1 cQQӴB4 ÙN{t*h49%7'e$Ye&-8JT* p8tG4u*ˑT"P9@\.WTL,ˆQ״k!뺓$0$ɾ-%?-2 Ce BPkVE4y^Ð9i.\D!}mۥR4\.l6 "?99wX,JJޞyĎJd2Q,1}~N5M+J\P(h60VԸi6WWGą>|yvvv(r]Dawi\Z22ZV(e9 NNNqDz|>_T"(] I0~ErVylZkaxxxqqjVVVSOxiZ”>:N>/DVP(t0Rc ]ZZr2 nKβ,GnJ))H\m1V.s-*=ސhZVRy߯iI)0_9+d0>B䲾n8B뺮4f16Lrq0$ DP(uBZV({iUt]!riZ;ι!%'8Mleu9eRDt,r9۶ èP~z*U]V777>LjZV#m;LRaHzvvvݏ|#aQćBE&eY׮]#ebL$5Lt~B\.W(nPXYY pjAu\rQi8N\.tmmۄ:Thض}zzzro&BU-=6 xnPX__'N4-/Zb6R\.GQT,Q$0Τ$+p84MOJRI,ih4...1hVFJ%9ѽah.--XEu;GGGobN:(J($ضM]=ι Z-E]>|Ȼ44MX)8̒}R^n޼YV%7(Jd6TUMzT׋"0s܍76x iKh4岮~4Mc۶B0$/vP0 c82^bH~O"sNTRls^*nݺEF_(\ץ0uP(4AM&yQ [n~pp@ @V]Tt]Fj_t<-2LӼvZ.{}?P(<䓝Nt jdދd8Ni4M[[[+a`ȶ퍍jZ.B>'ۀ4:[\NʏRwk}}="BUVXT*1Jy]~ݲ|>_TVHo---jgy& `iZt<+؄4Ympnܸ1Lhf^NtqE߾}L`": y0z}o2IU#ldbmIw3N_^(O!(&\a.$>vZ|>MIȲ,ZE7oޤo ["R\9Ŝ-r^9q;۶'G\ж\.&Wk6J91`|DLZ"vmO&\]^^r9qVWWUyd2!igY*!RdT*hD*!>e'83Lm+J4m<`EV׮]$V#EE8H q<#i-IA~u_\\xL8J8MمƤbH.Mc>'%Z?66!$&I9G`0 n{{X,v]THR̩f|mm.Қdnw8ZmX4hkZ-RL&aDi4|ׯw:jJsQl۞Nv|1VU2;e Q#4vO?d2١DJ^gNHh8꫍FZ]*uƶm?|p}}cl:Kҵk߿OB0xbHtb6!7-\.gv  fY(O?~bsNrQI?L&`0NoZ'l~%E+!y~~]U,Qo߾ s{0 CRt5M\]}@8 yVWWǙNdhF#ʬɌc.4WM$Egtv+vz~s^T;9 ۷߿O"Fv8yZ=88 =Z ]ðhMEgiBSA"S^SAضM4ɉeYbNCM7w9կH -Nsyy>1mtJ" uEdw]nK1&iPNɄ($n^T*x:uχQv]B=Bzq&gs!eYBa<K~sA0^R& d(]Ҳ,Rל Ib,z=:=h4?"(~/--I=0|^d2I󵵵zC2t EZN a>_ZZrh4u]YY)D hD=c"4!k"1DH!2'pibd$ad2!K}Ca7o\^^~7!- )D*q,)E6Llu¶m([1ȴ_>&灦uM3r9f4)cƺGMZj>0[yii|xxyB^/!grctwyy iZQdi_Z*jV,Lv˕ ۶l@.W P-E(3F[JbZ׀0frQl{y׮ E8_i}0Ѐx<,RyK6ia4t)Jm/GѵFc00 ji\8biIq `u=$%]- pE-<# )Q'\n4$ [[($eݶ(K%鍤dV{b^x<.Wc.|_Z'Aj\.\]-1K/Z-]'tzo:6---1~ܪa]m;h40vs s|Mlfhx@u^/xޙqDM,m{I@Ӵj7+˭it2J}ƾ 0MNf٬Tr]͛|>_,ðZ@m=F}\.s޾8|zh`29v@Ԍ %o%suu7Mrɘܲl,<#s*L&zVil6KVC*RneR{gy]|z~~OJV q6~(;^iʰbQ;T\iPdؑ"&aGQn>ɋNCR*VVV=s/"}[\.\\^^ ggg$Sx<^ZZ";wPP=)nnF]%tF1Nzz#BA@ZR)ONN?T9'yan?N?O ||8{M`tZ' ق`шP@ rs2eZsh<zqh4^eYggg~_VFݾy&cփ(‰1떴^{Bdy=zdYm3Hu}4M$vJlY[o%4yq=<#/1276669^v׃NNNKHez4~/T4jZT(^FWjU"w:1La .GEzvBzPooc֖ȣB! Xp84z](uaZuqS[qwӫhZCșe 4U!=Xz\u]iTjZdN~mr^MRGzSIFVk4SOȶms@&mootd2N6!oEF%R^qpp@eR1qyyiEO}~|<h#apqqA.]2uD*Qa0LSMvwwOOO>ݻwTӴuvvvd HZ<:h=Ȭ. aQ͛\n<6 BrZwyyI * rsjJ|>G4q lll :H @X|7C"%4RDDr~꺾cCL'G.Y$u9aKK'.* C %S4i l  2Z zZn>j- ( rooƍt>=Sr\sYHÃ"Pe^wzzj&9ZQJ} *ߗ3E6RG%$jxD싂GFmۚm˔ "RWɑ5~"J߿,JN)&cn:QrNCH`FV92r8jJ="gU垻]BD"AܿhXV-΃zǐx !SM 8$ wsMJYu]E1i )Aå/ް(zS<ϻښeu|B*JdWVstz.G"KSA}۞ ~.rZmuu$-9AK]lj!T#4xN]J ,zݲ|+$qB $Dc7"6f#LҝtJOžY_T}޽{DCQ}[߂%&IR>&HU-M|(ڪHNOӗ^ziwwk_ZE$nu/\4}o/9ENևe?Ԓ>fk]/ʃMFUu_Yxh_[9ZݎſB2o/ @E3q~zigc(} Ȣ+5;w| _㔫( ÂC!K(x;/&n?@Ŏ{e.utz|K5Uj_rE"p f‘QhWס489Hd\D  ̢^m~ef$zbH,Z>ƴ(bQiߡP\NJie^ah*ϑV([}o0ܸqIٶ,k<Oӫ&}8J9= 9 ꝙiNȓda\׉"tb/&/sdDbi~ED1F9K>YMKE:0-dww2fEEY̱gD;P֕K䢒A#vmm@7IȲM,t_?>H $mY}8ք!%3$3g~poewͲ =KD܃SxZ/Z"[ nooᶅoq*qށ9,Ya}~O)-`4z0! gabPj).58 $5fYrF鋴_G:cLHyMH{Xay>~NlY#'$/AcR'm" gS|TYMJk=fݲ^7?E<|Yba^` ZWM 7ֶU 歧S<~p#QUP(Pt@DŽ&Bif؎ed@@[O,ŎpVU#c~{NI#zo߾Ym6NZMZͬMZ?AHB5Yqg`D&^fZkρq XMңL 2sJ?3[f0coM int8ׯ_i !+h5E+.40Nّ)Zh_<8NouepIZ₱n1~vZZya$RueZe\z//T,=瞷,c8Ͳ, 7X.Bo7M pTRjd2MKyu}}YwZq^%sEf,z?(q* endstream endobj 306 0 obj << /Type /Page /Parent 3 0 R /Annots [ 308 0 R 310 0 R 313 0 R 315 0 R 317 0 R 319 0 R 321 0 R 323 0 R 325 0 R ] /Contents 307 0 R >> endobj 307 0 obj << /Length 23407 >> stream 0.271 0.267 0.267 rg q 15.000 32.123 577.500 744.877 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(big efforts have been performed in the National Alliance for Medical Imaging for data cleaning \()] TJ ET 0.267 0.267 0.267 rg BT 26.250 755.571 Td /F1 9.8 Tf [(https://www.nitrc.org/projects/dtiprep/)] TJ ET 0.271 0.267 0.267 rg BT 181.762 755.571 Td /F1 9.8 Tf [(\). These tools focus on spike artifacts caused by technical equipment in the scanner room )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(or by the scanner itself, based on the assumption that each image in a series should look similar to the other images. To some )] TJ ET BT 26.250 731.762 Td /F1 9.8 Tf [(extent, these approaches can be used on DTI analysis as well but those presented here \(or e.g. by the National Alliance for )] TJ ET BT 26.250 719.857 Td /F1 9.8 Tf [(Medical Imaging\) seem more appropriate as DTI data present multiple additional challenges. Image contrast depends on )] TJ ET BT 26.250 707.952 Td /F1 9.8 Tf [(strength and direction of diffusion weighting so that, in any two images, voxels in the same anatomical location may have )] TJ ET BT 26.250 696.048 Td /F1 9.8 Tf [(completely different intensities because of local diffusion properties. Therefore, two images from the same DTI series can be )] TJ ET BT 26.250 684.143 Td /F1 9.8 Tf [(compared directly only if they are acquired using the same diffusion weighting and direction. In addition, there are motion )] TJ ET BT 26.250 672.238 Td /F1 9.8 Tf [(related signal dropouts \(Figure 1\) which usually do not occur in sequences without diffusion weighting. Given limited scanning )] TJ ET BT 26.250 660.333 Td /F1 9.8 Tf [(time, most current DWI sequences are designed to include a high number of different diffusion directions rather than fewer )] TJ ET BT 26.250 648.429 Td /F1 9.8 Tf [(directions multiple times. This has the advantage that the local diffusion tensor can be more accurately described but limits )] TJ ET BT 26.250 636.524 Td /F1 9.8 Tf [(artifact detection software based on classic similarity measures.)] TJ ET 0.965 0.965 0.965 rg 26.250 422.361 555.000 204.282 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 626.643 m 581.250 626.643 l 581.250 625.893 l 26.250 625.893 l f 26.250 422.361 m 581.250 422.361 l 581.250 423.111 l 26.250 423.111 l f q 112.500 0 0 112.500 35.250 504.393 cm /I55 Do Q q 35.250 433.611 537.000 64.782 re W n 0.271 0.267 0.267 rg BT 35.250 488.869 Td /F4 9.8 Tf [(Fig. 4: For comparison with previous studies, FA maps of pre-symptomatic and early HD cases were compared )] TJ ET BT 35.250 476.964 Td /F4 9.8 Tf [(with healthy controls.)] TJ ET BT 35.250 457.594 Td /F1 9.8 Tf [(Results are overlaid on the scanner specific template. Color bars display T-scores for each of the comparisons. HD, early )] TJ ET BT 35.250 443.858 Td /F1 9.8 Tf [(affected manifest Huntington disease patients; PM, premanifest mutation carriers; CTR, controls.)] TJ ET Q BT 26.250 405.337 Td /F1 9.8 Tf [(The effect of QC on single data sets can be estimated to be in the range of the ratio of eliminated volumes to the total number of )] TJ ET BT 26.250 393.432 Td /F1 9.8 Tf [(volumes; here in this study due to a high number of gradient directions for single subjects and a moderate number of eliminated )] TJ ET BT 26.250 381.528 Td /F1 9.8 Tf [(volumes \(Figure 3\) this effect is low \(usually FA differences < 0.1\).)] TJ ET BT 26.250 362.123 Td /F1 9.8 Tf [(Nevertheless, in order to give a rough estimation, as over 60 \(b = 1000 mm/s)] TJ ET BT 357.623 366.011 Td /F1 8.7 Tf [(2)] TJ ET BT 362.442 362.123 Td /F1 9.8 Tf [(\) directions and also more than 5 \(b = 100 mm/s)] TJ ET BT 569.717 366.011 Td /F1 8.7 Tf [(2)] TJ ET BT 574.536 362.123 Td /F1 9.8 Tf [(\) )] TJ ET BT 26.250 350.218 Td /F1 9.8 Tf [(data sets were recorded, the exclusion of less than e.g. 10 data sets \(which is the case for most data sets, Figure 3\) generally )] TJ ET BT 26.250 338.313 Td /F1 9.8 Tf [(could lead to changes in single FA-maps of about 10-20 %, as the process of Eigenvector/Eigenvalue calculation and )] TJ ET BT 26.250 326.409 Td /F1 9.8 Tf [(subsequent FA calculation follows the rules of a linear process. Therefore, the changes in FA values \(without and with QC\) )] TJ ET BT 26.250 314.504 Td /F1 9.8 Tf [(cannot be expected too high for single data sets. Subsequent group comparison \(group strength about 20\) equalizes the )] TJ ET BT 26.250 302.599 Td /F1 9.8 Tf [(remaining outliers.)] TJ ET BT 26.250 283.194 Td /F1 9.8 Tf [(Therefore a high number of gradient recordings helps to improve the quality of the results. If the ratio between eliminated )] TJ ET BT 26.250 271.290 Td /F1 9.8 Tf [(volumes to the total number of volumes is high, QC could act as a tool to improve the quality of single subject results and )] TJ ET BT 26.250 259.385 Td /F1 9.8 Tf [(consequently also improve the results at the group level. Thus, beside signal accumulation, increasing the number of gradients )] TJ ET BT 26.250 247.480 Td /F1 9.8 Tf [(and further possibilities, QC is an additional tool to increase the signal-to-noise ratio in DTI data analysis in order to improve the )] TJ ET BT 26.250 235.575 Td /F1 9.8 Tf [(quality of the results in group comparison.)] TJ ET BT 26.250 216.171 Td /F1 9.8 Tf [(We present a novel approach for the QC of DWI data by use of both 1.5 and 3T data as the currently used standard field )] TJ ET BT 26.250 204.266 Td /F1 9.8 Tf [(strengths in MRI studies of HD. This QC detection method is suitable for the current DWI sequences that employ a high number )] TJ ET BT 26.250 192.361 Td /F1 9.8 Tf [(of unique directions rather than multiple times scanning fewer directions. The results of the data analyses support the current )] TJ ET BT 26.250 180.456 Td /F1 9.8 Tf [(literature of DTI applications to HD )] TJ ET 0.267 0.267 0.267 rg BT 177.970 180.456 Td /F1 9.8 Tf [([16])] TJ ET 0.271 0.267 0.267 rg BT 194.233 180.456 Td /F1 9.8 Tf [(, i.e. both significance levels and the regional distribution of HD-associated FA alterations )] TJ ET BT 26.250 168.552 Td /F1 9.8 Tf [(were in accordance with those previous studies.)] TJ ET BT 26.250 149.147 Td /F1 9.8 Tf [(As an additional indicator of plausibility of the results, more volumes were excluded as the disease progressed, i.e. more data )] TJ ET BT 26.250 137.242 Td /F1 9.8 Tf [(were excluded for HD in comparison with controls. This is not unexpected for neurodegenerative movement disorders, but other )] TJ ET BT 26.250 125.337 Td /F1 9.8 Tf [(factors such as increased anxiety may also have contributed to this effect. The threshold effectively controls the trade-off )] TJ ET BT 26.250 113.433 Td /F1 9.8 Tf [(between an unnecessary loss of data by being too conservative and including too much noise. The cut-off chosen in the current )] TJ ET BT 26.250 101.528 Td /F1 9.8 Tf [(study was selected through visual inspection of the images. Although this seems to be somewhat arbitrary, it has to be held that )] TJ ET BT 26.250 89.623 Td /F1 9.8 Tf [(when varying this threshold between 0.2 and 0.3 as detailed in the methods section, almost the identical slices were detected.)] TJ ET BT 26.250 70.218 Td /F1 9.8 Tf [(Several extensions and alternatives to the current implementation are possible, starting at the level of the preprocessing. We )] TJ ET BT 26.250 58.314 Td /F1 9.8 Tf [(refrained from performing a rigid body registration of the DWI data. Registration is difficult for images with high b value and )] TJ ET BT 26.250 46.409 Td /F1 9.8 Tf [(differing gradient directions. The interspersed images with low b value could be used but require strong assumptions regarding )] TJ ET Q q 15.000 32.123 577.500 744.877 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(big efforts have been performed in the National Alliance for Medical Imaging for data cleaning \()] TJ ET 0.267 0.267 0.267 rg BT 26.250 755.571 Td /F1 9.8 Tf [(https://www.nitrc.org/projects/dtiprep/)] TJ ET 0.271 0.267 0.267 rg BT 181.762 755.571 Td /F1 9.8 Tf [(\). These tools focus on spike artifacts caused by technical equipment in the scanner room )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(or by the scanner itself, based on the assumption that each image in a series should look similar to the other images. To some )] TJ ET BT 26.250 731.762 Td /F1 9.8 Tf [(extent, these approaches can be used on DTI analysis as well but those presented here \(or e.g. by the National Alliance for )] TJ ET BT 26.250 719.857 Td /F1 9.8 Tf [(Medical Imaging\) seem more appropriate as DTI data present multiple additional challenges. Image contrast depends on )] TJ ET BT 26.250 707.952 Td /F1 9.8 Tf [(strength and direction of diffusion weighting so that, in any two images, voxels in the same anatomical location may have )] TJ ET BT 26.250 696.048 Td /F1 9.8 Tf [(completely different intensities because of local diffusion properties. Therefore, two images from the same DTI series can be )] TJ ET BT 26.250 684.143 Td /F1 9.8 Tf [(compared directly only if they are acquired using the same diffusion weighting and direction. In addition, there are motion )] TJ ET BT 26.250 672.238 Td /F1 9.8 Tf [(related signal dropouts \(Figure 1\) which usually do not occur in sequences without diffusion weighting. Given limited scanning )] TJ ET BT 26.250 660.333 Td /F1 9.8 Tf [(time, most current DWI sequences are designed to include a high number of different diffusion directions rather than fewer )] TJ ET BT 26.250 648.429 Td /F1 9.8 Tf [(directions multiple times. This has the advantage that the local diffusion tensor can be more accurately described but limits )] TJ ET BT 26.250 636.524 Td /F1 9.8 Tf [(artifact detection software based on classic similarity measures.)] TJ ET 0.965 0.965 0.965 rg 26.250 422.361 555.000 204.282 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 626.643 m 581.250 626.643 l 581.250 625.893 l 26.250 625.893 l f 26.250 422.361 m 581.250 422.361 l 581.250 423.111 l 26.250 423.111 l f q 112.500 0 0 112.500 35.250 504.393 cm /I55 Do Q q 35.250 433.611 537.000 64.782 re W n 0.271 0.267 0.267 rg BT 35.250 488.869 Td /F4 9.8 Tf [(Fig. 4: For comparison with previous studies, FA maps of pre-symptomatic and early HD cases were compared )] TJ ET BT 35.250 476.964 Td /F4 9.8 Tf [(with healthy controls.)] TJ ET BT 35.250 457.594 Td /F1 9.8 Tf [(Results are overlaid on the scanner specific template. Color bars display T-scores for each of the comparisons. HD, early )] TJ ET BT 35.250 443.858 Td /F1 9.8 Tf [(affected manifest Huntington disease patients; PM, premanifest mutation carriers; CTR, controls.)] TJ ET Q BT 26.250 405.337 Td /F1 9.8 Tf [(The effect of QC on single data sets can be estimated to be in the range of the ratio of eliminated volumes to the total number of )] TJ ET BT 26.250 393.432 Td /F1 9.8 Tf [(volumes; here in this study due to a high number of gradient directions for single subjects and a moderate number of eliminated )] TJ ET BT 26.250 381.528 Td /F1 9.8 Tf [(volumes \(Figure 3\) this effect is low \(usually FA differences < 0.1\).)] TJ ET BT 26.250 362.123 Td /F1 9.8 Tf [(Nevertheless, in order to give a rough estimation, as over 60 \(b = 1000 mm/s)] TJ ET BT 357.623 366.011 Td /F1 8.7 Tf [(2)] TJ ET BT 362.442 362.123 Td /F1 9.8 Tf [(\) directions and also more than 5 \(b = 100 mm/s)] TJ ET BT 569.717 366.011 Td /F1 8.7 Tf [(2)] TJ ET BT 574.536 362.123 Td /F1 9.8 Tf [(\) )] TJ ET BT 26.250 350.218 Td /F1 9.8 Tf [(data sets were recorded, the exclusion of less than e.g. 10 data sets \(which is the case for most data sets, Figure 3\) generally )] TJ ET BT 26.250 338.313 Td /F1 9.8 Tf [(could lead to changes in single FA-maps of about 10-20 %, as the process of Eigenvector/Eigenvalue calculation and )] TJ ET BT 26.250 326.409 Td /F1 9.8 Tf [(subsequent FA calculation follows the rules of a linear process. Therefore, the changes in FA values \(without and with QC\) )] TJ ET BT 26.250 314.504 Td /F1 9.8 Tf [(cannot be expected too high for single data sets. Subsequent group comparison \(group strength about 20\) equalizes the )] TJ ET BT 26.250 302.599 Td /F1 9.8 Tf [(remaining outliers.)] TJ ET BT 26.250 283.194 Td /F1 9.8 Tf [(Therefore a high number of gradient recordings helps to improve the quality of the results. If the ratio between eliminated )] TJ ET BT 26.250 271.290 Td /F1 9.8 Tf [(volumes to the total number of volumes is high, QC could act as a tool to improve the quality of single subject results and )] TJ ET BT 26.250 259.385 Td /F1 9.8 Tf [(consequently also improve the results at the group level. Thus, beside signal accumulation, increasing the number of gradients )] TJ ET BT 26.250 247.480 Td /F1 9.8 Tf [(and further possibilities, QC is an additional tool to increase the signal-to-noise ratio in DTI data analysis in order to improve the )] TJ ET BT 26.250 235.575 Td /F1 9.8 Tf [(quality of the results in group comparison.)] TJ ET BT 26.250 216.171 Td /F1 9.8 Tf [(We present a novel approach for the QC of DWI data by use of both 1.5 and 3T data as the currently used standard field )] TJ ET BT 26.250 204.266 Td /F1 9.8 Tf [(strengths in MRI studies of HD. This QC detection method is suitable for the current DWI sequences that employ a high number )] TJ ET BT 26.250 192.361 Td /F1 9.8 Tf [(of unique directions rather than multiple times scanning fewer directions. The results of the data analyses support the current )] TJ ET BT 26.250 180.456 Td /F1 9.8 Tf [(literature of DTI applications to HD )] TJ ET 0.267 0.267 0.267 rg BT 177.970 180.456 Td /F1 9.8 Tf [([16])] TJ ET 0.271 0.267 0.267 rg BT 194.233 180.456 Td /F1 9.8 Tf [(, i.e. both significance levels and the regional distribution of HD-associated FA alterations )] TJ ET BT 26.250 168.552 Td /F1 9.8 Tf [(were in accordance with those previous studies.)] TJ ET BT 26.250 149.147 Td /F1 9.8 Tf [(As an additional indicator of plausibility of the results, more volumes were excluded as the disease progressed, i.e. more data )] TJ ET BT 26.250 137.242 Td /F1 9.8 Tf [(were excluded for HD in comparison with controls. This is not unexpected for neurodegenerative movement disorders, but other )] TJ ET BT 26.250 125.337 Td /F1 9.8 Tf [(factors such as increased anxiety may also have contributed to this effect. The threshold effectively controls the trade-off )] TJ ET BT 26.250 113.433 Td /F1 9.8 Tf [(between an unnecessary loss of data by being too conservative and including too much noise. The cut-off chosen in the current )] TJ ET BT 26.250 101.528 Td /F1 9.8 Tf [(study was selected through visual inspection of the images. Although this seems to be somewhat arbitrary, it has to be held that )] TJ ET BT 26.250 89.623 Td /F1 9.8 Tf [(when varying this threshold between 0.2 and 0.3 as detailed in the methods section, almost the identical slices were detected.)] TJ ET BT 26.250 70.218 Td /F1 9.8 Tf [(Several extensions and alternatives to the current implementation are possible, starting at the level of the preprocessing. We )] TJ ET BT 26.250 58.314 Td /F1 9.8 Tf [(refrained from performing a rigid body registration of the DWI data. Registration is difficult for images with high b value and )] TJ ET BT 26.250 46.409 Td /F1 9.8 Tf [(differing gradient directions. The interspersed images with low b value could be used but require strong assumptions regarding )] TJ ET Q q 15.000 32.123 577.500 744.877 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(big efforts have been performed in the National Alliance for Medical Imaging for data cleaning \()] TJ ET 0.267 0.267 0.267 rg BT 26.250 755.571 Td /F1 9.8 Tf [(https://www.nitrc.org/projects/dtiprep/)] TJ ET 0.271 0.267 0.267 rg BT 181.762 755.571 Td /F1 9.8 Tf [(\). These tools focus on spike artifacts caused by technical equipment in the scanner room )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(or by the scanner itself, based on the assumption that each image in a series should look similar to the other images. To some )] TJ ET BT 26.250 731.762 Td /F1 9.8 Tf [(extent, these approaches can be used on DTI analysis as well but those presented here \(or e.g. by the National Alliance for )] TJ ET BT 26.250 719.857 Td /F1 9.8 Tf [(Medical Imaging\) seem more appropriate as DTI data present multiple additional challenges. Image contrast depends on )] TJ ET BT 26.250 707.952 Td /F1 9.8 Tf [(strength and direction of diffusion weighting so that, in any two images, voxels in the same anatomical location may have )] TJ ET BT 26.250 696.048 Td /F1 9.8 Tf [(completely different intensities because of local diffusion properties. Therefore, two images from the same DTI series can be )] TJ ET BT 26.250 684.143 Td /F1 9.8 Tf [(compared directly only if they are acquired using the same diffusion weighting and direction. In addition, there are motion )] TJ ET BT 26.250 672.238 Td /F1 9.8 Tf [(related signal dropouts \(Figure 1\) which usually do not occur in sequences without diffusion weighting. Given limited scanning )] TJ ET BT 26.250 660.333 Td /F1 9.8 Tf [(time, most current DWI sequences are designed to include a high number of different diffusion directions rather than fewer )] TJ ET BT 26.250 648.429 Td /F1 9.8 Tf [(directions multiple times. This has the advantage that the local diffusion tensor can be more accurately described but limits )] TJ ET BT 26.250 636.524 Td /F1 9.8 Tf [(artifact detection software based on classic similarity measures.)] TJ ET 0.965 0.965 0.965 rg 26.250 422.361 555.000 204.282 re f 0.267 0.267 0.267 rg 0.267 0.267 0.267 RG 26.250 626.643 m 581.250 626.643 l 581.250 625.893 l 26.250 625.893 l f 26.250 422.361 m 581.250 422.361 l 581.250 423.111 l 26.250 423.111 l f q 112.500 0 0 112.500 35.250 504.393 cm /I55 Do Q q 35.250 433.611 537.000 64.782 re W n 0.271 0.267 0.267 rg BT 35.250 488.869 Td /F4 9.8 Tf [(Fig. 4: For comparison with previous studies, FA maps of pre-symptomatic and early HD cases were compared )] TJ ET BT 35.250 476.964 Td /F4 9.8 Tf [(with healthy controls.)] TJ ET BT 35.250 457.594 Td /F1 9.8 Tf [(Results are overlaid on the scanner specific template. Color bars display T-scores for each of the comparisons. HD, early )] TJ ET BT 35.250 443.858 Td /F1 9.8 Tf [(affected manifest Huntington disease patients; PM, premanifest mutation carriers; CTR, controls.)] TJ ET Q BT 26.250 405.337 Td /F1 9.8 Tf [(The effect of QC on single data sets can be estimated to be in the range of the ratio of eliminated volumes to the total number of )] TJ ET BT 26.250 393.432 Td /F1 9.8 Tf [(volumes; here in this study due to a high number of gradient directions for single subjects and a moderate number of eliminated )] TJ ET BT 26.250 381.528 Td /F1 9.8 Tf [(volumes \(Figure 3\) this effect is low \(usually FA differences < 0.1\).)] TJ ET BT 26.250 362.123 Td /F1 9.8 Tf [(Nevertheless, in order to give a rough estimation, as over 60 \(b = 1000 mm/s)] TJ ET BT 357.623 366.011 Td /F1 8.7 Tf [(2)] TJ ET BT 362.442 362.123 Td /F1 9.8 Tf [(\) directions and also more than 5 \(b = 100 mm/s)] TJ ET BT 569.717 366.011 Td /F1 8.7 Tf [(2)] TJ ET BT 574.536 362.123 Td /F1 9.8 Tf [(\) )] TJ ET BT 26.250 350.218 Td /F1 9.8 Tf [(data sets were recorded, the exclusion of less than e.g. 10 data sets \(which is the case for most data sets, Figure 3\) generally )] TJ ET BT 26.250 338.313 Td /F1 9.8 Tf [(could lead to changes in single FA-maps of about 10-20 %, as the process of Eigenvector/Eigenvalue calculation and )] TJ ET BT 26.250 326.409 Td /F1 9.8 Tf [(subsequent FA calculation follows the rules of a linear process. Therefore, the changes in FA values \(without and with QC\) )] TJ ET BT 26.250 314.504 Td /F1 9.8 Tf [(cannot be expected too high for single data sets. Subsequent group comparison \(group strength about 20\) equalizes the )] TJ ET BT 26.250 302.599 Td /F1 9.8 Tf [(remaining outliers.)] TJ ET BT 26.250 283.194 Td /F1 9.8 Tf [(Therefore a high number of gradient recordings helps to improve the quality of the results. If the ratio between eliminated )] TJ ET BT 26.250 271.290 Td /F1 9.8 Tf [(volumes to the total number of volumes is high, QC could act as a tool to improve the quality of single subject results and )] TJ ET BT 26.250 259.385 Td /F1 9.8 Tf [(consequently also improve the results at the group level. Thus, beside signal accumulation, increasing the number of gradients )] TJ ET BT 26.250 247.480 Td /F1 9.8 Tf [(and further possibilities, QC is an additional tool to increase the signal-to-noise ratio in DTI data analysis in order to improve the )] TJ ET BT 26.250 235.575 Td /F1 9.8 Tf [(quality of the results in group comparison.)] TJ ET BT 26.250 216.171 Td /F1 9.8 Tf [(We present a novel approach for the QC of DWI data by use of both 1.5 and 3T data as the currently used standard field )] TJ ET BT 26.250 204.266 Td /F1 9.8 Tf [(strengths in MRI studies of HD. This QC detection method is suitable for the current DWI sequences that employ a high number )] TJ ET BT 26.250 192.361 Td /F1 9.8 Tf [(of unique directions rather than multiple times scanning fewer directions. The results of the data analyses support the current )] TJ ET BT 26.250 180.456 Td /F1 9.8 Tf [(literature of DTI applications to HD )] TJ ET 0.267 0.267 0.267 rg BT 177.970 180.456 Td /F1 9.8 Tf [([16])] TJ ET 0.271 0.267 0.267 rg BT 194.233 180.456 Td /F1 9.8 Tf [(, i.e. both significance levels and the regional distribution of HD-associated FA alterations )] TJ ET BT 26.250 168.552 Td /F1 9.8 Tf [(were in accordance with those previous studies.)] TJ ET BT 26.250 149.147 Td /F1 9.8 Tf [(As an additional indicator of plausibility of the results, more volumes were excluded as the disease progressed, i.e. more data )] TJ ET BT 26.250 137.242 Td /F1 9.8 Tf [(were excluded for HD in comparison with controls. This is not unexpected for neurodegenerative movement disorders, but other )] TJ ET BT 26.250 125.337 Td /F1 9.8 Tf [(factors such as increased anxiety may also have contributed to this effect. The threshold effectively controls the trade-off )] TJ ET BT 26.250 113.433 Td /F1 9.8 Tf [(between an unnecessary loss of data by being too conservative and including too much noise. The cut-off chosen in the current )] TJ ET BT 26.250 101.528 Td /F1 9.8 Tf [(study was selected through visual inspection of the images. Although this seems to be somewhat arbitrary, it has to be held that )] TJ ET BT 26.250 89.623 Td /F1 9.8 Tf [(when varying this threshold between 0.2 and 0.3 as detailed in the methods section, almost the identical slices were detected.)] TJ ET BT 26.250 70.218 Td /F1 9.8 Tf [(Several extensions and alternatives to the current implementation are possible, starting at the level of the preprocessing. We )] TJ ET BT 26.250 58.314 Td /F1 9.8 Tf [(refrained from performing a rigid body registration of the DWI data. Registration is difficult for images with high b value and )] TJ ET BT 26.250 46.409 Td /F1 9.8 Tf [(differing gradient directions. The interspersed images with low b value could be used but require strong assumptions regarding )] TJ ET Q q 112.500 0 0 112.500 35.250 504.393 cm /I55 Do Q q 0.000 0.000 0.000 rg BT 291.710 19.825 Td /F1 11.0 Tf [(5)] TJ ET BT 25.000 19.825 Td /F1 11.0 Tf [(PLOS Currents Huntington Disease)] TJ ET Q endstream endobj 308 0 obj << /Type /Annot /Subtype /Link /A 309 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 754.6696 181.7625 764.5902 ] >> endobj 309 0 obj << /Type /Action /S /URI /URI (https://www.nitrc.org/projects/dtiprep/) >> endobj 310 0 obj << /Type /Annot /Subtype /Link /A 311 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 504.3930 147.7500 616.8930 ] >> endobj 311 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure4.jpg) >> endobj 312 0 obj << /Type /XObject /Subtype /Image /Width 150 /Height 150 /ColorSpace /DeviceRGB /Filter /DCTDecode /BitsPerComponent 8 /Length 11785>> stream JFIF;CREATOR: gd-jpeg v1.0 (using IJG JPEG v62), quality = 90 C     C   " }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz w!1AQaq"2B #3Rbr $4%&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz ?Q\NV0/o2?J"YMsr ${#g8/[ 4VCTqycbçx[דxoVأkn}k?j mOX*Hl%xԑB,H9=9~]|4m78nh#S v_ӗ4W{#j`o? 6ͬ_L-gto$%Aoq3^ĸ}B~3d]Mx㳹 t,rF}+X?=r[}?R%=*I&$3mϩ&YT5+-mP`c60a ⿅+f;nDc}y=} q1(jqqզӋiꋭJTe/B+ A~H~(ם_?~]%{e[9R;WLy\蘟Ν]q[up JX߲kcLt G&7y{W/'{Ě8ZS[Ooqj|*Ѯ՝% 5֕_j N7)pFk UU^kEWmU滯2[~'9MKϩ^AGO~𮾺ݱĤv:COF⯅ xŚ ƭEumn`>6Mh.{yH>w|Z<Sn~uW98z ׊Rai?F%=7o_/|5џlqe5} Kn{i{/mmD9y>lclO˫fY.}QG#1 g~O?xrxF׮UU)4㌔l@Om Xjze>Al<|8zzit_s/dw$ 'k-:-N2~I.ΛoZ|9h!O!w%7y!I+ C&KG ӵxO۱dg;G8)/Ҹ+1?(fUcisp&B۸#?v`}jL5]jqu3;g5OZ}v {5H+GWG/(֝TJcwʡ&Ls.z@xW5ZPNXIZ&GHSe W_gK\iLe4I`ێ˸ sMC/RgFVZR:x]IukTf_*]_kku?ڌ)^ c'7zhۍfIZ=w>et 3SZF|H*Y6C(PA|`>v _^*¾fEߠq~K}czψu(ʭvm8~8gR)em.}pxJX*6ͷIsKso~m~|  /x|GC+S溵3-J0+E=ܣ:du_$%gu}.~1~N;x>TZuAt5(;8brIΌ9y7:y?_WVdžc'oXOu(ɯH=G|V^x[X|WԿy%C;'#ou3D/i~})f;@MQ|AcjVJm'Iv7m'F,u:$0#p'A_/wgoi }sW+eʏ+qs`C^yN{{^1)Qr22 [/{yxe$+PG??_oY"ñ:2#BJ+KXyp8$URKڀ:9$c #jX~;+7UO~zn䃡Zݏ_P: _ / }|7qWme'W-SL6@N%41|b2gOxgY0WLK{9xi d~O NIU[/:tpzto+EuQGj(;Rה@4^*;:i:d{i Y^eY$bB5gAx6w 'b,E=3 QnM:Mrk{ ]X kdWD1ѷ [;֏׾ nNI$8EUUA,>>m!{ 2&Z&wso/IkF'Wi>ioRVX-ʲH '0J*I} GykV~E՜# H 36t3}7v=@ gᇌtZS{?R;fh#Ip)F r|B߯YeZJލ u3YG)>%ox[5=7:d.br\3qj.8gX;?hW? |[.ʶv7{c<#a AQ^+~՞YZ[O_$JY ;2V9zxLX]F@|$MUc Q\/Ŀ 4 ;#X5 ni`my]eRz7~Ծ[iwnm '6%g1۷ٮ#@4eQyI嶎?~;徒JG ˖G8eFA}*O2[amwyk|$I3y5x\w?~ ], XE'͑H'Ĺ8n9/>SYXkst1,ְGq,&JHAq0-hy7]p'_Ś7i/-~>,ڝD+HX+nf e9VW?ekyWC_i5@$y{}f]J+.wI)%'Nҧ__?)ֿ1O5S74 s /Mk[SJF vIwo.rŀXk3ֿ3?gZWekWE͜u?ПAik{!쐳,+s޼טPXW/t:(=(H/^6ᘭԧkxaY;x߲b Jy5>!e:?e'ZCU*&S0 OGM'Tկ%WjǼAlWڷy{Ÿ>.x[Wsmz/⽎dD;85_'dVn}SA%Fj `}+[O~} mtI ʩ++Cy/R)V8ݑɄb}CО(dؿtV=RɮIˑ^[~~vK%Ƌa|IxY9_:בn^?> 8C|-3?F1GɯbgN^920g_ m]:Von$cc>r?<1*>'o֍4۽ܚt{PT p^ү5o 蚶Z\Ill=g#~6:d9hFK:¢G|V-LkSadŒ@MC> ]i~+gSNeGĺ˩#K?y5Pvh]'t`,D 㩯kIs mұ瑤I噎I5hSIUKޕ鷧nrqP{##vbZWm&_Ho#vbZWm&_H?$b^Myulys[.\:⽿1eMC\c"y2!"3فOZ{WoSdp'k`޾% [7zO}6UЦ9g7 rC ,rW۵۽m#?P5=x>,|wx\-Ai.:n~TAú>Nsɧs{|ٚ䃍(~ӳ)wT7W,=3׊kuI Bvfƻϴd={kv-O5g?.|iu,}*"y?y4;A,7Hb?Qy3|k8_n4tI扼[0]_GiGExp Q]sWčxlx qhk|Y4v@+X|FXtwœ{..s ;&٦uCg_xGL k0Əϧ^ŽP RE 0FU9WǍm$>׋,4}J{ıѬX2`J E7С9V%I+oVyh$k}~ yR8#Zŏ>׼+ iH?]x?5-g(HUQ"rĐ9{7ŝľѤixO,YϋVHy4QlF|ti=Ӷ??\(U%'#o ǩ:'"Wg_gŞttXYkW6!sv&Z*̨nBFϷYſ x?Ķ n5^I٘.Xo"_w ;èfww+mI_ kW^/{zG[5b䟼16Nj6#~ YI6a?afShVg=|9x<#4!mL[Ϫݒ. k`PuTc8z/?_Uo؇T/'[#cc^z >U'thoykuk+:$lBK U6i9'%#6Xj o m#{OU KI2͎W/A}Û:OV^ >wgq{-ۅbYe1@Xۏ)A~~-|uy[TD>u{;sri24 g/+iYoh.qyD_hZ牣{H-'x6i(ᄇ8 Gsx9Ki J>+;?ݣ75I].N1YWM&Ս&G7h/AZkۺVf(m5;kcwPY :b_׿fߎ?ռWc|7&~]Z4`&B;PFkGEm[}:]%REײZ^igz7|"]|'sEE·GXe$'gTA iӵMNDnB+ H^G jُ@z_?C |a}+B7MK@^_įxj>*4%O, Ѳcqh~!7{Uٯ3=Φ-uR9k)` 148s_uw৉5\m3Dɂ~k>TzL ~aʥXRI/7wfN׿]gqUƗzŖlҽPBΥ&AW?|NCBH)hzš{|7ra '^1wzZWv<[1ɷ=i>-ϖ5eEqm{&'|5CZ>E^1[%~aך5?|/V_Eq ;oj 1**{=.Xd@׸5Н9ZqvgK7[koMύ<;]V48E,t o9< 1+ bRhVXYh^"g Aߕ~tXĺug(TKƹR0y;v'8GCG7=zإII#m2<z+29-NfE5Sy˛ך(~=8qvK'({x8;_>"aq2R*lqڿ[hJ_xb=gWrU cҊ+ h?|5Q֗Rۦ$!P瞝νjW~Vu4]ȃ2HYð%ǒ}=Wq* 'z6R[I5zYzk_ٵqw v^&6iE=:R?i7.^#5S5xnt; {E#p_{n :1~4Q_GשQURoG%xՒGK9ҿ+'د$Q^>'qLHa *$2w)0|SoCΣw-ΧAM<̱ ^F=(a[F^?D45NTk{Kue>!&Z嶹 x1YÍgϽ|/c@_[kĿe'[-6,ll{t+Lq51QI.g{/#gR_.G;֣ww:qO?v `ӽycsFowk>pc1lg4Q_ՎqK:rmy?槇ҿc$?gQN|Q?K1i.5mWNmVVTk2=hu'IBrmp_oj(O endstream endobj 313 0 obj << /Type /Annot /Subtype /Link /A 314 0 R /Border [0 0 0] /H /I /Rect [ 177.9698 179.5546 194.2328 189.4752 ] >> endobj 314 0 obj << /Type /Action >> endobj 315 0 obj << /Type /Annot /Subtype /Link /A 316 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 754.6696 181.7625 764.5902 ] >> endobj 316 0 obj << /Type /Action /S /URI /URI (https://www.nitrc.org/projects/dtiprep/) >> endobj 317 0 obj << /Type /Annot /Subtype /Link /A 318 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 504.3930 147.7500 616.8930 ] >> endobj 318 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure4.jpg) >> endobj 319 0 obj << /Type /Annot /Subtype /Link /A 320 0 R /Border [0 0 0] /H /I /Rect [ 177.9698 179.5546 194.2328 189.4752 ] >> endobj 320 0 obj << /Type /Action >> endobj 321 0 obj << /Type /Annot /Subtype /Link /A 322 0 R /Border [0 0 0] /H /I /Rect [ 26.2500 754.6696 181.7625 764.5902 ] >> endobj 322 0 obj << /Type /Action /S /URI /URI (https://www.nitrc.org/projects/dtiprep/) >> endobj 323 0 obj << /Type /Annot /Subtype /Link /A 324 0 R /Border [0 0 0] /H /I /Rect [ 35.2500 504.3930 147.7500 616.8930 ] >> endobj 324 0 obj << /Type /Action /S /URI /URI (https://currents.plos.org/hd/files/2011/06/figure4.jpg) >> endobj 325 0 obj << /Type /Annot /Subtype /Link /A 326 0 R /Border [0 0 0] /H /I /Rect [ 177.9698 179.5546 194.2328 189.4752 ] >> endobj 326 0 obj << /Type /Action >> endobj 327 0 obj << /Type /Page /Parent 3 0 R /Annots [ 329 0 R 331 0 R 333 0 R ] /Contents 328 0 R >> endobj 328 0 obj << /Length 22060 >> stream 0.271 0.267 0.267 rg q 15.000 36.735 577.500 740.265 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(the type of movement that occurred. Moreover, this study was restricted to FA measures, the extension to more complex DTI )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(parameters such as fiber tracking, which are more sensitive on an accurate diffusion tensor and thus the number of gradient )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(directions, has to be topic of future studies.)] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(Although it should be kept in mind that excessive movement and other artifacts increase noise and will therefore decrease the )] TJ ET BT 26.250 712.357 Td /F1 9.8 Tf [(sensitivity to detect true artifacts, the results presented here are encouraging for large-scale studies in HD. Despite obvious )] TJ ET BT 26.250 700.452 Td /F1 9.8 Tf [(movement in several cases, these movements did not influence the FA value systematically. These results do not differ when )] TJ ET BT 26.250 688.548 Td /F1 9.8 Tf [(the QC tool is included into the postprocessing, even when the statistics are leniently uncorrected. This speaks to the relative )] TJ ET BT 26.250 676.643 Td /F1 9.8 Tf [(robustness of the FA values in DTI research in HD which are computed by taking all directions into account. Given a thorough )] TJ ET BT 26.250 664.738 Td /F1 9.8 Tf [(postprocessing of the MRI data as previously demonstrated in morphometric T1 weighted MRI analysis )] TJ ET 0.267 0.267 0.267 rg BT 472.751 664.738 Td /F1 9.8 Tf [([17])] TJ ET 0.271 0.267 0.267 rg BT 489.014 664.738 Td /F1 9.8 Tf [(, this observation, as )] TJ ET BT 26.250 652.833 Td /F1 9.8 Tf [(a further conclusion, speaks to the potential of the use of MRI-based measures such as DTI as a biomarker in HD)] TJ ET BT 26.250 616.231 Td /F4 12.0 Tf [(Competing interests)] TJ ET BT 26.250 596.277 Td /F1 9.8 Tf [(The authors have declared that no competing interests exist.)] TJ ET BT 26.250 559.674 Td /F4 12.0 Tf [(Acknowledgements)] TJ ET BT 26.250 539.720 Td /F1 9.8 Tf [(The authors wish to extend their gratitude to the London TRACK-HD study participants and to Beth Borowsky, scientific director )] TJ ET BT 26.250 527.815 Td /F1 9.8 Tf [(for TRACK-HD at CHDI. Some of this work was undertaken at UCLH/UCL who acknowledge support from the respective )] TJ ET BT 26.250 515.910 Td /F1 9.8 Tf [(Department of Healths NIHR Biomedical Research Centres.)] TJ ET BT 26.250 486.808 Td /F4 12.0 Tf [(References)] TJ ET BT 26.250 459.354 Td /F1 9.8 Tf [(1.)] TJ ET BT 38.132 459.354 Td /F1 9.8 Tf [(Bohanna I, Georgiou-Karistianis N, Hannan AJ, Egan GF. Magnetic resonance imaging as an approach towards identifying )] TJ ET BT 26.250 447.449 Td /F1 9.8 Tf [(neuropathological biomarkers for Huntington's disease. Brain Res Rev. 2008 Jun;58\(1\):209-25. Epub 2008 Apr 9. Review. )] TJ ET BT 26.250 435.544 Td /F1 9.8 Tf [(PubMed PMID: 18486229.)] TJ ET BT 26.250 416.139 Td /F1 9.8 Tf [(2.)] TJ ET BT 38.132 416.139 Td /F1 9.8 Tf [(Klppel S, Henley SM, Hobbs NZ, Wolf RC, Kassubek J, Tabrizi SJ, Frackowiak RS. Magnetic resonance imaging of )] TJ ET BT 26.250 404.235 Td /F1 9.8 Tf [(Huntington's disease: preparing for clinical trials. Neuroscience. 2009 Nov 24;164\(1\):205-19. Epub 2009 Jan 29. Review. )] TJ ET BT 26.250 392.330 Td /F1 9.8 Tf [(PubMed PMID: 19409230; PubMed Central PMCID: PMC2771270.)] TJ ET BT 26.250 372.925 Td /F1 9.8 Tf [(3.)] TJ ET BT 38.132 372.925 Td /F1 9.8 Tf [(Basser PJ, Jones DK. Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR )] TJ ET BT 26.250 361.020 Td /F1 9.8 Tf [(Biomed. 2002 Nov-Dec;15\(7-8\):456-67. Review. PubMed PMID: 12489095.)] TJ ET BT 26.250 341.616 Td /F1 9.8 Tf [(4.)] TJ ET BT 38.132 341.616 Td /F1 9.8 Tf [(Weaver KE, Richards TL, Liang O, Laurino MY, Sami A, Aylward EH. Longitudinal diffusion tensor imaging in Huntington's )] TJ ET BT 26.250 329.711 Td /F1 9.8 Tf [(Disease. Exp Neurol. 2009 Jan 13. [Epub ahead of print] PubMed PMID: 19416685.)] TJ ET BT 26.250 310.306 Td /F1 9.8 Tf [(5.)] TJ ET BT 38.132 310.306 Td /F1 9.8 Tf [(Dumas EM, van den Bogaard SJ, Ruber ME, Reilman RR, Stout JC, Craufurd D, Hicks SL, Kennard C, Tabrizi SJ, van )] TJ ET BT 26.250 298.401 Td /F1 9.8 Tf [(Buchem MA, van der Grond J, Roos RA. Early changes in white matter pathways of the sensorimotor cortex in premanifest )] TJ ET BT 26.250 286.497 Td /F1 9.8 Tf [(Huntington's disease. Hum Brain Mapp. 2011 Jan 24. doi: 10.1002/hbm.21205. [Epub ahead of print] PubMed PMID: 21264990.)] TJ ET BT 26.250 267.092 Td /F1 9.8 Tf [(6.)] TJ ET BT 38.132 267.092 Td /F1 9.8 Tf [(Klppel S, Draganski B, Golding CV, Chu C, Nagy Z, Cook PA, Hicks SL, Kennard C, Alexander DC, Parker GJ, Tabrizi SJ, )] TJ ET BT 26.250 255.187 Td /F1 9.8 Tf [(Frackowiak RS. White matter connections reflect changes in voluntary-guided saccades in pre-symptomatic Huntington's )] TJ ET BT 26.250 243.282 Td /F1 9.8 Tf [(disease. Brain. 2008 Jan;131\(Pt 1\):196-204. Epub 2007 Dec 3. PubMed PMID: 18056161.)] TJ ET BT 26.250 223.878 Td /F1 9.8 Tf [(7.)] TJ ET BT 38.132 223.878 Td /F1 9.8 Tf [(Paulsen JS, Hayden M, Stout JC, Langbehn DR, Aylward E, Ross CA, Guttman M, Nance M, Kieburtz K, Oakes D, Shoulson )] TJ ET BT 26.250 211.973 Td /F1 9.8 Tf [(I, Kayson E, Johnson S, Penziner E; Predict-HD Investigators of the Huntington Study Group. Preparing for preventive clinical )] TJ ET BT 26.250 200.068 Td /F1 9.8 Tf [(trials: the Predict-HD study. Arch Neurol. 2006 Jun;63\(6\):883-90. PubMed PMID: 16769871.)] TJ ET BT 26.250 180.663 Td /F1 9.8 Tf [(8.)] TJ ET BT 38.132 180.663 Td /F1 9.8 Tf [(Tabrizi SJ, Langbehn DR, Leavitt BR, Roos RA, Durr A, Craufurd D, Kennard C, Hicks SL, Fox NC, Scahill RI, Borowsky B, )] TJ ET BT 26.250 168.759 Td /F1 9.8 Tf [(Tobin AJ, Rosas HD, Johnson H, Reilmann R, Landwehrmeyer B, Stout JC; TRACK-HD investigators. Biological and clinical )] TJ ET BT 26.250 156.854 Td /F1 9.8 Tf [(manifestations of Huntington's disease in the longitudinal TRACK-HD study: cross-sectional analysis of baseline data. Lancet )] TJ ET BT 26.250 144.949 Td /F1 9.8 Tf [(Neurol. 2009 Sep;8\(9\):791-801. Epub 2009 Jul 29. PubMed PMID: 19646924.)] TJ ET BT 26.250 125.544 Td /F1 9.8 Tf [(9.)] TJ ET BT 38.132 125.544 Td /F1 9.8 Tf [(Langbehn DR, Brinkman RR, Falush D, Paulsen JS, Hayden MR; International Huntington's Disease Collaborative Group. A )] TJ ET BT 26.250 113.640 Td /F1 9.8 Tf [(new model for prediction of the age of onset and penetrance for Huntington's disease based on CAG length. Clin Genet. 2004 )] TJ ET BT 26.250 101.735 Td /F1 9.8 Tf [(Apr;65\(4\):267-77. Erratum in: Clin Genet. 2004 Jul;66\(1\):81. PubMed PMID: 15025718.)] TJ ET BT 26.250 82.330 Td /F1 9.8 Tf [(10.)] TJ ET BT 43.553 82.330 Td /F1 9.8 Tf [(Reese TG, Heid O, Weisskoff RM, Wedeen VJ. Reduction of eddy-current-induced distortion in diffusion MRI using a twice-)] TJ ET BT 26.250 70.425 Td /F1 9.8 Tf [(refocused spin echo. Magn Reson Med. 2003 Jan;49\(1\):177-82. PubMed PMID: 12509835.)] TJ ET BT 26.250 51.021 Td /F1 9.8 Tf [(11.)] TJ ET BT 43.553 51.021 Td /F1 9.8 Tf [(Basser PJ, Mattiello J, LeBihan D. Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson )] TJ ET Q q 15.000 36.735 577.500 740.265 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(the type of movement that occurred. Moreover, this study was restricted to FA measures, the extension to more complex DTI )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(parameters such as fiber tracking, which are more sensitive on an accurate diffusion tensor and thus the number of gradient )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(directions, has to be topic of future studies.)] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(Although it should be kept in mind that excessive movement and other artifacts increase noise and will therefore decrease the )] TJ ET BT 26.250 712.357 Td /F1 9.8 Tf [(sensitivity to detect true artifacts, the results presented here are encouraging for large-scale studies in HD. Despite obvious )] TJ ET BT 26.250 700.452 Td /F1 9.8 Tf [(movement in several cases, these movements did not influence the FA value systematically. These results do not differ when )] TJ ET BT 26.250 688.548 Td /F1 9.8 Tf [(the QC tool is included into the postprocessing, even when the statistics are leniently uncorrected. This speaks to the relative )] TJ ET BT 26.250 676.643 Td /F1 9.8 Tf [(robustness of the FA values in DTI research in HD which are computed by taking all directions into account. Given a thorough )] TJ ET BT 26.250 664.738 Td /F1 9.8 Tf [(postprocessing of the MRI data as previously demonstrated in morphometric T1 weighted MRI analysis )] TJ ET 0.267 0.267 0.267 rg BT 472.751 664.738 Td /F1 9.8 Tf [([17])] TJ ET 0.271 0.267 0.267 rg BT 489.014 664.738 Td /F1 9.8 Tf [(, this observation, as )] TJ ET BT 26.250 652.833 Td /F1 9.8 Tf [(a further conclusion, speaks to the potential of the use of MRI-based measures such as DTI as a biomarker in HD)] TJ ET BT 26.250 616.231 Td /F4 12.0 Tf [(Competing interests)] TJ ET BT 26.250 596.277 Td /F1 9.8 Tf [(The authors have declared that no competing interests exist.)] TJ ET BT 26.250 559.674 Td /F4 12.0 Tf [(Acknowledgements)] TJ ET BT 26.250 539.720 Td /F1 9.8 Tf [(The authors wish to extend their gratitude to the London TRACK-HD study participants and to Beth Borowsky, scientific director )] TJ ET BT 26.250 527.815 Td /F1 9.8 Tf [(for TRACK-HD at CHDI. Some of this work was undertaken at UCLH/UCL who acknowledge support from the respective )] TJ ET BT 26.250 515.910 Td /F1 9.8 Tf [(Department of Healths NIHR Biomedical Research Centres.)] TJ ET BT 26.250 486.808 Td /F4 12.0 Tf [(References)] TJ ET BT 26.250 459.354 Td /F1 9.8 Tf [(1.)] TJ ET BT 38.132 459.354 Td /F1 9.8 Tf [(Bohanna I, Georgiou-Karistianis N, Hannan AJ, Egan GF. Magnetic resonance imaging as an approach towards identifying )] TJ ET BT 26.250 447.449 Td /F1 9.8 Tf [(neuropathological biomarkers for Huntington's disease. Brain Res Rev. 2008 Jun;58\(1\):209-25. Epub 2008 Apr 9. Review. )] TJ ET BT 26.250 435.544 Td /F1 9.8 Tf [(PubMed PMID: 18486229.)] TJ ET BT 26.250 416.139 Td /F1 9.8 Tf [(2.)] TJ ET BT 38.132 416.139 Td /F1 9.8 Tf [(Klppel S, Henley SM, Hobbs NZ, Wolf RC, Kassubek J, Tabrizi SJ, Frackowiak RS. Magnetic resonance imaging of )] TJ ET BT 26.250 404.235 Td /F1 9.8 Tf [(Huntington's disease: preparing for clinical trials. Neuroscience. 2009 Nov 24;164\(1\):205-19. Epub 2009 Jan 29. Review. )] TJ ET BT 26.250 392.330 Td /F1 9.8 Tf [(PubMed PMID: 19409230; PubMed Central PMCID: PMC2771270.)] TJ ET BT 26.250 372.925 Td /F1 9.8 Tf [(3.)] TJ ET BT 38.132 372.925 Td /F1 9.8 Tf [(Basser PJ, Jones DK. Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR )] TJ ET BT 26.250 361.020 Td /F1 9.8 Tf [(Biomed. 2002 Nov-Dec;15\(7-8\):456-67. Review. PubMed PMID: 12489095.)] TJ ET BT 26.250 341.616 Td /F1 9.8 Tf [(4.)] TJ ET BT 38.132 341.616 Td /F1 9.8 Tf [(Weaver KE, Richards TL, Liang O, Laurino MY, Sami A, Aylward EH. Longitudinal diffusion tensor imaging in Huntington's )] TJ ET BT 26.250 329.711 Td /F1 9.8 Tf [(Disease. Exp Neurol. 2009 Jan 13. [Epub ahead of print] PubMed PMID: 19416685.)] TJ ET BT 26.250 310.306 Td /F1 9.8 Tf [(5.)] TJ ET BT 38.132 310.306 Td /F1 9.8 Tf [(Dumas EM, van den Bogaard SJ, Ruber ME, Reilman RR, Stout JC, Craufurd D, Hicks SL, Kennard C, Tabrizi SJ, van )] TJ ET BT 26.250 298.401 Td /F1 9.8 Tf [(Buchem MA, van der Grond J, Roos RA. Early changes in white matter pathways of the sensorimotor cortex in premanifest )] TJ ET BT 26.250 286.497 Td /F1 9.8 Tf [(Huntington's disease. Hum Brain Mapp. 2011 Jan 24. doi: 10.1002/hbm.21205. [Epub ahead of print] PubMed PMID: 21264990.)] TJ ET BT 26.250 267.092 Td /F1 9.8 Tf [(6.)] TJ ET BT 38.132 267.092 Td /F1 9.8 Tf [(Klppel S, Draganski B, Golding CV, Chu C, Nagy Z, Cook PA, Hicks SL, Kennard C, Alexander DC, Parker GJ, Tabrizi SJ, )] TJ ET BT 26.250 255.187 Td /F1 9.8 Tf [(Frackowiak RS. White matter connections reflect changes in voluntary-guided saccades in pre-symptomatic Huntington's )] TJ ET BT 26.250 243.282 Td /F1 9.8 Tf [(disease. Brain. 2008 Jan;131\(Pt 1\):196-204. Epub 2007 Dec 3. PubMed PMID: 18056161.)] TJ ET BT 26.250 223.878 Td /F1 9.8 Tf [(7.)] TJ ET BT 38.132 223.878 Td /F1 9.8 Tf [(Paulsen JS, Hayden M, Stout JC, Langbehn DR, Aylward E, Ross CA, Guttman M, Nance M, Kieburtz K, Oakes D, Shoulson )] TJ ET BT 26.250 211.973 Td /F1 9.8 Tf [(I, Kayson E, Johnson S, Penziner E; Predict-HD Investigators of the Huntington Study Group. Preparing for preventive clinical )] TJ ET BT 26.250 200.068 Td /F1 9.8 Tf [(trials: the Predict-HD study. Arch Neurol. 2006 Jun;63\(6\):883-90. PubMed PMID: 16769871.)] TJ ET BT 26.250 180.663 Td /F1 9.8 Tf [(8.)] TJ ET BT 38.132 180.663 Td /F1 9.8 Tf [(Tabrizi SJ, Langbehn DR, Leavitt BR, Roos RA, Durr A, Craufurd D, Kennard C, Hicks SL, Fox NC, Scahill RI, Borowsky B, )] TJ ET BT 26.250 168.759 Td /F1 9.8 Tf [(Tobin AJ, Rosas HD, Johnson H, Reilmann R, Landwehrmeyer B, Stout JC; TRACK-HD investigators. Biological and clinical )] TJ ET BT 26.250 156.854 Td /F1 9.8 Tf [(manifestations of Huntington's disease in the longitudinal TRACK-HD study: cross-sectional analysis of baseline data. Lancet )] TJ ET BT 26.250 144.949 Td /F1 9.8 Tf [(Neurol. 2009 Sep;8\(9\):791-801. Epub 2009 Jul 29. PubMed PMID: 19646924.)] TJ ET BT 26.250 125.544 Td /F1 9.8 Tf [(9.)] TJ ET BT 38.132 125.544 Td /F1 9.8 Tf [(Langbehn DR, Brinkman RR, Falush D, Paulsen JS, Hayden MR; International Huntington's Disease Collaborative Group. A )] TJ ET BT 26.250 113.640 Td /F1 9.8 Tf [(new model for prediction of the age of onset and penetrance for Huntington's disease based on CAG length. Clin Genet. 2004 )] TJ ET BT 26.250 101.735 Td /F1 9.8 Tf [(Apr;65\(4\):267-77. Erratum in: Clin Genet. 2004 Jul;66\(1\):81. PubMed PMID: 15025718.)] TJ ET BT 26.250 82.330 Td /F1 9.8 Tf [(10.)] TJ ET BT 43.553 82.330 Td /F1 9.8 Tf [(Reese TG, Heid O, Weisskoff RM, Wedeen VJ. Reduction of eddy-current-induced distortion in diffusion MRI using a twice-)] TJ ET BT 26.250 70.425 Td /F1 9.8 Tf [(refocused spin echo. Magn Reson Med. 2003 Jan;49\(1\):177-82. PubMed PMID: 12509835.)] TJ ET BT 26.250 51.021 Td /F1 9.8 Tf [(11.)] TJ ET BT 43.553 51.021 Td /F1 9.8 Tf [(Basser PJ, Mattiello J, LeBihan D. Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson )] TJ ET Q q 15.000 36.735 577.500 740.265 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(the type of movement that occurred. Moreover, this study was restricted to FA measures, the extension to more complex DTI )] TJ ET BT 26.250 755.571 Td /F1 9.8 Tf [(parameters such as fiber tracking, which are more sensitive on an accurate diffusion tensor and thus the number of gradient )] TJ ET BT 26.250 743.667 Td /F1 9.8 Tf [(directions, has to be topic of future studies.)] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(Although it should be kept in mind that excessive movement and other artifacts increase noise and will therefore decrease the )] TJ ET BT 26.250 712.357 Td /F1 9.8 Tf [(sensitivity to detect true artifacts, the results presented here are encouraging for large-scale studies in HD. Despite obvious )] TJ ET BT 26.250 700.452 Td /F1 9.8 Tf [(movement in several cases, these movements did not influence the FA value systematically. These results do not differ when )] TJ ET BT 26.250 688.548 Td /F1 9.8 Tf [(the QC tool is included into the postprocessing, even when the statistics are leniently uncorrected. This speaks to the relative )] TJ ET BT 26.250 676.643 Td /F1 9.8 Tf [(robustness of the FA values in DTI research in HD which are computed by taking all directions into account. Given a thorough )] TJ ET BT 26.250 664.738 Td /F1 9.8 Tf [(postprocessing of the MRI data as previously demonstrated in morphometric T1 weighted MRI analysis )] TJ ET 0.267 0.267 0.267 rg BT 472.751 664.738 Td /F1 9.8 Tf [([17])] TJ ET 0.271 0.267 0.267 rg BT 489.014 664.738 Td /F1 9.8 Tf [(, this observation, as )] TJ ET BT 26.250 652.833 Td /F1 9.8 Tf [(a further conclusion, speaks to the potential of the use of MRI-based measures such as DTI as a biomarker in HD)] TJ ET BT 26.250 616.231 Td /F4 12.0 Tf [(Competing interests)] TJ ET BT 26.250 596.277 Td /F1 9.8 Tf [(The authors have declared that no competing interests exist.)] TJ ET BT 26.250 559.674 Td /F4 12.0 Tf [(Acknowledgements)] TJ ET BT 26.250 539.720 Td /F1 9.8 Tf [(The authors wish to extend their gratitude to the London TRACK-HD study participants and to Beth Borowsky, scientific director )] TJ ET BT 26.250 527.815 Td /F1 9.8 Tf [(for TRACK-HD at CHDI. Some of this work was undertaken at UCLH/UCL who acknowledge support from the respective )] TJ ET BT 26.250 515.910 Td /F1 9.8 Tf [(Department of Healths NIHR Biomedical Research Centres.)] TJ ET BT 26.250 486.808 Td /F4 12.0 Tf [(References)] TJ ET BT 26.250 459.354 Td /F1 9.8 Tf [(1.)] TJ ET BT 38.132 459.354 Td /F1 9.8 Tf [(Bohanna I, Georgiou-Karistianis N, Hannan AJ, Egan GF. Magnetic resonance imaging as an approach towards identifying )] TJ ET BT 26.250 447.449 Td /F1 9.8 Tf [(neuropathological biomarkers for Huntington's disease. Brain Res Rev. 2008 Jun;58\(1\):209-25. Epub 2008 Apr 9. Review. )] TJ ET BT 26.250 435.544 Td /F1 9.8 Tf [(PubMed PMID: 18486229.)] TJ ET BT 26.250 416.139 Td /F1 9.8 Tf [(2.)] TJ ET BT 38.132 416.139 Td /F1 9.8 Tf [(Klppel S, Henley SM, Hobbs NZ, Wolf RC, Kassubek J, Tabrizi SJ, Frackowiak RS. Magnetic resonance imaging of )] TJ ET BT 26.250 404.235 Td /F1 9.8 Tf [(Huntington's disease: preparing for clinical trials. Neuroscience. 2009 Nov 24;164\(1\):205-19. Epub 2009 Jan 29. Review. )] TJ ET BT 26.250 392.330 Td /F1 9.8 Tf [(PubMed PMID: 19409230; PubMed Central PMCID: PMC2771270.)] TJ ET BT 26.250 372.925 Td /F1 9.8 Tf [(3.)] TJ ET BT 38.132 372.925 Td /F1 9.8 Tf [(Basser PJ, Jones DK. Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR )] TJ ET BT 26.250 361.020 Td /F1 9.8 Tf [(Biomed. 2002 Nov-Dec;15\(7-8\):456-67. Review. PubMed PMID: 12489095.)] TJ ET BT 26.250 341.616 Td /F1 9.8 Tf [(4.)] TJ ET BT 38.132 341.616 Td /F1 9.8 Tf [(Weaver KE, Richards TL, Liang O, Laurino MY, Sami A, Aylward EH. Longitudinal diffusion tensor imaging in Huntington's )] TJ ET BT 26.250 329.711 Td /F1 9.8 Tf [(Disease. Exp Neurol. 2009 Jan 13. [Epub ahead of print] PubMed PMID: 19416685.)] TJ ET BT 26.250 310.306 Td /F1 9.8 Tf [(5.)] TJ ET BT 38.132 310.306 Td /F1 9.8 Tf [(Dumas EM, van den Bogaard SJ, Ruber ME, Reilman RR, Stout JC, Craufurd D, Hicks SL, Kennard C, Tabrizi SJ, van )] TJ ET BT 26.250 298.401 Td /F1 9.8 Tf [(Buchem MA, van der Grond J, Roos RA. Early changes in white matter pathways of the sensorimotor cortex in premanifest )] TJ ET BT 26.250 286.497 Td /F1 9.8 Tf [(Huntington's disease. Hum Brain Mapp. 2011 Jan 24. doi: 10.1002/hbm.21205. [Epub ahead of print] PubMed PMID: 21264990.)] TJ ET BT 26.250 267.092 Td /F1 9.8 Tf [(6.)] TJ ET BT 38.132 267.092 Td /F1 9.8 Tf [(Klppel S, Draganski B, Golding CV, Chu C, Nagy Z, Cook PA, Hicks SL, Kennard C, Alexander DC, Parker GJ, Tabrizi SJ, )] TJ ET BT 26.250 255.187 Td /F1 9.8 Tf [(Frackowiak RS. White matter connections reflect changes in voluntary-guided saccades in pre-symptomatic Huntington's )] TJ ET BT 26.250 243.282 Td /F1 9.8 Tf [(disease. Brain. 2008 Jan;131\(Pt 1\):196-204. Epub 2007 Dec 3. PubMed PMID: 18056161.)] TJ ET BT 26.250 223.878 Td /F1 9.8 Tf [(7.)] TJ ET BT 38.132 223.878 Td /F1 9.8 Tf [(Paulsen JS, Hayden M, Stout JC, Langbehn DR, Aylward E, Ross CA, Guttman M, Nance M, Kieburtz K, Oakes D, Shoulson )] TJ ET BT 26.250 211.973 Td /F1 9.8 Tf [(I, Kayson E, Johnson S, Penziner E; Predict-HD Investigators of the Huntington Study Group. Preparing for preventive clinical )] TJ ET BT 26.250 200.068 Td /F1 9.8 Tf [(trials: the Predict-HD study. Arch Neurol. 2006 Jun;63\(6\):883-90. PubMed PMID: 16769871.)] TJ ET BT 26.250 180.663 Td /F1 9.8 Tf [(8.)] TJ ET BT 38.132 180.663 Td /F1 9.8 Tf [(Tabrizi SJ, Langbehn DR, Leavitt BR, Roos RA, Durr A, Craufurd D, Kennard C, Hicks SL, Fox NC, Scahill RI, Borowsky B, )] TJ ET BT 26.250 168.759 Td /F1 9.8 Tf [(Tobin AJ, Rosas HD, Johnson H, Reilmann R, Landwehrmeyer B, Stout JC; TRACK-HD investigators. Biological and clinical )] TJ ET BT 26.250 156.854 Td /F1 9.8 Tf [(manifestations of Huntington's disease in the longitudinal TRACK-HD study: cross-sectional analysis of baseline data. Lancet )] TJ ET BT 26.250 144.949 Td /F1 9.8 Tf [(Neurol. 2009 Sep;8\(9\):791-801. Epub 2009 Jul 29. PubMed PMID: 19646924.)] TJ ET BT 26.250 125.544 Td /F1 9.8 Tf [(9.)] TJ ET BT 38.132 125.544 Td /F1 9.8 Tf [(Langbehn DR, Brinkman RR, Falush D, Paulsen JS, Hayden MR; International Huntington's Disease Collaborative Group. A )] TJ ET BT 26.250 113.640 Td /F1 9.8 Tf [(new model for prediction of the age of onset and penetrance for Huntington's disease based on CAG length. Clin Genet. 2004 )] TJ ET BT 26.250 101.735 Td /F1 9.8 Tf [(Apr;65\(4\):267-77. Erratum in: Clin Genet. 2004 Jul;66\(1\):81. PubMed PMID: 15025718.)] TJ ET BT 26.250 82.330 Td /F1 9.8 Tf [(10.)] TJ ET BT 43.553 82.330 Td /F1 9.8 Tf [(Reese TG, Heid O, Weisskoff RM, Wedeen VJ. Reduction of eddy-current-induced distortion in diffusion MRI using a twice-)] TJ ET BT 26.250 70.425 Td /F1 9.8 Tf [(refocused spin echo. Magn Reson Med. 2003 Jan;49\(1\):177-82. PubMed PMID: 12509835.)] TJ ET BT 26.250 51.021 Td /F1 9.8 Tf [(11.)] TJ ET BT 43.553 51.021 Td /F1 9.8 Tf [(Basser PJ, Mattiello J, LeBihan D. Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson )] TJ ET Q q 0.000 0.000 0.000 rg BT 291.710 19.825 Td /F1 11.0 Tf [(6)] TJ ET BT 25.000 19.825 Td /F1 11.0 Tf [(PLOS Currents Huntington Disease)] TJ ET Q endstream endobj 329 0 obj << /Type /Annot /Subtype /Link /A 330 0 R /Border [0 0 0] /H /I /Rect [ 472.7513 663.8363 489.0143 673.7570 ] >> endobj 330 0 obj << /Type /Action >> endobj 331 0 obj << /Type /Annot /Subtype /Link /A 332 0 R /Border [0 0 0] /H /I /Rect [ 472.7513 663.8363 489.0143 673.7570 ] >> endobj 332 0 obj << /Type /Action >> endobj 333 0 obj << /Type /Annot /Subtype /Link /A 334 0 R /Border [0 0 0] /H /I /Rect [ 472.7513 663.8363 489.0143 673.7570 ] >> endobj 334 0 obj << /Type /Action >> endobj 335 0 obj << /Type /Page /Parent 3 0 R /Contents 336 0 R >> endobj 336 0 obj << /Length 8104 >> stream 0.271 0.267 0.267 rg q 15.000 514.619 577.500 262.381 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(B. 1994 Mar;103\(3\):247-54. PubMed PMID: 8019776.)] TJ ET BT 26.250 748.071 Td /F1 9.8 Tf [(12.)] TJ ET BT 43.553 748.071 Td /F1 9.8 Tf [(Wheeler-Kingshott CA, Parker GJ, Symms MR, Hickman SJ, Tofts PS, Miller DH, Barker GJ. ADC mapping of the human )] TJ ET BT 26.250 736.167 Td /F1 9.8 Tf [(optic nerve: increased resolution, coverage, and reliability with CSF-suppressed ZOOM-EPI. Magn Reson Med. 2002 )] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(Jan;47\(1\):24-31. PubMed PMID: 11754439.)] TJ ET BT 26.250 704.857 Td /F1 9.8 Tf [(13.)] TJ ET BT 43.553 704.857 Td /F1 9.8 Tf [(Deichmann R, Schwarzbauer C, Turner R. Optimisation of the 3D MDEFT sequence for anatomical brain imaging: technical )] TJ ET BT 26.250 692.952 Td /F1 9.8 Tf [(implications at 1.5 and 3 T. Neuroimage. 2004 Feb;21\(2\):757-67. PubMed PMID: 14980579.)] TJ ET BT 26.250 673.548 Td /F1 9.8 Tf [(14.)] TJ ET BT 43.553 673.548 Td /F1 9.8 Tf [(Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage. 2007 Oct 15;38\(1\):95-113. Epub 2007 Jul 18. )] TJ ET BT 26.250 661.643 Td /F1 9.8 Tf [(PubMed PMID: 17761438.)] TJ ET BT 26.250 642.238 Td /F1 9.8 Tf [(15.)] TJ ET BT 43.553 642.238 Td /F1 9.8 Tf [(Rosas HD, Tuch DS, Hevelone ND, Zaleta AK, Vangel M, Hersch SM, Salat DH. Diffusion tensor imaging in )] TJ ET BT 26.250 630.333 Td /F1 9.8 Tf [(presymptomatic and early Huntington's disease: Selective white matter pathology and its relationship to clinical measures. Mov )] TJ ET BT 26.250 618.429 Td /F1 9.8 Tf [(Disord. 2006 Sep;21\(9\):1317-25. PubMed PMID: 16755582.)] TJ ET BT 26.250 599.024 Td /F1 9.8 Tf [(16.)] TJ ET BT 43.553 599.024 Td /F1 9.8 Tf [(Douaud G, Behrens TE, Poupon C, Cointepas Y, Jbabdi S, Gaura V, Golestani N, Krystkowiak P, Verny C, Damier P, )] TJ ET BT 26.250 587.119 Td /F1 9.8 Tf [(Bachoud-Lvi AC, Hantraye P, Remy P. In vivo evidence for the selective subcortical degeneration in Huntington's disease. )] TJ ET BT 26.250 575.214 Td /F1 9.8 Tf [(Neuroimage. 2009 Jul 15;46\(4\):958-66. Epub 2009 Mar 28. PubMed PMID: 19332141.)] TJ ET BT 26.250 555.810 Td /F1 9.8 Tf [(17.)] TJ ET BT 43.553 555.810 Td /F1 9.8 Tf [(Henley SM, Ridgway GR, Scahill RI, Klppel S, Tabrizi SJ, Fox NC, Kassubek J; EHDN Imaging Working Group. Pitfalls in )] TJ ET BT 26.250 543.905 Td /F1 9.8 Tf [(the use of voxel-based morphometry as a biomarker: examples from huntington disease. AJNR Am J Neuroradiol. 2010 )] TJ ET BT 26.250 532.000 Td /F1 9.8 Tf [(Apr;31\(4\):711-9. Epub 2009 Dec 24. PubMed PMID: 20037137.)] TJ ET Q q 15.000 514.619 577.500 262.381 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(B. 1994 Mar;103\(3\):247-54. PubMed PMID: 8019776.)] TJ ET BT 26.250 748.071 Td /F1 9.8 Tf [(12.)] TJ ET BT 43.553 748.071 Td /F1 9.8 Tf [(Wheeler-Kingshott CA, Parker GJ, Symms MR, Hickman SJ, Tofts PS, Miller DH, Barker GJ. ADC mapping of the human )] TJ ET BT 26.250 736.167 Td /F1 9.8 Tf [(optic nerve: increased resolution, coverage, and reliability with CSF-suppressed ZOOM-EPI. Magn Reson Med. 2002 )] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(Jan;47\(1\):24-31. PubMed PMID: 11754439.)] TJ ET BT 26.250 704.857 Td /F1 9.8 Tf [(13.)] TJ ET BT 43.553 704.857 Td /F1 9.8 Tf [(Deichmann R, Schwarzbauer C, Turner R. Optimisation of the 3D MDEFT sequence for anatomical brain imaging: technical )] TJ ET BT 26.250 692.952 Td /F1 9.8 Tf [(implications at 1.5 and 3 T. Neuroimage. 2004 Feb;21\(2\):757-67. PubMed PMID: 14980579.)] TJ ET BT 26.250 673.548 Td /F1 9.8 Tf [(14.)] TJ ET BT 43.553 673.548 Td /F1 9.8 Tf [(Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage. 2007 Oct 15;38\(1\):95-113. Epub 2007 Jul 18. )] TJ ET BT 26.250 661.643 Td /F1 9.8 Tf [(PubMed PMID: 17761438.)] TJ ET BT 26.250 642.238 Td /F1 9.8 Tf [(15.)] TJ ET BT 43.553 642.238 Td /F1 9.8 Tf [(Rosas HD, Tuch DS, Hevelone ND, Zaleta AK, Vangel M, Hersch SM, Salat DH. Diffusion tensor imaging in )] TJ ET BT 26.250 630.333 Td /F1 9.8 Tf [(presymptomatic and early Huntington's disease: Selective white matter pathology and its relationship to clinical measures. Mov )] TJ ET BT 26.250 618.429 Td /F1 9.8 Tf [(Disord. 2006 Sep;21\(9\):1317-25. PubMed PMID: 16755582.)] TJ ET BT 26.250 599.024 Td /F1 9.8 Tf [(16.)] TJ ET BT 43.553 599.024 Td /F1 9.8 Tf [(Douaud G, Behrens TE, Poupon C, Cointepas Y, Jbabdi S, Gaura V, Golestani N, Krystkowiak P, Verny C, Damier P, )] TJ ET BT 26.250 587.119 Td /F1 9.8 Tf [(Bachoud-Lvi AC, Hantraye P, Remy P. In vivo evidence for the selective subcortical degeneration in Huntington's disease. )] TJ ET BT 26.250 575.214 Td /F1 9.8 Tf [(Neuroimage. 2009 Jul 15;46\(4\):958-66. Epub 2009 Mar 28. PubMed PMID: 19332141.)] TJ ET BT 26.250 555.810 Td /F1 9.8 Tf [(17.)] TJ ET BT 43.553 555.810 Td /F1 9.8 Tf [(Henley SM, Ridgway GR, Scahill RI, Klppel S, Tabrizi SJ, Fox NC, Kassubek J; EHDN Imaging Working Group. Pitfalls in )] TJ ET BT 26.250 543.905 Td /F1 9.8 Tf [(the use of voxel-based morphometry as a biomarker: examples from huntington disease. AJNR Am J Neuroradiol. 2010 )] TJ ET BT 26.250 532.000 Td /F1 9.8 Tf [(Apr;31\(4\):711-9. Epub 2009 Dec 24. PubMed PMID: 20037137.)] TJ ET Q q 15.000 514.619 577.500 262.381 re W n 0.271 0.267 0.267 rg BT 26.250 767.476 Td /F1 9.8 Tf [(B. 1994 Mar;103\(3\):247-54. PubMed PMID: 8019776.)] TJ ET BT 26.250 748.071 Td /F1 9.8 Tf [(12.)] TJ ET BT 43.553 748.071 Td /F1 9.8 Tf [(Wheeler-Kingshott CA, Parker GJ, Symms MR, Hickman SJ, Tofts PS, Miller DH, Barker GJ. ADC mapping of the human )] TJ ET BT 26.250 736.167 Td /F1 9.8 Tf [(optic nerve: increased resolution, coverage, and reliability with CSF-suppressed ZOOM-EPI. Magn Reson Med. 2002 )] TJ ET BT 26.250 724.262 Td /F1 9.8 Tf [(Jan;47\(1\):24-31. PubMed PMID: 11754439.)] TJ ET BT 26.250 704.857 Td /F1 9.8 Tf [(13.)] TJ ET BT 43.553 704.857 Td /F1 9.8 Tf [(Deichmann R, Schwarzbauer C, Turner R. Optimisation of the 3D MDEFT sequence for anatomical brain imaging: technical )] TJ ET BT 26.250 692.952 Td /F1 9.8 Tf [(implications at 1.5 and 3 T. Neuroimage. 2004 Feb;21\(2\):757-67. PubMed PMID: 14980579.)] TJ ET BT 26.250 673.548 Td /F1 9.8 Tf [(14.)] TJ ET BT 43.553 673.548 Td /F1 9.8 Tf [(Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage. 2007 Oct 15;38\(1\):95-113. Epub 2007 Jul 18. )] TJ ET BT 26.250 661.643 Td /F1 9.8 Tf [(PubMed PMID: 17761438.)] TJ ET BT 26.250 642.238 Td /F1 9.8 Tf [(15.)] TJ ET BT 43.553 642.238 Td /F1 9.8 Tf [(Rosas HD, Tuch DS, Hevelone ND, Zaleta AK, Vangel M, Hersch SM, Salat DH. Diffusion tensor imaging in )] TJ ET BT 26.250 630.333 Td /F1 9.8 Tf [(presymptomatic and early Huntington's disease: Selective white matter pathology and its relationship to clinical measures. Mov )] TJ ET BT 26.250 618.429 Td /F1 9.8 Tf [(Disord. 2006 Sep;21\(9\):1317-25. PubMed PMID: 16755582.)] TJ ET BT 26.250 599.024 Td /F1 9.8 Tf [(16.)] TJ ET BT 43.553 599.024 Td /F1 9.8 Tf [(Douaud G, Behrens TE, Poupon C, Cointepas Y, Jbabdi S, Gaura V, Golestani N, Krystkowiak P, Verny C, Damier P, )] TJ ET BT 26.250 587.119 Td /F1 9.8 Tf [(Bachoud-Lvi AC, Hantraye P, Remy P. In vivo evidence for the selective subcortical degeneration in Huntington's disease. )] TJ ET BT 26.250 575.214 Td /F1 9.8 Tf [(Neuroimage. 2009 Jul 15;46\(4\):958-66. Epub 2009 Mar 28. PubMed PMID: 19332141.)] TJ ET BT 26.250 555.810 Td /F1 9.8 Tf [(17.)] TJ ET BT 43.553 555.810 Td /F1 9.8 Tf [(Henley SM, Ridgway GR, Scahill RI, Klppel S, Tabrizi SJ, Fox NC, Kassubek J; EHDN Imaging Working Group. Pitfalls in )] TJ ET BT 26.250 543.905 Td /F1 9.8 Tf [(the use of voxel-based morphometry as a biomarker: examples from huntington disease. AJNR Am J Neuroradiol. 2010 )] TJ ET BT 26.250 532.000 Td /F1 9.8 Tf [(Apr;31\(4\):711-9. Epub 2009 Dec 24. PubMed PMID: 20037137.)] TJ ET Q q 0.000 0.000 0.000 rg BT 291.710 19.825 Td /F1 11.0 Tf [(7)] TJ ET BT 25.000 19.825 Td /F1 11.0 Tf [(PLOS Currents Huntington Disease)] TJ ET Q endstream endobj xref 0 337 0000000000 65535 f 0000000008 00000 n 0000000073 00000 n 0000000119 00000 n 0000001073 00000 n 0000001110 00000 n 0000001380 00000 n 0000001988 00000 n 0000031887 00000 n 0000031994 00000 n 0000032102 00000 n 0000032213 00000 n 0000032326 00000 n 0000032714 00000 n 0000037195 00000 n 0000037322 00000 n 0000037520 00000 n 0000037647 00000 n 0000037845 00000 n 0000037972 00000 n 0000038080 00000 n 0000038207 00000 n 0000038310 00000 n 0000038438 00000 n 0000038540 00000 n 0000038668 00000 n 0000038769 00000 n 0000038897 00000 n 0000039000 00000 n 0000039128 00000 n 0000039231 00000 n 0000039359 00000 n 0000039465 00000 n 0000039593 00000 n 0000039688 00000 n 0000039814 00000 n 0000039909 00000 n 0000040036 00000 n 0000040139 00000 n 0000040267 00000 n 0000040368 00000 n 0000040496 00000 n 0000040595 00000 n 0000040723 00000 n 0000040824 00000 n 0000040952 00000 n 0000040988 00000 n 0000041116 00000 n 0000041152 00000 n 0000041280 00000 n 0000041316 00000 n 0000041444 00000 n 0000041480 00000 n 0000041608 00000 n 0000041644 00000 n 0000041772 00000 n 0000041808 00000 n 0000041936 00000 n 0000041972 00000 n 0000042100 00000 n 0000042136 00000 n 0000042260 00000 n 0000042296 00000 n 0000042423 00000 n 0000042621 00000 n 0000042748 00000 n 0000042946 00000 n 0000043073 00000 n 0000043181 00000 n 0000043308 00000 n 0000043411 00000 n 0000043539 00000 n 0000043641 00000 n 0000043769 00000 n 0000043870 00000 n 0000043998 00000 n 0000044101 00000 n 0000044229 00000 n 0000044332 00000 n 0000044460 00000 n 0000044566 00000 n 0000044694 00000 n 0000044789 00000 n 0000044915 00000 n 0000045010 00000 n 0000045137 00000 n 0000045240 00000 n 0000045368 00000 n 0000045469 00000 n 0000045597 00000 n 0000045696 00000 n 0000045824 00000 n 0000045925 00000 n 0000046053 00000 n 0000046089 00000 n 0000046217 00000 n 0000046253 00000 n 0000046381 00000 n 0000046417 00000 n 0000046545 00000 n 0000046581 00000 n 0000046711 00000 n 0000046748 00000 n 0000046878 00000 n 0000046915 00000 n 0000047045 00000 n 0000047082 00000 n 0000047212 00000 n 0000047249 00000 n 0000047375 00000 n 0000047412 00000 n 0000047541 00000 n 0000047740 00000 n 0000047869 00000 n 0000048068 00000 n 0000048197 00000 n 0000048306 00000 n 0000048435 00000 n 0000048539 00000 n 0000048669 00000 n 0000048772 00000 n 0000048902 00000 n 0000049004 00000 n 0000049134 00000 n 0000049238 00000 n 0000049368 00000 n 0000049472 00000 n 0000049602 00000 n 0000049709 00000 n 0000049839 00000 n 0000049935 00000 n 0000050063 00000 n 0000050159 00000 n 0000050288 00000 n 0000050392 00000 n 0000050522 00000 n 0000050624 00000 n 0000050754 00000 n 0000050854 00000 n 0000050984 00000 n 0000051086 00000 n 0000051216 00000 n 0000051253 00000 n 0000051383 00000 n 0000051420 00000 n 0000051550 00000 n 0000051587 00000 n 0000051717 00000 n 0000051754 00000 n 0000051884 00000 n 0000051921 00000 n 0000052051 00000 n 0000052088 00000 n 0000052218 00000 n 0000052255 00000 n 0000052385 00000 n 0000052422 00000 n 0000052548 00000 n 0000052585 00000 n 0000052808 00000 n 0000097066 00000 n 0000097196 00000 n 0000097233 00000 n 0000097363 00000 n 0000097400 00000 n 0000097530 00000 n 0000097567 00000 n 0000097697 00000 n 0000097734 00000 n 0000097864 00000 n 0000097901 00000 n 0000098031 00000 n 0000098068 00000 n 0000098198 00000 n 0000098235 00000 n 0000098365 00000 n 0000098402 00000 n 0000098532 00000 n 0000098569 00000 n 0000098699 00000 n 0000098736 00000 n 0000098866 00000 n 0000098903 00000 n 0000099033 00000 n 0000099070 00000 n 0000099200 00000 n 0000099237 00000 n 0000099367 00000 n 0000099404 00000 n 0000099534 00000 n 0000099571 00000 n 0000099701 00000 n 0000099738 00000 n 0000099868 00000 n 0000099905 00000 n 0000100035 00000 n 0000100072 00000 n 0000100247 00000 n 0000124681 00000 n 0000125927 00000 n 0000126224 00000 n 0000126629 00000 n 0000126903 00000 n 0000127308 00000 n 0000127582 00000 n 0000128117 00000 n 0000128396 00000 n 0000128972 00000 n 0000129253 00000 n 0000130640 00000 n 0000130940 00000 n 0000131426 00000 n 0000131704 00000 n 0000131834 00000 n 0000131871 00000 n 0000132001 00000 n 0000132038 00000 n 0000132166 00000 n 0000132203 00000 n 0000132331 00000 n 0000132368 00000 n 0000133614 00000 n 0000133911 00000 n 0000134316 00000 n 0000134590 00000 n 0000134995 00000 n 0000135269 00000 n 0000135804 00000 n 0000136083 00000 n 0000136659 00000 n 0000136940 00000 n 0000138327 00000 n 0000138627 00000 n 0000139113 00000 n 0000139391 00000 n 0000139521 00000 n 0000139558 00000 n 0000139688 00000 n 0000139725 00000 n 0000139853 00000 n 0000139890 00000 n 0000140018 00000 n 0000140055 00000 n 0000141301 00000 n 0000141598 00000 n 0000142003 00000 n 0000142277 00000 n 0000142682 00000 n 0000142956 00000 n 0000143491 00000 n 0000143770 00000 n 0000144346 00000 n 0000144627 00000 n 0000146014 00000 n 0000146314 00000 n 0000146800 00000 n 0000147078 00000 n 0000147208 00000 n 0000147245 00000 n 0000147375 00000 n 0000147412 00000 n 0000147540 00000 n 0000147577 00000 n 0000147705 00000 n 0000147742 00000 n 0000147941 00000 n 0000160731 00000 n 0000160860 00000 n 0000160971 00000 n 0000170323 00000 n 0000170452 00000 n 0000170555 00000 n 0000170963 00000 n 0000192500 00000 n 0000192629 00000 n 0000192740 00000 n 0000200635 00000 n 0000200762 00000 n 0000200870 00000 n 0000200998 00000 n 0000201093 00000 n 0000201222 00000 n 0000201333 00000 n 0000201462 00000 n 0000201565 00000 n 0000201973 00000 n 0000223510 00000 n 0000223639 00000 n 0000223750 00000 n 0000223877 00000 n 0000223985 00000 n 0000224113 00000 n 0000224208 00000 n 0000224337 00000 n 0000224448 00000 n 0000224577 00000 n 0000224680 00000 n 0000225088 00000 n 0000246625 00000 n 0000246754 00000 n 0000246865 00000 n 0000246992 00000 n 0000247100 00000 n 0000247228 00000 n 0000247323 00000 n 0000247731 00000 n 0000269268 00000 n 0000269419 00000 n 0000292881 00000 n 0000293010 00000 n 0000293101 00000 n 0000293230 00000 n 0000293336 00000 n 0000305291 00000 n 0000305421 00000 n 0000305458 00000 n 0000305587 00000 n 0000305678 00000 n 0000305807 00000 n 0000305913 00000 n 0000306043 00000 n 0000306080 00000 n 0000306209 00000 n 0000306300 00000 n 0000306429 00000 n 0000306535 00000 n 0000306665 00000 n 0000306702 00000 n 0000306805 00000 n 0000328920 00000 n 0000329050 00000 n 0000329087 00000 n 0000329217 00000 n 0000329254 00000 n 0000329384 00000 n 0000329421 00000 n 0000329488 00000 n trailer << /Size 337 /Root 1 0 R /Info 5 0 R >> startxref 337646 %%EOF