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PurposeTo determine the precision and accuracy of an automated method for segmenting white matter hyperintensities (WMH) on fast fluid-attenuated inversion-recovery (FLAIR) images in elderly brains at 3T.Materials and MethodsFLAIR images from 18 individuals (60–82 years, 9 females) with WMH burdens ranging from 1–80 cm3 were used. The protocol included the removal of clearly hyperintense voxels; two-class fuzzy C-means clustering (FCM); and thresholding to segment probable WMH. Two false-positive minimization (FPM) methods using white matter templates were tested. Precision was assessed by adding synthetic hyperintense voxels to brain slices. Accuracy was validated by comparing automatic and manual segmentations. Whole-brain, voxel-wise metrics of similarity, under- and overestimation were used to evaluate both precision and accuracy.ResultsPrecision was high, as the lowest accuracy in the synthetic datasets was 93%. Both FPM strategies successfully improved overall accuracy. Whole-brain accuracy for the FCM segmentation alone ranged from 45%–81%, which improved to 75%–85% using the FPM strategies.ConclusionThe method was accurate across the range of WMH burden typically seen in the elderly. Accuracy levels achieved or exceeded those of other approaches using multispectral and/or more sophisticated pattern recognition methods. J. Magn. Reson. Imaging 2010;31:1311–1322. © 2010 Wiley-Liss, Inc.

Background and Purpose Post-stroke cognitive impairment (PSCI) is typified by prominent deficits in processing speed and executive function. However, the underlying neuroanatomical substrates of executive deficits are not well understood and further elucidation is needed. There may be utility in fractionating executive functions to delineate neural substrates. Methods One test amenable to fine delineation is the Trail Making Test (TMT), which emphasizes processing speed (TMT-A) and set-shifting (TMT-B-A difference, proportion, quotient scores and TMT-B set-shifting errors). The TMT was administered to two overt ischemic stroke cohorts from a multinational study: (i) a chronic stroke cohort (N=61) and (ii) an acute-sub-acute stroke cohort (N=45). Volumetric quantification of ischemic stroke and White Matter HyperIntensities (WMH) was done on MRI, along with ratings of involvement of cholinergic projections, using the previously published Cholinergic Hyperintensities Projections Scale (CHIPS). Damage to the superior longitudinal fasciculus (SLF), which co-localizes with some cholinergic projections, was also documented. Results Multiple linear regression analyses were completed. While larger infarcts (β=0.37, p<0.0001) were associated with slower processing speed, CHIPS severity (β=0.39, p<0.0001) was associated with all metrics of set shifting. Left SLF damage, however, was only associated with the difference score (β=0.17, p=0.03). These findings were replicated in both cohorts. Patients with ≥2 TMT-B set shifting errors also had greater CHIPS severity. Conclusions In this multinational stroke cohort study, damage to lateral cholinergic pathways and the SLF emerged as significant neuroanatomical correlates for executive deficits in set shifting.