• Dana Cobzas, Hongfu Sun, Andrew J Walsh, R Marc Lebel, Gregg Blevins, and Alan H Wilman.
• Biomedical Engineering, University of Alberta, Edmonton, Canada.
• J Magn Reson Imaging. 2015 Dec 1; 42 (6): 1601-10.

PurposeTo investigate subcortical gray matter segmentation using transverse relaxation rate (R2 *) and quantitative susceptibility mapping (QSM) and apply it to voxel-based analysis in multiple sclerosis (MS).Materials And MethodsVoxel-based variation in R2 * and QSM within deep gray matter was examined and compared to standard whole-structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T1 -weighted images. Segmentation accuracy and scan-rescan reliability were tested.ResultsWhen considering only significant regions as returned by the multivariate voxel-based analysis, increased R2 * and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R2 *, regional analysis yielded at least 66-fold improved P-value significance in all nuclei over standard whole-structure analysis, while for QSM only thalamus benefited, with 5-fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high-contrast QSM into the atlas. Voxel-based reliability was highest for QSM (<1% variation).ConclusionAutomatic segmentation of iron-rich deep gray matter can be improved by incorporating QSM. Voxel-based evaluation yielded increased R2 * and QSM in MS subjects in all four nuclei studied with R2 *, benefiting the most from localized analysis over whole-structure measures.© 2015 Wiley Periodicals, Inc.

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