Label-fusion-segmentation and deformation-based shape analysis of deep gray matter in multiple sclerosis: the impact of thalamic subnuclei on disability

基于标签融合分割和形变的多发性硬化症深部灰质形状分析:丘脑亚核对残疾的影响

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Abstract

Deep gray matter (DGM) atrophy has been reported in patients with multiple sclerosis (MS) already at early stages of the disease and progresses throughout the disease course. We studied DGM volume and shape and their relation to disability in a large cohort of clinically well-described MS patients using new subcortical segmentation methods and shape analysis. Structural 3D magnetic resonance images were acquired at 1.5 T in 118 patients with relapsing remitting MS. Subcortical structures were segmented using a multiatlas technique that relies on the generation of an automatically generated template library. To localize focal morphological changes, shape analysis was performed by estimating the vertex-wise displacements each subject must undergo to deform to a template. Multiple linear regression analysis showed that the volume of specific thalamic nuclei (the ventral nuclear complex) together with normalized gray matter volume explains a relatively large proportion of expanded disability status scale (EDSS) variability. The deformation-based displacement analysis confirmed the relation between thalamic shape and EDSS scores. Furthermore, white matter lesion volume was found to relate to the shape of all subcortical structures. This novel method for the analysis of subcortical volume and shape allows depicting specific contributions of DGM abnormalities to neurological deficits in MS patients. The results stress the importance of ventral thalamic nuclei in this respect.

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