Diffusion-Informed Joint Segmentation Enhances Detection of Thalamic Atrophy in Parkinson’s Disease

作者：Gozde Kizilates-Evin, Ani Kıçık, Emel Erdoğdu, Dilek Betül Arslan, Sevim Cengiz, Başar Bılgıç, Haşmet Ayhan HANAĞASI, Esin Öztürk-Işık, Tamer Demıralp, Ali Bayram · 发表于：Brain Topography · 年份：2026 · DOI：10.1007/s10548-026-01226-2 · 研究领域：Parkinson's Disease Mechanisms and Treatments、Neurological disorders and treatments、Advanced Neuroimaging Techniques and Applications

The thalamus is a critical subcortical hub that relays sensorimotor information and regulates higher-order cognitive processes. Accurate delineation of thalamic nuclei is essential for elucidating disease mechanisms and tracking clinical progression. In this study, we compared two segmentation approaches implemented in FreeSurfer: the conventional structural method and a joint framework that integrates diffusion tensor imaging. Magnetic resonance imaging (MRI) data from 24 healthy controls (HC), 27 patients with cognitively normal Parkinson's disease (PD-CN), and 33 Parkinson's disease patients with mild cognitive impairment (PD-MCI) were analyzed. Segmentation methods were compared in HC to assess their effect on volume estimates. Group comparisons were then conducted separately for each method to evaluate sensitivity in detecting disease-related volumetric differences. Finally, nuclei with significant group effects in joint segmentation were tested for associations with Addenbrooke's Cognitive Examination-Revised (ACE-R) scores. Joint segmentation yielded systematically lower thalamic volume estimates than the structural method, with significant differences across hemispheres and nuclei in HC. Group-wise analyses revealed that joint segmentation, but not structural segmentation, detected significant atrophy in the right thalamus of PD-MCI patients. At the nuclei group level, joint segmentation showed greater sensitivity, identifying bilateral anterolateral and posterior nuc...