Cortical thickness estimation in individuals with cerebral small vessel disease, focal atrophy, and chronic stroke lesions.

Background: Regional changes to cortical thickness in individuals with neurodegenerative and cerebrovascular diseases can be estimated using specialised neuroimaging software. However, the presence of cerebral small vessel disease, focal atrophy, and cortico-subcortical stroke lesions, pose significant challenges that increase the likelihood of misclassification errors and segmentation failures. Purpose: The main goal of this study was to examine a correction procedure developed for enhancing FreeSurfer9s cortical thickness estimation tool, particularly when applied to the most challenging MRI obtained from participants with chronic stroke and cerebrovascular disease, with varying degrees of neurovascular lesions and brain atrophy. Methods: In 155 cerebrovascular disease participants enrolled in the Ontario Neurodegenerative Disease Research Initiative (ONDRI), FreeSurfer outputs were compared between a fully automated, unmodified procedure and a corrected procedure that accounted for potential sources of error due to atrophy and neurovascular lesions. Quality control (QC) measures were obtained from both procedures. Association between cortical thickness and global cognitive status as assessed by the Montreal Cognitive Assessment (MoCA) score was also investigated from both procedures. Results: Corrected procedures increased 9Acceptable9 QC ratings from 18% to 76% for the cortical ribbon and from 38% to 92% for tissue segmentation. Corrected procedures reduced 9Fail9 ratings from 11% to 0% for the cortical ribbon and 62% to 8% for tissue segmentation. FreeSurfer-based segmentation of T1-weighted white matter hypointensities were significantly greater in the corrected procedure (5.8mL vs. 15.9mL, p