Frontiers in NeuroscienceNeurosciencePeer-reviewed journal article
Cortical thickness estimation in individuals with cerebral small vessel disease, focal atrophy, and chronic stroke lesions.
Miracle OzzoudeiD, Joel RamireziD, Pradeep Reddy RaamanaiD, Melissa F. Holmes, Kirstin Walker, Christopher J.M. ScottiD, Maged GoubraniD, Donna KwaniD, Maria Carmela TartagliaiD, Derek BeatoniD, Gustavo SaposnikiD, Ayman HassaniD, Jane M. Lawrence‐DewariD, Dar D DowlatshahiiD, Stephen C. StrotheriD, Sean Symons, Robert BarthaiD, Richard H. SwartziD, Sandra E. BlackiD, on behalf of the ONDRI Investigators
- Citations
- 21
- FWCI
- 1.26
- Field percentile
- top 20%
Abstract
BackgroundRegional 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. PurposeThe main goal of this study was to examine a correction procedure developed for enhancing FreeSurfers 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. MethodsIn 155 cerebrovascular disease patients 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. ResultsCorrected procedures increased Acceptable QC ratings from 18% to 76% for the cortical ribbon and from 38% to 92% for tissue segmentation. Corrected procedures reduced Fail 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<0.001). The unmodified procedure yielded no significant associations with global cognitive status, whereas the corrected procedure yielded positive associations between MoCA total score and clusters of cortical thickness in the left superior parietal (p=0.018) and left insula (p=0.04) regions. Further analyses with the corrected cortical thickness results and MoCA subscores showed a positive association between left superior parietal cortical thickness and Attention (p<0.001). ConclusionsThese findings suggest that correction procedures that account for brain atrophy and neurovascular lesions can significantly improve FreeSurfers segmentation results, reduce failure rates, and potentially increase sensitivity to examine brain-behaviour relationships. Future work will examine relationships between cortical thickness, cerebral small vessel disease, and neurodegenerative disease in the ONDRI study.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Using Outliers in Freesurfer Segmentation Statistics to Identify Cortical Reconstruction Errors in Structural Scans
Abigail B. Waters, Ryan A. Mace, … David A. Gansler·Brain Imaging and BehaviorPeer-reviewed·Aug 25, 2018
- Optimizing the Accuracy of Cortical Volumetric Analysis in Traumatic Brain Injury
Bram R. Diamond, Christine L. Mac Donald, … Brian L. Edlow·MethodsXPeer-reviewed·Jan 1, 2020
- Vessel Density Mapping of Cerebral Small Vessels on 3D High Resolution Black Blood MRI
Mona Sharifi Sarabi, Samantha J Ma, … Yonggang Shi·NeuroImagePeer-reviewed·Jan 11, 2024
- Beware of White Matter Hyperintensities Causing Systematic Errors in Grey Matter Segmentations!
Mahsa Dadar, Olivier Potvin, … Alzheimer’s Disease Neuroimaging Initiative·Human Brain MappingPeer-reviewed·Mar 30, 2021
- Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer - ASEG and SAMSEG
Donatas Sederevičius, Dídac Vidal-piñeiro A, … for the Alzheimers Disease Neuroimaging Initiative·NeuroImagePeer-reviewed·May 1, 2021
- Automated quantification of small vessel disease brain changes on MRI predicts cognitive and functional decline
Hanna Jokinen, Juha R. Koikkalainen, … Timo Erkinjuntti·StrokePeer-reviewed·Nov 8, 2019