期刊
MEDICAL IMAGE ANALYSIS
卷 42, 期 -, 页码 14-25出版社
ELSEVIER
DOI: 10.1016/j.media.2017.07.001
关键词
Gyral net; Cortical folding; MRI; Autism
类别
资金
- National Institutes of Health [DA033393, AG042599, EB006733, MH100217, MH107815, MH108914]
- National Science Foundation [IIS-1149260, CBET-1302089, BCS-1439051, DBI-1564736]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1149260] Funding Source: National Science Foundation
One distinct feature of the cerebral cortex is its convex (gyri) and concave (sulci) folding patterns. Due to the remarkable complexity and variability of gyralisulcal shapes, it has been challenging to quantitatively model their organization patterns. Inspired by the observation that the lines of gyral crests can form a connected graph on each brain hemisphere, we propose a new representation of cortical gyri/sulci organization pattern - gyral net, which models cortical architecture from a graph perspective, starting with nodes and edges obtained from the reconstructed cortical surfaces. A novel computational framework is developed to efficiently and automatically construct gyral nets from surface meshes, and four measurements are devised to quantify the folding patterns. Using an MRI dataset for autism study as a test bed, we identified reduced local connectivity cost and increased curviness of gyral net bilaterally on the parietal lobe, occipital lobe, and temporal lobe in autistic patients. Additionally, we found that the cortical thickness and the gyral straightness of gyral joints are higher than the rest of gyral crest regions. The proposed representation offers a new tool for a comprehensive and reliable characterization of the cortical folding organization. This novel computational framework will enable large-scale analyses of cortical folding patterns in the future. (C) 2017 Elsevier B.V. All rights reserved.
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