The cerebral cortex rapidly develops its folding during the second and third trimester of pregnancy. In preterm birth, this growth might be disrupted and influence neurodevelopment. The aim of this work is to extract quantitative biomarkers describing the cortex and evaluate them on a set of preterm infants without brain pathology.
For this study, a set of 19 preterm - but otherwise healthy - infants scanned coronally with 3T MRI at the postmenstrual age of 30 weeks were selected. In ten patients (test set), the gray and white matter were manually annotated by an expert on the T2-weighted scans. Manual segmentations were used to extract cortical volume, surface area, thickness, and curvature using voxel-based methods. To compute these biomarkers per region in every patient, a template brain image has been generated by iterative registration and averaging of the scans of the remaining nine patients. This template has been manually divided in eight regions, and is transformed to every test image using elastic registration.
In the results, gray and white matter volumes and cortical surface area appear symmetric between hemispheres, but small regional differences are visible. Cortical thickness seems slightly higher in the right parietal lobe than in other regions. The parietal lobes exhibit a higher global curvature, indicating more complex folding compared to other regions.
The proposed approach can potentially - together with an automatic segmentation algorithm - be applied as a tool to assist in early diagnosis of abnormalities and prediction of the development of the cognitive abilities of these children.