“Joint analysis of area and thickness using NPC as a replacement for the analysis of volume of the cerebral cortex”

Hosted by Mallinckrodt Institute of Radiology’s Computational Imaging Laboratories (CIL)

Abstract: Cortical surface area is an increasingly used brain morphology metric that is ontogenetically and phylogenetically distinct from cortical thickness and offers a separate index of neurodevelopment and disease. I will discuss existing methods to assess cortical area, and show that the method implemented in FreeSurfer corresponds closely to the exact, but computationally more demanding, pycnophylactic method, provided that smoothing is applied. Thus, data produced by this method can be interpreted as estimates of cortical surface area itself, as opposed to areal expansion as previously reported. In addition, focusing on the joint analysis of thickness and area, I will show a comparison of an analytic method for measuring cortical volume to the permutation-based Non-Parametric Combination (NPC). Using these methods to analyze area, thickness and volume in young adults born preterm with very low birth weight, I will show that NPC analysis is a more sensitive option than volume for studying joint effects on area and thickness, giving equal weight to variation in both of these two morphological features.

Reference: Winkler AM, Greve DN, Bjuland KJ, et al. Joint Analysis of Cortical Area and Thickness as a Replacement for the Analysis of the Volume of the Cerebral Cortex. Cerebral Cortex 2018;28(2):738–49. https://doi.org/10.1093/cercor/bhx308

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