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Abstract #2586

Optimization of ROI transposition for atlas-based analysis of MRI quantitative metrics in neuroimaging studies

Mustafa Okan Irfanoglu 1,2 , Amritha Nayak 1,2 , Lindsay Walker 3 , Carlo Pierpaoli 1 , and The Brain Development Cooperative Group 4

1 NICHD, NIH, Bethesda, MD, United States, 2 CNRM, USUHS, Bethesda, MD, United States, 3 Brown University, RI, United States, 4, MD, United States

In analyzing quantitative MRI metrics in large population neuroimaging studies, it is convenient to define ROIs on a representative atlas and then transpose the ROIs onto individual subject space and extract values. Here we assess the contribution to overall variance that different ROI transformation methods introduce on the analysis of developmental trajectories of the diffusion MRI pediatric neuroimaging project, a large database of more than 400 subjects age 0-20. We find that the contribution to overall variance varies significantly with various methods and we propose a novel strategy that is more robust than previous approaches.

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