Gray Matter Surface based Spatial Statistics in Neuroimaging Studies
Citation: Gray Matter Surface based Spatial Statistics in Neuroimaging Studies. Authors: Prasanna Parvatheni, Baxter P. Rogers, Yuankai Huo, Kurt G. Schilling, Allison E. Hainline, Adam W. Anderson, Neil D. Woodward, Bennett A. Landman. Frontiers in Biomedical Imaging Science VI. May 2017. Abstract.
In this study, we propose gray matter surface based spatial statistics (GS-BSS) method, to perform statistical analysis using gray matter (GM) surfaces. Structural image is registered to MNI space and segmented into gray matter surfaces using established methods of registration and segmentation techniques. GM surfaces and microstructure based imaging features from neurite orientation dispersion and density imaging (NODDI) are transferred to standard space. All the surfaces are non-linearly registered to a common target surface using diffeomorphic spectral matching on cortical surfaces and imaging features are then projected onto common surface. Significant results confirming the microstructural changes are presented and compared against an existing gray matter spatial statistics (GBSS) method. GS-BSS method yielded more highly probable gray matter voxels in cortical region and showed higher sensitivity to group differences between healthy and psychosis population in previously known regions.