Covariance statistics and network analysis of brain PET imaging studies.

ABSTRACT: The analysis of structural and functional neuroimaging data using graph theory has increasingly become a popular approach for visualising and understanding anatomical and functional relationships between different cerebral areas. In this work we applied a network-based approach for brain PET studies using population-based covariance matrices, with the aim to explore topological tracer kinetic differences in cross-sectional investigations. Simulations, test-retest studies and applications to cross-sectional datasets from three different tracers ([¹⁸F]FDG, [¹⁸F]FDOPA and [¹¹C]SB217045) and more than 400 PET scans were investigated to assess the applicability of the methodology in healthy controls and patients. A validation of statistics, including the assessm

SUBMITTER: Veronese M 

PROVIDER: S-EPMC6385265 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature