Mapping covariance in brain FDG uptake to structural connectivity
Igor Yakushev, Isabelle Ripp, Min Wang, Alexandre Savio, Michael Schütte, Aldana Lizarraga, Borjana Bogdanović, Janine Diehl‐Schmid, Dennis M. Hedderich, Timo Grimmer, Kuangyu Shi
Abstract
Abstract Purpose Inter-subject covariance of regional 18F-fluorodeoxyglucose (FDG) PET measures (FDG cov ) as proxy of brain connectivity has been gaining an increasing acceptance in the community. Yet, it is still unclear to what extent FDG cov is underlied by actual structural connectivity via white matter fiber tracts. In this study, we quantified the degree of spatial overlap between FDG cov and structural connectivity networks. Methods We retrospectively analyzed neuroimaging data from 303 subjects, both patients with suspected neurodegenerative disorders and healthy individuals. For each subject, structural magnetic resonance, diffusion tensor imaging, and FDG-PET data were available. The images were spatially normalized to a standard space and segmented into 62 anatomical regions using a probabilistic atlas. Sparse inverse covariance estimation was employed to estimate FDG cov . Structural connectivity was measured by streamline tractography through fiber assignment by continuous tracking. Results For the whole brain, 55% of detected connections were found to be convergent, i.e., present in both FDG cov and structural networks. This metric for random networks was significantly lower, i.e., 12%. Convergent were 80% of intralobe connections and only 30% of interhemispheric interlobe connections. Conclusion Structural connectivity via white matter fiber tracts is a relevant substrate of FDG cov , underlying around a half of connections at the whole brain level. Short-range white matter tracts appear to be a major substrate of intralobe FDG cov connections.