Mapping covariance in brain FDG uptake to structural connectivity.

Purpose: Inter-subject covariance of regional 18F-fluorodeoxyglucose (FDG) PET measures (FDGcov) as proxy of brain connectivity has been gaining an increasing acceptance in the community. Yet, it is still unclear to what extent FDGcov is underlied by actual structural connectivity via white matter f...

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Publicado en:European Journal of Nuclear Medicine & Molecular Imaging Vol. 49; no. 4; pp. 1288 - 1298
Autores principales: Yakushev, Igor, Ripp, Isabelle, Wang, Min, Savio, Alex, Schutte, Michael, Lizarraga, Aldana, Bogdanovic, Borjana, Diehl-Schmid, Janine, Hedderich, Dennis M., Grimmer, Timo, Shi, Kuangyu
Formato: Journal Article
Publicado: Springer Nature Mar2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2022
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      pub: Springer Nature
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        10.1007/s00259-021-05590-y
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        atl: Mapping covariance in brain FDG uptake to structural connectivity.
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          Yakushev, Igor
          Ripp, Isabelle
          Wang, Min
          Savio, Alex
          Schutte, Michael
          Lizarraga, Aldana
          Bogdanovic, Borjana
          Diehl-Schmid, Janine
          Hedderich, Dennis M.
          Grimmer, Timo
          Shi, Kuangyu
        affil: Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
      sug:
      ab: Purpose: Inter-subject covariance of regional 18F-fluorodeoxyglucose (FDG) PET measures (FDGcov) as proxy of brain connectivity has been gaining an increasing acceptance in the community. Yet, it is still unclear to what extent FDGcov is underlied by actual structural connectivity via white matter fiber tracts. In this study, we quantified the degree of spatial overlap between FDGcov 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 FDGcov. 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 FDGcov 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 FDGcov, underlying around a half of connections at the whole brain level. Short-range white matter tracts appear to be a major substrate of intralobe FDGcov connections.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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