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Mapping covariance in brain FDG uptake to structural connectivity
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 matt...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921091/ https://www.ncbi.nlm.nih.gov/pubmed/34677627 http://dx.doi.org/10.1007/s00259-021-05590-y |
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author | Yakushev, Igor Ripp, Isabelle Wang, Min Savio, Alex Schutte, Michael Lizarraga, Aldana Bogdanovic, Borjana Diehl-Schmid, Janine Hedderich, Dennis M. Grimmer, Timo Shi, Kuangyu |
author_facet | Yakushev, Igor Ripp, Isabelle Wang, Min Savio, Alex Schutte, Michael Lizarraga, Aldana Bogdanovic, Borjana Diehl-Schmid, Janine Hedderich, Dennis M. Grimmer, Timo Shi, Kuangyu |
author_sort | Yakushev, Igor |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-021-05590-y. |
format | Online Article Text |
id | pubmed-8921091 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-89210912022-03-17 Mapping covariance in brain FDG uptake to structural connectivity Yakushev, Igor Ripp, Isabelle Wang, Min Savio, Alex Schutte, Michael Lizarraga, Aldana Bogdanovic, Borjana Diehl-Schmid, Janine Hedderich, Dennis M. Grimmer, Timo Shi, Kuangyu Eur J Nucl Med Mol Imaging Original Article 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-021-05590-y. Springer Berlin Heidelberg 2021-10-22 2022 /pmc/articles/PMC8921091/ /pubmed/34677627 http://dx.doi.org/10.1007/s00259-021-05590-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Yakushev, Igor Ripp, Isabelle Wang, Min Savio, Alex Schutte, Michael Lizarraga, Aldana Bogdanovic, Borjana Diehl-Schmid, Janine Hedderich, Dennis M. Grimmer, Timo Shi, Kuangyu Mapping covariance in brain FDG uptake to structural connectivity |
title | Mapping covariance in brain FDG uptake to structural connectivity |
title_full | Mapping covariance in brain FDG uptake to structural connectivity |
title_fullStr | Mapping covariance in brain FDG uptake to structural connectivity |
title_full_unstemmed | Mapping covariance in brain FDG uptake to structural connectivity |
title_short | Mapping covariance in brain FDG uptake to structural connectivity |
title_sort | mapping covariance in brain fdg uptake to structural connectivity |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921091/ https://www.ncbi.nlm.nih.gov/pubmed/34677627 http://dx.doi.org/10.1007/s00259-021-05590-y |
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