Distributed changes of the functional connectome in patients with glioblastoma
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s41598-020-74726-1.pdf
Description
Published version
Size
3.48 MB
Format
Adobe PDF
Checksum (MD5)
6fc1abe9fc42faab00bed6a66c03c7be
Author(s)
Golland, Polina
Langs, Georg
Date Issued
October 2020
Journal
Scientific Reports
Publisher
Springer Science and Business Media LLC
Citation
Nenning, Karl‑Heinz et al. “Distributed changes of the functional connectome in patients with glioblastoma.” Scientific Reports, 10, 1 (October 2020): 18312 © 2020 The Author(s)
Version
Final published version
Abstract
Glioblastoma might have widespread effects on the neural organization and cognitive function, and even focal lesions may be associated with distributed functional alterations. However, functional changes do not necessarily follow obvious anatomical patterns and the current understanding of this interrelation is limited. In this study, we used resting-state functional magnetic resonance imaging to evaluate changes in global functional connectivity patterns in 15 patients with glioblastoma. For six patients we followed longitudinal trajectories of their functional connectome and structural tumour evolution using bi-monthly follow-up scans throughout treatment and disease progression. In all patients, unilateral tumour lesions were associated with inter-hemispherically symmetric network alterations, and functional proximity of tumour location was stronger linked to distributed network deterioration than anatomical distance. In the longitudinal subcohort of six patients, we observed patterns of network alterations with initial transient deterioration followed by recovery at first follow-up, and local network deterioration to precede structural tumour recurrence by two months. In summary, the impact of focal glioblastoma lesions on the functional connectome is global and linked to functional proximity rather than anatomical distance to tumour regions. Our findings further suggest a relevance for functional network trajectories as a possible means supporting early detection of tumour recurrence.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/s41598-020-74726-1
