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Connectomic profile and clinical phenotype in newly diagnosed glioma patients.

Authors :
Derks J
Dirkson AR
de Witt Hamer PC
van Geest Q
Hulst HE
Barkhof F
Pouwels PJ
Geurts JJ
Reijneveld JC
Douw L
Source :
NeuroImage. Clinical [Neuroimage Clin] 2017 Jan 16; Vol. 14, pp. 87-96. Date of Electronic Publication: 2017 Jan 16 (Print Publication: 2017).
Publication Year :
2017

Abstract

Gliomas are primary brain tumors, originating from the glial cells in the brain. In contrast to the more traditional view of glioma as a localized disease, it is becoming clear that global brain functioning is impacted, even with respect to functional communication between brain regions remote from the tumor itself. However, a thorough investigation of glioma-related functional connectomic profiles is lacking. Therefore, we constructed functional brain networks using functional MR scans of 71 glioma patients and 19 matched healthy controls using the automated anatomical labelling (AAL) atlas and interregional Pearson correlation coefficients. The frequency distributions across connectivity values were calculated to depict overall connectomic profiles and quantitative features of these distributions (full-width half maximum (FWHM), peak position, peak height) were calculated. Next, we investigated the spatial distribution of the connectomic profile. We defined hub locations based on the literature and determined connectivity (1) between hubs, (2) between hubs and non-hubs, and (3) between non-hubs. Results show that patients had broader and flatter connectivity distributions compared to controls. Spatially, glioma patients particularly showed increased connectivity between non-hubs and hubs. Furthermore, connectivity distributions and hub-non-hub connectivity differed within the patient group according to tumor grade, while relating to Karnofsky performance status and progression-free survival. In conclusion, newly diagnosed glioma patients have globally altered functional connectomic profiles, which mainly affect hub connectivity and relate to clinical phenotypes. These findings underscore the promise of using connectomics as a future biomarker in this patient population.

Details

Language :
English
ISSN :
2213-1582
Volume :
14
Database :
MEDLINE
Journal :
NeuroImage. Clinical
Publication Type :
Academic Journal
Accession number :
28154795
Full Text :
https://doi.org/10.1016/j.nicl.2017.01.007