Explaining recovery from coma with multimodal neuroimaging.

Details

Serval ID
serval:BIB_A3FE91993F48
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Explaining recovery from coma with multimodal neuroimaging.
Journal
Journal of neurology
Author(s)
Pozeg P. (co-first), Jöhr J. (co-first), Prior J.O., Diserens K. (co-last), Dunet V. (co-last)
ISSN
1432-1459 (Electronic)
ISSN-L
0340-5354
Publication state
Published
Issued date
09/2024
Peer-reviewed
Oui
Volume
271
Number
9
Pages
6274-6288
Language
english
Notes
Publication types: Journal Article ; Observational Study
Publication Status: ppublish
Abstract
The aim of this prospective, observational cohort study was to investigate and assess diverse neuroimaging biomarkers to predict patients' neurological recovery after coma. 32 patients (18-76 years, M = 44.8, SD = 17.7) with disorders of consciousness participated in the study. Multimodal neuroimaging data acquired during the patient's hospitalization were used to derive cortical glucose metabolism ( <sup>18</sup> F-fluorodeoxyglucose positron emission tomography/computed tomography), and structural (diffusion-weighted imaging) and functional connectivity (resting-state functional MRI) indices. The recovery outcome was defined as a continuous composite score constructed from a multivariate neurobehavioral recovery assessment administered upon the discharge from the hospital. Fractional anisotropy-based white matter integrity in the anterior forebrain mesocircuit (r = 0.72, p < .001, 95% CI: 0.87, 0.45), and the functional connectivity between the antagonistic default mode and dorsal attention resting-state networks (r = - 0.74, p < 0.001, 95% CI: - 0.46, - 0.88) strongly correlated with the recovery outcome. The association between the posterior glucose metabolism and the recovery outcome was moderate (r = 0.38, p = 0.040, 95% CI: 0.66, 0.02). Structural (adjusted R <sup>2</sup> = 0.84, p = 0.003) or functional connectivity biomarker (adjusted R <sup>2</sup> = 0.85, p = 0.001), but not their combination, significantly improved the model fit to predict the recovery compared solely to bedside neurobehavioral evaluation (adjusted R <sup>2</sup> = 0.75). The present study elucidates an important role of specific MRI-derived structural and functional connectivity biomarkers in diagnosis and prognosis of recovery after coma and has implications for clinical care of patients with severe brain injury.
Keywords
Humans, Middle Aged, Coma/diagnostic imaging, Coma/physiopathology, Adult, Male, Female, Aged, Recovery of Function/physiology, Adolescent, Multimodal Imaging, Young Adult, Neuroimaging/methods, Magnetic Resonance Imaging, Prospective Studies, Brain/diagnostic imaging, Brain/physiopathology, Cohort Studies, Positron Emission Tomography Computed Tomography, Diffusion Magnetic Resonance Imaging, Brain injury, DWI, Disorders of consciousness, PET, Recovery, fMRI
Pubmed
Web of science
Open Access
Yes
Create date
07/08/2024 9:08
Last modification date
27/09/2024 16:45
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