Explaining recovery from coma with multimodal neuroimaging.
J Neurol
; 271(9): 6274-6288, 2024 Sep.
Article
em En
| MEDLINE
| ID: mdl-39090230
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 (18F-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 R2 = 0.84, p = 0.003) or functional connectivity biomarker (adjusted R2 = 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 R2 = 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.
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Base de dados:
MEDLINE
Assunto principal:
Coma
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Recuperação de Função Fisiológica
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Imagem Multimodal
Limite:
Adolescent
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Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article