Regional brain volumetry and brain function in severely brain‐injured patients

• Published in: Annals of neurology Vol. 83; no. 4; pp. 842 - 853
• Main Authors: Annen, Jitka, Frasso, Gianluca, Crone, Julia Sophia, Heine, Lizette, Di Perri, Carol, Martial, Charlotte, Cassol, Helena, Demertzi, Athena, Naccache, Lionel, Laureys, Steven
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.04.2018
• Subjects: Adult; Analysis of Variance; Atrophy; Atrophy - etiology; Brain; Brain - diagnostic imaging; Brain Injuries - complications; Brain Injuries - diagnostic imaging; Classification; Confidence intervals; Consciousness; Cortex; Emission analysis; Female; Fluorodeoxyglucose F18 - metabolism; Glasgow Outcome Scale; Gray Matter - diagnostic imaging; Humans; Image Processing, Computer-Assisted; Injuries; Magnetic Resonance Imaging; Male; Medical imaging; Middle Aged; Neural networks; Neuroimaging; Neurology; Patients; Persistent Vegetative State - diagnostic imaging; Persistent Vegetative State - etiology; Positron emission; Positron emission tomography; Retrospective Studies; ROC Curve; Sleep and wakefulness; Substantia alba; Substantia grisea; Wakefulness; White Matter - diagnostic imaging; Young Adult
• ISSN: 0364-5134; 1531-8249; 1531-8249
• DOI: 10.1002/ana.25214

Objective The relationship between residual brain tissue in patients with disorders of consciousness (DOC) and the clinical condition is unclear. This observational study aimed to quantify gray (GM) and white matter (WM) atrophy in states of (altered) consciousness. Methods Structural T1‐weighted magnetic resonance images were processed for 102 severely brain‐injured and 52 healthy subjects. Regional brain volume was quantified for 158 (sub)cortical regions using Freesurfer. The relationship between regional brain volume and clinical characteristics of patients with DOC and conscious brain‐injured patients was assessed using a linear mixed‐effects model. Classification of patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) using regional volumetric information was performed and compared to classification using cerebral glucose uptake from fluorodeoxyglucose positron emission tomography. For validation, the T1‐based classifier was tested on independent datasets. Results Patients were characterized by smaller regional brain volumes than healthy subjects. Atrophy occurred faster in UWS compared to MCS (GM) and conscious (GM and WM) patients. Classification was successful (misclassification with leave‐one‐out cross‐validation between 2% and 13%) and generalized to the independent data set with an area under the receiver operator curve of 79% (95% confidence interval [CI; 67–91.5]) for GM and 70% (95% CI [55.6–85.4]) for WM. Interpretation Brain volumetry at the single‐subject level reveals that regions in the default mode network and subcortical gray matter regions, as well as white matter regions involved in long range connectivity, are most important to distinguish levels of consciousness. Our findings suggest that changes of brain structure provide information in addition to the assessment of functional neuroimaging and thus should be evaluated as well. Ann Neurol 2018;83:842–853