4.7 Article

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

Journal

ANNALS OF NEUROLOGY
Volume 83, Issue 4, Pages 842-853

Publisher

WILEY
DOI: 10.1002/ana.25214

Keywords

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Funding

  1. University and University Hospital of Liege
  2. Belgian National Funds for Scientific Research (FRS-FNRS)
  3. Human Brain Project [EU-H2020-fetflagship-hbp-sga1-ga720270]
  4. Luminous project [EU-H2020-fetopen-ga686764]
  5. French Speaking Community Concerted Research Action [ARC - 06/11 - 340]
  6. NSERC discovery grant
  7. IAP research network of the Belgian Government (Belgian Science Policy) [P7/06]
  8. European Commission
  9. James McDonnell Foundation
  10. Mind Science Foundation
  11. BIAL foundation
  12. European Space Agency (ESA)
  13. Public Utility Foundation Universitee Europeenne duTravail

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ObjectiveThe 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. MethodsStructural 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. ResultsPatients 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. InterpretationBrain 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

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