Deep white matter MRI predicts outcomes in coma of various etiologies: a cohort study.
| Title: | Deep white matter MRI predicts outcomes in coma of various etiologies: a cohort study. |
|---|---|
| Authors: | Puybasset L; APHP, Hôpital Pitié-Salpêtrière, Neurosurgical Intensive Care Unit, Sorbonne Université, Paris, France. louis.puybasset@aphp.fr.; CNRS, INSERM, Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, Paris, France. louis.puybasset@aphp.fr.; Department of Anesthesiology and Intensive Care, Groupe Hospitalier Pitié-Salpêtrière, 47-83 Boulevard de l'Hôpital, Paris, 75013, France. louis.puybasset@aphp.fr.; Siméone P; CNRS, INSERM, Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, Paris, France.; Department of Anesthesiology and Intensive Care, APHM, Aix-Marseille Université, CHU Timone, Marseille, France.; CNRS, Inst Neurosci Timone, Aix Marseille Université, Marseille, France.; Grange M; CNRS, INSERM, Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, Paris, France.; Cassereau D; CNRS, INSERM, Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, Paris, France.; Galanaud D; CNRS, INSERM, Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, Paris, France.; Department of Neuroradiology, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France.; Bernard R; APHP, Hôpital Pitié-Salpêtrière, Neurosurgical Intensive Care Unit, Sorbonne Université, Paris, France.; Velly L; Department of Anesthesiology and Intensive Care, APHM, Aix-Marseille Université, CHU Timone, Marseille, France.; CNRS, Inst Neurosci Timone, Aix Marseille Université, Marseille, France.; Perlbarg V; BrainTale SAS, Strasbourg, France.; Capdeville C; APHP, Hôpital Pitié-Salpêtrière, Neurosurgical Intensive Care Unit, Sorbonne Université, Paris, France.; Battisti V; APHP, Hôpital Pitié-Salpêtrière, Neurosurgical Intensive Care Unit, Sorbonne Université, Paris, France.; Abdennour L; APHP, Hôpital Pitié-Salpêtrière, Neurosurgical Intensive Care Unit, Sorbonne Université, Paris, France.; Bouglé A; Department of Cardiovascular and Thoracic Surgery, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Institute of Cardiology, Paris, France.; Constantin JM; Department of Anaesthesiology and Critical Care, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, GRC 29, DMU DREAM, Paris, France.; Monsel A; Department of Anaesthesiology and Critical Care, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, GRC 29, DMU DREAM, Paris, France.; APHP, INSERM, Immunology-Immunopathology-Immunotherapy, UMR-S 959, Hôpital Pitié-Salpêtrière, Paris, France.; Chommeloux J; APHP, Hôpital Pitié-Salpêtrière, Institut de Cardiologie, Medical Intensive Care Unit, Sorbonne Université, Paris, France.; Mayaux J; APHP, Hôpital Pitié-Salpêtrière, Médecine Intensive Réanimation (Département 'R3S'), Sorbonne Université, Paris, France.; INSERM, UMR-S1158, Neurophysiologie Respiratoire Expérimentale Et Clinique, Sorbonne Université, Paris, France.; Rohaut B; INSERM, CNRS, Institut du Cerveau-Paris Brain Institute-ICM, Sorbonne Université, Paris, France.; APHP, DMU Neurosciences, Hôpital Pitié-Salpêtrière, Paris, France.; Naccache L; INSERM, CNRS, Institut du Cerveau-Paris Brain Institute-ICM, Sorbonne Université, Paris, France.; APHP, DMU Neurosciences, Hôpital Pitié-Salpêtrière, Paris, France.; Jacquens A; APHP, Hôpital Pitié-Salpêtrière, Neurosurgical Intensive Care Unit, Sorbonne Université, Paris, France.; Degos V; APHP, Hôpital Pitié-Salpêtrière, Neurosurgical Intensive Care Unit, Sorbonne Université, Paris, France.; Pélégrini-Issac M; CNRS, INSERM, Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, Paris, France. |
| Corporate Authors: | MRI-COMA investigators; CENTER-TBI MRI participants |
| Source: | Critical care (London, England) [Crit Care] 2026 Mar 04. Date of Electronic Publication: 2026 Mar 04. |
| Publication Model: | Ahead of Print |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 9801902 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1466-609X (Electronic) Linking ISSN: 13648535 NLM ISO Abbreviation: Crit Care Subsets: MEDLINE |
| Imprint Name(s): | Publication: London, UK : BioMed Central Ltd; Original Publication: London : Current Science Ltd, c1997- |
| Competing Interests: | Declarations. Ethics approval and consent to participate: This study was approved by the local ethics committees and adhered to the Reporting of Observational Studies in Epidemiology (STROBE) guidelines and the Declaration of Helsinki. Written informed consent was obtained from all participants or their legal representatives. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. |
| References: | Edlow JA, Rabinstein A, Traub SJ, Wijdicks EFM. Diagnosis of reversible causes of coma. Lancet. 2014;384:2064–76. https://doi.org/10.1016/S0140-6736(13)62184-4.; Giacino JT, Ashwal S, Childs N, et al. The minimally conscious state: definition and diagnostic criteria. Neurology. 2002;58:349–53.; Laureys S, Celesia GG, Cohadon F, et al. Unresponsive wakefulness syndrome: a new name for the vegetative state or apallic syndrome. BMC Med. 2010;8:1–4.; Sandroni C, Cariou A, Cavallaro F, et al. Prognostication in comatose survivors of cardiac arrest: an advisory statement from the European Resuscitation Council and the European Society of Intensive Care Medicine. Intensive Care Med. 2014;40:1816–31. https://doi.org/10.1007/s00134-014-3470-x.; Fischer D, Edlow BL. Coma prognostication after acute brain injury: a review. JAMA Neurol. 2024. https://doi.org/10.1001/jamaneurol.2023.5634.; Herridge MS, Azoulay É. Outcomes after critical illness. N Engl J Med. 2023;388:913–24.; Bodien YG, Busl KM, Chang CWJ, et al. Disorders of consciousness diagnosis, interventions, and prognostication for the intensivist: report of the 2025 ISICEM roundtable. Intensive Care Med. 2025. https://doi.org/10.1007/s00134-025-08224-1.; Sondag L, Ruijter BJ, Tjepkema-Cloostermans MC, et al. Early EEG for outcome prediction of postanoxic coma: prospective cohort study with cost-minimization analysis. Crit Care. 2017;21:1–8.; Rossetti AO, Oddo M, Logroscino G, Kaplan PW. Prognostication after cardiac arrest and hypothermia: a prospective study. Ann Neurol. 2010;67:301–7.; Velly L, Perlbarg V, Boulier T, et al. Use of brain diffusion tensor imaging for the prediction of long-term neurological outcomes in patients after cardiac arrest: a multicentre, international, prospective, observational, cohort study. Lancet Neurol. 2018;17:317–26. https://doi.org/10.1016/S1474-4422(18)30027-9.; Puybasset L, Perlbarg V, Unrug J, et al. Prognostic value of global deep white matter DTI metrics for 1-year outcome prediction in ICU traumatic brain injury patients: an MRI-COMA and CENTER-TBI combined study. Intensive Care Med. 2022;48:201–12. https://doi.org/10.1007/s00134-021-06583-z.; Alexander AL, Lee JE, Lazar M, Field AS. Diffusion tensor imaging of the brain. Neurotherapeutics. 2007;4:316–29. https://doi.org/10.1016/j.nurt.2007.05.011.; Sotak CH. The role of diffusion tensor imaging in the evaluation of ischemic brain injury–a review. NMR Biomed Int J Devoted Dev Appl Magn Reson Vivo. 2002;15:561–9.; Dehaene S, Kerszberg M, Changeux J-P. A neuronal model of a global workspace in effortful cognitive tasks. Proc Natl Acad Sci. 1998;95:14529–34. https://doi.org/10.1073/pnas.95.24.14529.; Baars BJ. The global workspace theory of consciousness. Blackwell Companion Conscious. 2007 236–246.; Simeone P, Auzias G, Lefevre J, et al. Long-term follow-up of neurodegenerative phenomenon in severe traumatic brain injury using MRI. Ann Phys Rehabil Med. 2021;65:101599.; Van Der Eerden AW, Khalilzadeh O, Perlbarg V, et al. White matter changes in comatose survivors of anoxic ischemic encephalopathy and traumatic brain injury: comparative diffusion-tensor imaging study. Radiology. 2014;270:506–16.; Jenkinson M, Smith S. A global optimisation method for robust affine registration of brain images. Med Image Anal. 2001;5:143–56. https://doi.org/10.1016/s1361-8415(01)00036-6.; Cai LY, Yang Q, Kanakaraj P, et al. MASiVar: multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted MRI. Magn Reson Med. 2021;86:3304–20.; Team RC. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Httpwww R-Proj Org. 2016.; Team P. RStudio: integrated development environment for R. Posit Software, PBC, Boston, MA. 2023.; Pedregosa F, Varoquaux G, Gramfort A, et al. Scikit-learn: Machine Learning in Python. J Mach Learn Res. 2011;12:2825–30.; Lundberg SM, Lee SI. A unified approach to interpreting model predictions. Adv Neural Inf Process Syst 2017 30.; Lundberg SM, Nair B, Vavilala MS, et al. Explainable machine-learning predictions for the prevention of hypoxaemia during surgery. Nat Biomed Eng. 2018;2:749–60.; Sergent C, Dehaene S. Neural processes underlying conscious perception: experimental findings and a global neuronal workspace framework. J Physiol-Paris. 2004;98:374–84.; Dehaene S, Changeux J-P, Naccache L. The Global Neuronal Workspace Model of Conscious Access: From Neuronal Architectures to Clinical Applications. In: Dehaene S, Christen Y, editors. Characterizing Consciousness: From Cognition to the Clinic? Berlin Heidelberg, Berlin, Heidelberg: Springer; 2011. p. 55–84.; Bartolomei F, Naccache L. The global workspace (GW) theory of consciousness and epilepsy. Behav Neurol. 2011;24:67–74. https://doi.org/10.3233/BEN-2011-0313.; Mashour GA, Roelfsema P, Changeux J-P, Dehaene S. Conscious processing and the global neuronal workspace hypothesis. Neuron. 2020;105:776–98. https://doi.org/10.1016/j.neuron.2020.01.026.; Fischer D, Edlow BL, Giacino JT, Greer DM. Neuroprognostication: a conceptual framework. Nat Rev Neurol. 2022;18:419–27. https://doi.org/10.1038/s41582-022-00644-7.; Rohaut B, Calligaris C, Hermann B, et al. Multimodal assessment improves neuroprognosis performance in clinically unresponsive critical-care patients with brain injury. Nat Med. 2024. https://doi.org/10.1038/s41591-024-03019-1.; Sitt JD, King J-R, El Karoui I, et al. Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state. Brain. 2014;137:2258–70.; Claassen J, Doyle K, Matory A, et al. Detection of brain activation in unresponsive patients with acute brain injury. N Engl J Med. 2019;380:2497–505. https://doi.org/10.1056/NEJMoa1812757.; Tollard E, Galanaud D, Perlbarg V, et al. Experience of diffusion tensor imaging and 1H spectroscopy for outcome prediction in severe traumatic brain injury: preliminary results. Crit Care Med. 2009;37:1448–55. https://doi.org/10.1097/CCM.0b013e31819cf050.; Quintard H, Velly L, Boussen S, et al. Value of assessment of multivoxel proton chemical shift imaging to predict long term outcome in patients after out-of-hospital cardiac arrest: a preliminary prospective observational study. Resuscitation. 2019;134:136–44. https://doi.org/10.1016/j.resuscitation.2018.09.007.; Stender J, Gosseries O, Bruno M-A, et al. Diagnostic precision of PET imaging and functional MRI in disorders of consciousness: a clinical validation study. |
| Grant Information: | 2005 #051061 Programme Hospitalier de Recherche Clinique; ANR-10-IAIHU-06 "Investissements d'avenir"; Ricerca Finalizzata 2010 - RF-2010-2319503 Italian Ministry of health and Regione Lombardia; 2024 Bourse à la mobilité de SFAR; 2024 Bourse à la mobilité de Phoceo |
| Contributed Indexing: | Keywords: Coma; Deep white matter; Diffusion tensor imaging; Outcome; Prognosis |
| Entry Date(s): | Date Created: 20260304 Latest Revision: 20260304 |
| Update Code: | 20260305 |
| DOI: | 10.1186/s13054-026-05909-x |
| PMID: | 41782003 |
| Database: | MEDLINE |
Journal Article