Article (Scientific journals)
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
Velly, Lionel; Perlbarg, Vincent; Boulier, Thomas et al.
2018In The Lancet Neurology, 17 (4), p. 317-326
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Keywords :
MRI; Glasgow coma scale; Rankin scale
Abstract :
[en] Background: Prediction of neurological outcome after cardiac arrest is a major challenge. The aim of this study was to assess whether quantitative whole-brain white matter fractional anisotropy (WWM-FA) measured by diffusion tensor imaging between day 7 and day 28 after cardiac arrest can predict long-term neurological outcome. Methods: This prospective, observational, cohort study (part of the MRI-COMA study) was done in 14 centres in France, Italy, and Belgium. We enrolled patients aged 18 years or older who had been unconscious for at least 7 days after cardiac arrest into the derivation cohort. The following year, we recruited the validation cohort on the same basis. We also recruited a minimum of five healthy volunteers at each centre for the normalisation procedure. WWM-FA values were compared with standard criteria for unfavourable outcome, conventional MRI sequences (fluid-attenuated inversion recovery and diffusion-weighted imaging), and proton magnetic resonance spectroscopy. The primary outcome was the best achieved Glasgow-Pittsburgh Cerebral Performance Categories (CPC) at 6 months, dichotomised as favourable (CPC 1–2) and unfavourable outcome (CPC 3–5). Prognostication performance was assessed by the area under the receiver operating characteristic (ROC) curves and compared between groups. This study was registered with ClinicalTrials.gov, number NCT00577954. Findings: Between Oct 1, 2006, and June 30, 2014, 185 patients were enrolled in the derivation cohort, of whom 150 had an interpretable multimodal MRI and were included in the analysis. 33 (22%) patients had a favourable neurological outcome at 6 months. Prognostic accuracy, as quantified by the area under the ROC curve, was significantly higher with the normalised WWM-FA value (area under the ROC curve 0·95, 95% CI 0·91–0·98) than with the standard criteria for unfavourable outcome or other MRI sequences. In a subsequent validation cohort of 50 patients (enrolled between April 1, 2015, and March 31, 2016), a normalised WWM-FA value lower than 0·91, set from the derivation cohort, had a negative predictive value of 71·4% (95% CI 41·9–91·6) and a positive predictive value of 100% (90·0–100), with 89·7% sensitivity (75·8–97·1) and 100% specificity (69·1–100) for the prediction of unfavourable outcome. Interpretation: In patients who are unconscious 7 days after cardiac arrest, the normalised WWM-FA value, measured by diffusion tensor imaging, could be used to accurately predict neurological outcome at 6 months. This evidence requires confirmation from future large-scale trials with a strict protocol of withdrawal or limitation-of-care decisions and time window for MRI.
Disciplines :
Neurology
Author, co-author :
Velly, Lionel;  Institut de Neurosciences, MeCA (UMR 7289, CNRS), Aix Marseille Université, Marseille, France
Perlbarg, Vincent;  CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Sorbonne Université, Paris, France, Institut du Cerveau et de la Moelle Epinière, AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Boulier, Thomas;  CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Sorbonne Université, Paris, France
Adam, Nicolas;  AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Delphine, Sébastien;  CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Sorbonne Université, Paris, France
Luyt, Charles Édouard;  AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Battisti, Valentine;  AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Torkomian, Grégory;  AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Arbelot, Charlotte;  AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Chabanne, Russell;  Centre Hospitalier Universitaire de Clermont-Ferrand, Clermont-Ferrand, France
Jean, Beatrix;  Centre Hospitalier Universitaire de Clermont-Ferrand, Clermont-Ferrand, France
Di Perri, Carol ;  Université de Liège - ULiège > GIGA : Coma Group
Laureys, Steven  ;  Université de Liège - ULiège > GIGA : Coma Group
Citerio, Giuseppe;  Milan Bicocca University, Milan, Italy, Hospital San Gerardo, Monza, Italy
Vargiolu, Alessia;  Milan Bicocca University, Milan, Italy, Hospital San Gerardo, Monza, Italy
Rohaut, Benjamin;  AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Bruder, Nicolas;  Assistance Publique–Hôpitaux de Marseille, Hôpital Timone Adultes, Marseille, France
Girard, Nadine;  Assistance Publique–Hôpitaux de Marseille, Hôpital Timone Adultes, Marseille, France
Silva, Stein;  Neuro-Campus Baudot, Toulouse, France
Cottenceau, Vincent;  Hôpital Universitaire Pellegrin, Bordeaux, France
Tourdias, Thomas;  Hôpital Universitaire Pellegrin, Bordeaux, France
Coulon, Olivier;  Institut de Neurosciences, MeCA (UMR 7289, CNRS), Aix Marseille Université, Marseille, France
Riou, Bruno;  AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Naccache, Lionel;  Institut du Cerveau et de la Moelle Epinière, AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Gupta, Rajiv;  Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
Benali, Habib;  CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Sorbonne Université, Paris, France
Galanaud, Damien;  AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Puybasset, Louis;  CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Sorbonne Université, Paris, France, AP-HP, Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France
Constantin, Jean-Michel
Chastre, Jean
Amour, Julien
Vezinet, Corine
Rouby, Jean-Jacques
Raux, Mathieu
Langeron, Olivier
Degos, Vincent
Bolgert, Francis
Weiss, Nicolas
Similowski, Thomas
Demoule, Alexandre
Duguet, Alexandre
Tollard, Eléonore
Veber, Benoît
Lotterie, Jean-Albert
SANCHEZ-PENA, Paola
Génestal, Michelle
Patassini, Mirko
MRI-COMA Investigators
More authors (38 more) Less
Language :
English
Title :
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
Publication date :
April 2018
Journal title :
The Lancet Neurology
ISSN :
1474-4422
eISSN :
1474-4465
Publisher :
Lancet Publishing Group
Volume :
17
Issue :
4
Pages :
317-326
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
French Ministry of Health
French National Agency for Research
Italian Ministry of Health
Regione Lombardia
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since 30 May 2020

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