• Damien Galanaud, Vincent Perlbarg, Rajiv Gupta, Robert D Stevens, Paola Sanchez, Eléonore Tollard, Nicolas Menjot de Champfleur, Julien Dinkel, Sébastien Faivre, Gustavo Soto-Ares, Benoit Veber, Vincent Cottenceau, Françoise Masson, Thomas Tourdias, Edith André, Gérard Audibert, Emmanuelle Schmitt, Danielle Ibarrola, Frédéric Dailler, Audrey Vanhaudenhuyse, Luaba Tshibanda, Jean-François Payen, Jean-François Le Bas, Alexandre Krainik, Nicolas Bruder, Nadine Girard, Steven Laureys, Habib Benali, Louis Puybasset, and Neuro Imaging for Coma Emergence and Recovery Consortium.
• Department of Neuroradiology, Pitié Salpêtrière Hospital, & Université Pierre et Marie Curie (Paris VI), Boulevard de l'Hôpital, Paris, France. galanaud@gmail.com
• Anesthesiology. 2012 Dec 1;117(6):1300-10.

BackgroundExisting methods to predict recovery after severe traumatic brain injury lack accuracy. The aim of this study is to determine the prognostic value of quantitative diffusion tensor imaging (DTI).MethodsIn a multicenter study, the authors prospectively enrolled 105 patients who remained comatose at least 7 days after traumatic brain injury. Patients underwent brain magnetic resonance imaging, including DTI in 20 preselected white matter tracts. Patients were evaluated at 1 yr with a modified Glasgow Outcome Scale. A composite DTI score was constructed for outcome prognostication on this training database and then validated on an independent database (n=38). DTI score was compared with the International Mission for Prognosis and Analysis of Clinical Trials Score.ResultsUsing the DTI score for prediction of unfavorable outcome on the training database, the area under the receiver operating characteristic curve was 0.84 (95% CI: 0.75-0.91). The DTI score had a sensitivity of 64% and a specificity of 95% for the prediction of unfavorable outcome. On the validation-independent database, the area under the receiver operating characteristic curve was 0.80 (95% CI: 0.54-0.94). On the training database, reclassification methods showed significant improvement of classification accuracy (P < 0.05) compared with the International Mission for Prognosis and Analysis of Clinical Trials score. Similar results were observed on the validation database.ConclusionsWhite matter assessment with quantitative DTI increases the accuracy of long-term outcome prediction compared with the available clinical/radiographic prognostic score.

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