Assessment of white matter injury and outcome in severe brain trauma: a prospective multicenter cohort.
Damien Galanaud
(1, 2)
,
Vincent Perlbarg
(3)
,
Rajiv Gupta
,
Robert D Stevens
,
Paola Sanchez
,
Eléonore Tollard
(4)
,
Nicolas Menjot de Champfleur
(5)
,
Julien Dinkel
,
Sébastien Faivre
,
Gustavo Soto-Ares
,
Benoit Veber
(6)
,
Vincent Cottenceau
,
Françoise Masson
,
Thomas Tourdias
(7)
,
Edith André
,
Gérard Audibert
(8)
,
Emmanuelle Schmitt
,
Danielle Ibarrola
,
Frédéric Dailler
,
Audrey Vanhaudenhuyse
,
Luaba Tshibanda
,
Jean-François Payen
(9)
,
Jean-François Le Bas
(10, 11)
,
Alexandre Krainik
(10)
,
Nicolas Bruder
(12)
,
Nadine Girard
,
Steven Laureys
(13, 14)
,
Habib Benali
(3)
,
Louis Puybasset
(1)
,
Non Renseigné
1
CHU Pitié-Salpêtrière [AP-HP]
2 NEMESIS-CRICM - Equipe NEMESIS - Centre de Recherches de l'Institut du Cerveau et de la Moelle épinière
3 LIF - Laboratoire d'Imagerie Fonctionnelle
4 Service d'imagerie médicale [CHU Rouen]
5 Urgence et post-urgence psychiatrique
6 Service de réanimation médicale [CHU Rouen]
7 Neuroinflammation: imagerie et thérapie de la sclérose en plaques
8 RCV - Risque cardiovasculaire, rigidité-fibrose et hypercoagulabilité
9 CIC - Grenoble
10 GIN - Grenoble Institut des Neurosciences
11 IRMaGe - IRMaGe
12 Department of Anesthesiology and Intensive Care
13 Coma Science Group [Liege]
14 CRC - Centre de Recherches du Cyclotron [Liège]
2 NEMESIS-CRICM - Equipe NEMESIS - Centre de Recherches de l'Institut du Cerveau et de la Moelle épinière
3 LIF - Laboratoire d'Imagerie Fonctionnelle
4 Service d'imagerie médicale [CHU Rouen]
5 Urgence et post-urgence psychiatrique
6 Service de réanimation médicale [CHU Rouen]
7 Neuroinflammation: imagerie et thérapie de la sclérose en plaques
8 RCV - Risque cardiovasculaire, rigidité-fibrose et hypercoagulabilité
9 CIC - Grenoble
10 GIN - Grenoble Institut des Neurosciences
11 IRMaGe - IRMaGe
12 Department of Anesthesiology and Intensive Care
13 Coma Science Group [Liege]
14 CRC - Centre de Recherches du Cyclotron [Liège]
Damien Galanaud
- Function : Author
- PersonId : 756491
- ORCID : 0000-0002-9285-8121
Vincent Perlbarg
- Function : Author
- PersonId : 758332
- ORCID : 0000-0002-3438-2479
Rajiv Gupta
- Function : Author
Robert D Stevens
- Function : Author
Paola Sanchez
- Function : Author
Nicolas Menjot de Champfleur
- Function : Author
- PersonId : 174064
- IdHAL : nicolas-menjot-de-champfleur
- ORCID : 0000-0002-4098-5962
- IdRef : 134144481
Julien Dinkel
- Function : Author
Sébastien Faivre
- Function : Author
Gustavo Soto-Ares
- Function : Author
Vincent Cottenceau
- Function : Author
Françoise Masson
- Function : Author
Edith André
- Function : Author
Gérard Audibert
- Function : Author
- PersonId : 761625
- ORCID : 0000-0001-7919-5434
Emmanuelle Schmitt
- Function : Author
- PersonId : 762648
- ORCID : 0000-0002-6704-3158
Danielle Ibarrola
- Function : Author
Frédéric Dailler
- Function : Author
Audrey Vanhaudenhuyse
- Function : Author
Luaba Tshibanda
- Function : Author
Alexandre Krainik
- Function : Author
- PersonId : 758317
- ORCID : 0000-0002-4375-0982
- IdRef : 089427491
Nadine Girard
- Function : Author
Steven Laureys
- Function : Author
- PersonId : 768384
- ORCID : 0000-0002-3096-3807
- IdRef : 092126235
Louis Puybasset
- Function : Author
- PersonId : 759706
- ORCID : 0000-0002-6849-1825
Non Renseigné
- Function : Author
Abstract
BACKGROUND: Existing 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). METHODS: In 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. RESULTS: Using 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. CONCLUSIONS: White matter assessment with quantitative DTI increases the accuracy of long-term outcome prediction compared with the available clinical/radiographic prognostic score.