Assessment of white matter injury and outcome in severe brain trauma: A prospective multicenter cohort

Damien Galanaud, Vincent Perlbarg, Rajiv Gupta, Robert David 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 VanhaudenhuyseLuaba Tshibanda, Jean François Payen, Jean François Le Bas, Alexandre Krainik, Nicolas Bruder, Nadine Girard, Steven Laureys, Habib Benali, Louis Puybasset

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)1300-1310
Number of pages11
JournalAnesthesiology
Volume117
Issue number6
DOIs
StatePublished - Dec 2012

Fingerprint

Diffusion Tensor Imaging
Databases
Wounds and Injuries
ROC Curve
Clinical Trials
Glasgow Outcome Scale
Coma
White Matter
Traumatic Brain Injury
Multicenter Studies
Magnetic Resonance Imaging
Brain

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine

Cite this

Assessment of white matter injury and outcome in severe brain trauma : A prospective multicenter cohort. / Galanaud, Damien; Perlbarg, Vincent; Gupta, Rajiv; Stevens, Robert David; Sanchez, Paola; Tollard, Eléonore; De Champfleur, Nicolas Menjot; Dinkel, Julien; Faivre, Sébastien; Soto-Ares, Gustavo; Veber, Benoit; Cottenceau, Vincent; Masson, Françoise; Tourdias, Thomas; André, Edith; Audibert, Gérard; Schmitt, Emmanuelle; Ibarrola, Danielle; Dailler, Frédéric; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Payen, Jean François; Le Bas, Jean François; Krainik, Alexandre; Bruder, Nicolas; Girard, Nadine; Laureys, Steven; Benali, Habib; Puybasset, Louis.

In: Anesthesiology, Vol. 117, No. 6, 12.2012, p. 1300-1310.

Research output: Contribution to journalArticle

Galanaud, D, Perlbarg, V, Gupta, R, Stevens, RD, Sanchez, P, Tollard, E, De Champfleur, NM, Dinkel, J, Faivre, S, Soto-Ares, G, Veber, B, Cottenceau, V, Masson, F, Tourdias, T, André, E, Audibert, G, Schmitt, E, Ibarrola, D, Dailler, F, Vanhaudenhuyse, A, Tshibanda, L, Payen, JF, Le Bas, JF, Krainik, A, Bruder, N, Girard, N, Laureys, S, Benali, H & Puybasset, L 2012, 'Assessment of white matter injury and outcome in severe brain trauma: A prospective multicenter cohort', Anesthesiology, vol. 117, no. 6, pp. 1300-1310. https://doi.org/10.1097/ALN.0b013e3182755558
Galanaud, Damien ; Perlbarg, Vincent ; Gupta, Rajiv ; Stevens, Robert David ; Sanchez, Paola ; Tollard, Eléonore ; De Champfleur, Nicolas Menjot ; Dinkel, Julien ; Faivre, Sébastien ; Soto-Ares, Gustavo ; Veber, Benoit ; Cottenceau, Vincent ; Masson, Françoise ; Tourdias, Thomas ; André, Edith ; Audibert, Gérard ; Schmitt, Emmanuelle ; Ibarrola, Danielle ; Dailler, Frédéric ; Vanhaudenhuyse, Audrey ; Tshibanda, Luaba ; Payen, Jean François ; Le Bas, Jean François ; Krainik, Alexandre ; Bruder, Nicolas ; Girard, Nadine ; Laureys, Steven ; Benali, Habib ; Puybasset, Louis. / Assessment of white matter injury and outcome in severe brain trauma : A prospective multicenter cohort. In: Anesthesiology. 2012 ; Vol. 117, No. 6. pp. 1300-1310.
@article{ade10e84623943419e76e1316456175f,
title = "Assessment of white matter injury and outcome in severe brain trauma: A prospective multicenter cohort",
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.",
author = "Damien Galanaud and Vincent Perlbarg and Rajiv Gupta and Stevens, {Robert David} and Paola Sanchez and El{\'e}onore Tollard and {De Champfleur}, {Nicolas Menjot} and Julien Dinkel and S{\'e}bastien Faivre and Gustavo Soto-Ares and Benoit Veber and Vincent Cottenceau and Fran{\cc}oise Masson and Thomas Tourdias and Edith Andr{\'e} and G{\'e}rard Audibert and Emmanuelle Schmitt and Danielle Ibarrola and Fr{\'e}d{\'e}ric Dailler and Audrey Vanhaudenhuyse and Luaba Tshibanda and Payen, {Jean Fran{\cc}ois} and {Le Bas}, {Jean Fran{\cc}ois} and Alexandre Krainik and Nicolas Bruder and Nadine Girard and Steven Laureys and Habib Benali and Louis Puybasset",
year = "2012",
month = "12",
doi = "10.1097/ALN.0b013e3182755558",
language = "English (US)",
volume = "117",
pages = "1300--1310",
journal = "Anesthesiology",
issn = "0003-3022",
publisher = "Lippincott Williams and Wilkins",
number = "6",

}

TY - JOUR

T1 - Assessment of white matter injury and outcome in severe brain trauma

T2 - A prospective multicenter cohort

AU - Galanaud, Damien

AU - Perlbarg, Vincent

AU - Gupta, Rajiv

AU - Stevens, Robert David

AU - Sanchez, Paola

AU - Tollard, Eléonore

AU - De Champfleur, Nicolas Menjot

AU - Dinkel, Julien

AU - Faivre, Sébastien

AU - Soto-Ares, Gustavo

AU - Veber, Benoit

AU - Cottenceau, Vincent

AU - Masson, Françoise

AU - Tourdias, Thomas

AU - André, Edith

AU - Audibert, Gérard

AU - Schmitt, Emmanuelle

AU - Ibarrola, Danielle

AU - Dailler, Frédéric

AU - Vanhaudenhuyse, Audrey

AU - Tshibanda, Luaba

AU - Payen, Jean François

AU - Le Bas, Jean François

AU - Krainik, Alexandre

AU - Bruder, Nicolas

AU - Girard, Nadine

AU - Laureys, Steven

AU - Benali, Habib

AU - Puybasset, Louis

PY - 2012/12

Y1 - 2012/12

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84870255733&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84870255733&partnerID=8YFLogxK

U2 - 10.1097/ALN.0b013e3182755558

DO - 10.1097/ALN.0b013e3182755558

M3 - Article

C2 - 23135261

AN - SCOPUS:84870255733

VL - 117

SP - 1300

EP - 1310

JO - Anesthesiology

JF - Anesthesiology

SN - 0003-3022

IS - 6

ER -