Author
Listed:
- Frédéric Clarençon
- Éric Bardinet
- Jacques Martinerie
- Vincent Pelbarg
- Nicolas Menjot de Champfleur
- Rajiv Gupta
- Eléonore Tollard
- Gustavo Soto-Ares
- Danielle Ibarrola
- Emmanuelle Schmitt
- Thomas Tourdias
- Vincent Degos
- Jérome Yelnik
- Didier Dormont
- Louis Puybasset
- Damien Galanaud
- for the Neuro Imaging for Coma Emergence and Recovery (NICER) consortium
Abstract
Purpose: This study evaluates the correlation between injuries to deep gray matter nuclei, as quantitated by lesions in these nuclei on MR T2 Fast Spin Echo (T2 FSE) images, with 6-month neurological outcome after severe traumatic brain injury (TBI). Materials and methods: Ninety-five patients (80 males, mean age = 36.7y) with severe TBI were prospectively enrolled. All patients underwent a MR scan within the 45 days after the trauma that included a T2 FSE acquisition. A 3D deformable atlas of the deep gray matter was registered to this sequence; deep gray matter lesions (DGML) were evaluated using a semi-quantitative classification scheme. The 6-month outcome was dichotomized into unfavorable (death, vegetative or minimally conscious state) or favorable (minimal or no neurologic deficit) outcome. Results: Sixty-six percent of the patients (63/95) had both satisfactory registration of the 3D atlas on T2 FSE and available clinical follow-up. Patients without DGML had an 89% chance (P = 0.0016) of favorable outcome while those with bilateral DGML had an 80% risk of unfavorable outcome (P = 0.00008). Multivariate analysis based on DGML accurately classified patients with unfavorable neurological outcome in 90.5% of the cases. Conclusion: Lesions in deep gray matter nuclei may predict long-term outcome after severe TBI with high sensitivity and specificity.
Suggested Citation
Frédéric Clarençon & Éric Bardinet & Jacques Martinerie & Vincent Pelbarg & Nicolas Menjot de Champfleur & Rajiv Gupta & Eléonore Tollard & Gustavo Soto-Ares & Danielle Ibarrola & Emmanuelle Schmitt &, 2017.
"Lesions in deep gray nuclei after severe traumatic brain injury predict neurologic outcome,"
PLOS ONE, Public Library of Science, vol. 12(11), pages 1-16, November.
Handle:
RePEc:plo:pone00:0186641
DOI: 10.1371/journal.pone.0186641
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