Assessment of Tissue Injury in Severe Brain Trauma

Christophe Maggia (1) , Senan Doyle (2, 1) , Florence Forbes (3) , Olivier Heck (1) , Irène Troprès (1) , Corentin Berthet (1) , Yann Teyssier (1) , Lionel Velly (1) , Jean-Francois Payen (4, 1) , Michel Dojat (1)

1 GIN - [GIN] Grenoble Institut des Neurosciences
2 Pixyl Medical [Grenoble]
3 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
4 ANTE-INSERM U836, équipe 5 - Neuro-imagerie fonctionnelle et métabolique

We report our methodological developments to investigate, in a multi-center study using mean diffusivity, the tissue damage caused by a severe traumatic brain injury (GSC<9) in the 10 days post-event. To assess the diffuse aspect of the injury, we fuse several atlases to parcel cortical, subcortical and WM structures into well identified regions where MD values are computed and compared to normative values. We used P-LOCUS to provide brain tissue segmentation and exclude voxels labeled as CSF, ventricles and hemorrhagic lesion and then automatically detect the lesion load. Preliminary results demonstrate that our method is coherent with expert opinion in the identification of lesions. We outline the challenges posed in automatic analysis for TBI.

Domaines: Statistiques [math.ST]; Sciences du Vivant [q-bio]

Christophe Maggia, Senan Doyle, Florence Forbes, Olivier Heck, Irène Troprès, et al.. Assessment of Tissue Injury in Severe Brain Trauma. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. , 9556, Springer International Publishing, pp.57-68, 2016, Lecture Notes in Computer Science, 978-3-319-30857-9. ⟨10.1007/978-3-319-30858-6_6⟩. ⟨hal-01423467⟩