Artificial Intelligence Analysis of Initial Scan Evolution of Traumatic Brain Injured Patient to Predict Neurological Outcome

Traumatic brain injury is a common and serious pathology, responsible of an important morbi-mortality. The TBI can be consider as a complex set of nosological entities of different evolution with difficult early identification whereas the main issue of this pathology depends on prevention and management of the lesions caused by the initial cerebral aggression. Different evolutionary profiles seems to exist and sometimes coexists: edema evolution, hemorrhagic transformation and/or cerebrospinal fluid (CSF) resorption issues with hydrocephalus apparition. Currently, there is no Imaging methods that can be used in every day clinical management that allows a visualization, quantification and prediction of these different lesional evolutions CT scan is the reference imaging method for TBI patient monitoring. It allows a lesion description, a therapeutic adaptation and an evaluation of the prognostic. Even if it is used as a routine examination, the analysis of cerebral scanners remains manual and a non-quantitative one, which make a little informative analysis as far as lesions evolution is concerned. Recently it has been established the automatic MRI analysis with AI approach allows: 1. \- To show aspects of images that can't be seen to the naked eye 2. \- To automatically segment and quantify the different tissues (edema, hemorrhage...). First tests on this kind of analysis on CT scans shows that this technology can be transferred from MRI to CT scans and more importantly it brings out new quantitative informations on cerebral lesions evolution.