Coma Clinical Trial
Official title:
Multimodal Magnetic Resonance (MRI) Development in Comatose Patients for an Algorithm in the Prediction of Consciousness Recovery
Stroke, traumatic head injury, subarachnoid hemorrhage and cerebral anoxia are main causes of a coma condition implying severe brain damage and thus, poor prognosis. Clinicians are often in need for a tool able to predict the awakening of these patients. Multimodal MRI, associating the traditional morphological sequences with spectroscopy-MRI (MRS) and the diffusion tensor imaging, could provide such a prediction.
Predicting the awakening of patients in comas is one of the principal stakes of the current
neurointensive care unit (neuroICU). Several studies and clinical practice suggest that the
multimodal MRI, which associates the traditional morphological sequences (T1, T2*, FLAIR/T2),
the spectroscopy-MRI (MRS) and the diffusion tensor imaging, is a tool allowing such a
prediction. However, this strategy has not been yet validated. Additionally, currently there
is no method of analysis including the 4 different sequences.
Objective: The goal of this study is to develop a composite score able to predict the
awakening of coma patients following events such as a severe cranial trauma, ischemic or
hemorrhagic cerebrovascular accident and cerebral anoxia. This composite score will be built
from the results of the multimodal MRI (quantified indicator) in combination with clinical
covariables (e.g., age of the patient, the mechanism of the accident (high versus low speed),
etc.). The final score will aim to predict the outcome of patients at 1 year, evaluated by
one of the following categories: favourable (Glasgow Outcome Scale (GOS 3+, 4, and 5) or
unfavourable outcome (GOS 1, 2, and 3). GOS 3- score has been defined as minimally conscious
state and GOS 3+ score as severe disability excluding cognitive sequelae.
MRI Analysis: The lesions present on the MRI will be quantified by a neuroradiologist and a
dedicated clinical engineer from the coordination centre (Pitié-Salpêtrière Hospital) in a
blinded way regarding patients' clinical data. Lesion load-indicators will be calculated on
the sequences of FLAIR/T2, T2*, MRS and diffusion tensor imaging from a predefined analysis
grid allowing the regional study of the lesions as well as the appreciation of their nature,
their uni- or bilateral character and if bilateral, their symmetry.
Hypothesis and applicability: The multivariate analysis of morphological MRI, MRS and
diffusion tensor imaging data, combined with the clinical covariables, will aim to develop a
statistical algorithm, able to predict the clinical outcome of the patients. In the long
term, it will be integrated into an expert system which will be the subject of a patent
submission. The final objective is to provide the clinicians a diagnostic tool able to
determine outcome of patients with severe cranial trauma and other neurological conditions
such as stroke, subarachnoid hemorrhage and cerebral anoxia.
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