Multimodal Resonance Imaging for Outcome Prediction on Coma Patients (MRI-Coma)
|ClinicalTrials.gov Identifier: NCT00577954|
Recruitment Status : Completed
First Posted : December 20, 2007
Last Update Posted : September 21, 2017
|Condition or disease||Intervention/treatment|
|Coma||Procedure: Multimodal MRI|
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.
|Study Type :||Observational|
|Actual Enrollment :||417 participants|
|Official Title:||Multimodal Magnetic Resonance (MRI) Development in Comatose Patients for an Algorithm in the Prediction of Consciousness Recovery|
|Study Start Date :||October 2006|
|Primary Completion Date :||March 2010|
|Study Completion Date :||June 2014|
Patients in a coma condition after a traumatic brain injury (250), stroke, cerebral anoxia or subarachnoid hemorrhage (150), for at least 7 days.
Procedure: Multimodal MRI
- To define a quantified indicator resulting from the analysis of the multimodal MRI combined with clinical data to create a score to predict the 1 year outcome as measured by the dichotomized Glasgow Outcome Scale (extended version [GOSE]). [ Time Frame: one year ]
- Relevance of the composite score to predict the clinical outcome at 1 year assessed by the Rankin score, the GOSE and the disability rating scale (DRS). [ Time Frame: one year ]
- Intra and inter-observer reproducibility study of the analysis of the various sequences. [ Time Frame: during the study ]
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT00577954
|Assistance Publique Hopitaux de Paris Pitie Salpetriere|
|Paris, France, 75013|
|Principal Investigator:||Pr Louis Puybasset,, MD, PhD||Assistance Publique Hopitaux de Paris Pitié Salpetriere|