Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
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.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 1 | Patients in a coma condition after a traumatic brain injury (250), stroke, cerebral anoxia or subarachnoid hemorrhage (150), for at least 7 days. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Multimodal MRI | Procedure | Multimodal MRI |
|
| Measure | Description | Time Frame |
|---|---|---|
| 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]). | one year |
| Measure | Description | Time Frame |
|---|---|---|
| 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). | one year | |
| Intra and inter-observer reproducibility study of the analysis of the various sequences. |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Traumatic brain injured patients, stroke patients, subarachnoid hemorrhage (SAH) patients and cerebral anoxia patients
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Pr Louis Puybasset,, MD, PhD | Assistance Publique Hopitaux de Paris Pitié Salpetriere | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Assistance Publique Hopitaux de Paris Pitie Salpetriere | Paris | 75013 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34904191 | Derived | Puybasset L, Perlbarg V, Unrug J, Cassereau D, Galanaud D, Torkomian G, Battisti V, Lefort M, Velly L, Degos V, Citerio G, Bayen E, Pelegrini-Issac M; MRI-COMA Investigators CENTER-TBI MRI Participants and MRI Only Investigators. Prognostic value of global deep white matter DTI metrics for 1-year outcome prediction in ICU traumatic brain injury patients: an MRI-COMA and CENTER-TBI combined study. Intensive Care Med. 2022 Feb;48(2):201-212. doi: 10.1007/s00134-021-06583-z. Epub 2022 Dec 14. | |
| 34718191 |
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D003128 | Coma |
| D020521 | Stroke |
| D002534 | Hypoxia, Brain |
| ID | Term |
|---|---|
| D014474 | Unconsciousness |
| D003244 | Consciousness Disorders |
| D019954 | Neurobehavioral Manifestations |
| D009461 | Neurologic Manifestations |
Not provided
Not provided
Not provided
Not provided
Not provided
| during the study |
| Derived |
| Simeone P, Auzias G, Lefevre J, Takerkart S, Coulon O, Lesimple B, Torkomian G, Battisti V, Jacquens A, Couret D, Naccache L, Bayen E, Bruder N, Perlbarg V, Puybasset L, Velly L. Long-term follow-up of neurodegenerative phenomenon in severe traumatic brain injury using MRI. Ann Phys Rehabil Med. 2022 Nov;65(6):101599. doi: 10.1016/j.rehab.2021.101599. Epub 2022 Feb 15. |
| 29500154 | Derived | Velly L, Perlbarg V, Boulier T, Adam N, Delphine S, Luyt CE, Battisti V, Torkomian G, Arbelot C, Chabanne R, Jean B, Di Perri C, Laureys S, Citerio G, Vargiolu A, Rohaut B, Bruder N, Girard N, Silva S, Cottenceau V, Tourdias T, Coulon O, Riou B, Naccache L, Gupta R, Benali H, Galanaud D, Puybasset L; MRI-COMA Investigators. Use of brain diffusion tensor imaging for the prediction of long-term neurological outcomes in patients after cardiac arrest: a multicentre, international, prospective, observational, cohort study. Lancet Neurol. 2018 Apr;17(4):317-326. doi: 10.1016/S1474-4422(18)30027-9. Epub 2018 Feb 27. |
| 23135257 | Derived | Luyt CE, Galanaud D, Perlbarg V, Vanhaudenhuyse A, Stevens RD, Gupta R, Besancenot H, Krainik A, Audibert G, Combes A, Chastre J, Benali H, Laureys S, Puybasset L; Neuro Imaging for Coma Emergence and Recovery Consortium. Diffusion tensor imaging to predict long-term outcome after cardiac arrest: a bicentric pilot study. Anesthesiology. 2012 Dec;117(6):1311-21. doi: 10.1097/ALN.0b013e318275148c. |
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D000860 | Hypoxia |
| D012818 | Signs and Symptoms, Respiratory |