Standard predictors of outcome after cardiac arrest (CA) have substantial limitations in terms of reliability and generalizability. By providing brain structural connectivity maps, or connectomes, advanced MRI techniques, operating through high-strength magnetic field (HF; 1.5 to 3-T), have precisely revealed white and grey brain matter damages induced by CA, and have demonstrated the high sensitivity and specificity of these indicators for predicting neurological outcome after CA. However, HF MRI requires rigid safety precautions, highly trained technicians and patient transport to dedicated hospital imaging suites, hindering the implementation of these promising neuroimaging techniques in the setting of critical illness.
Interestingly, a recent report demonstrates the capability of a proof-of-concept very low-field (VLF; 0.064-T) mobile MRI to obtain neuroimaging at the bedside in critically ill patients. Nevertheless, the spatial resolution of VLF-MRI seems low and there is no available evidence about the use of VLF-MRI to extract highly needed new predictors of neurological recovery based on critical brain structural connectomes.
The CUBE project holds the promise of providing a radical paradigm shift in the field of neuroprognostication of anoxic coma patients. The current proposal is a "proof-of concept" study which aims to compare for the first time, HF, VLF and enhanced VLF (recon-VLF) structural connectomes from anoxic coma patients and healthy subjects across the time (3 paired HF and VLF brain scan across the first two weeks after CA). To obtain recon-VLF data, the Investigators will use an ensemble of ground-breaking methods to increase the native spatial resolution of VLF-MRI data. The whole brain imaging dataset will be used to prepare future neuroprognostication studies based on fully bedside assessment of brain structural integrity after CA.