CCNI | Clinical Computational Neuroimaging Group

Cardiac Arrest

The goal of this research is to predict likelihood of good long-term neurological recovery in people who are initially in coma after experiencing a cardiac arrest. We previously shown that patients with extensive abnormalities on DWI were likely to have poor outcomes at 6 months. You can read our paper, “Comatose Patients with Cardiac Arrest: Predicting Clinical Outcome with Diffusion-weighted MR Imaging”, here: https://pubs.rsna.org/doi/10.1148/radiol.2521081232.

We showed that for CT imaging, combining CT findings with clinical assessments improved neuroprognostication. For more information, you can read our paper, “Predicting clinical outcome in comatose cardiac arrest patients using early noncontrast computed tomography”, here: https://www.ahajournals.org/doi/10.1161/STROKEAHA.110.594879.

We are now working on improving our understanding of the mechanisms underlying recovery of consciousness after cardiac arrest using advanced MRI techniques (diffusion tensor imaging, resting state fMRI, task-based fMRI) with EEG and clinical neurological examinations (such as the Glasgow Coma Scale and Coma Recovery Scale-Revised). 

Examples of alterations in brain diffusivity and structural connectivity in cardiac arrest patients who are comatose

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