Dr. Edilberto Amorim is a neurologist with subspecialty training in critical care and epilepsy who aims to employ biomedical technology innovations in brain monitoring to personalize treatment for patients with hypoxic- ischemic brain injury post-cardiac arrest. This career development award and its rigorous curriculum will establish Dr. Amorim as a clinician-scientist with independent expertise in: 1) Deep learning applied to physiology time-series, 2) Causal inference for observational data, and 3) Quantitative brain imaging. Every year, more than 500,000 Americans have a cardiac arrest. Brain injury is the number one cause of death for patients surviving initial resuscitation, and refractory seizures and other seizure-like brain activity are diagnosed in up to 50% of patients. Despite being a common complication, outcomes are dismal and current treatment strategies for seizures post-cardiac arrest are limited. Dr. Amorim aims to identify physiology-driven biomarkers of resilience to hypoxic-ischemic brain injury by utilizing state-of-the-art computational methods and a massive EEG and neuroimaging dataset with >1,500 subjects. His central hypothesis is that specific time- dependent changes in spike and accompanying EEG activity during cardiac arrest treatment predict seizure control and, ultimately, neurological recovery. The primary objectives of this proposal are: 1) Identify early longitudinal epileptiform EEG phenotypes predictive of neurological recovery using interpretable and deep learning algorithms; 2) Establish quantitative EEG biomarkers of seizure treatment response to anesthetics; and 3) Estimate the causal effect of rapid seizure treatment with anesthetics in preventing structural brain injury quantified with brain MRI. Dr. Amorim has generated preliminary data to demonstrate the feasibility of modeling EEG phenotypes longitudinally for outcome prediction and has applied quantitative EEG biomarkers to predict degree of brain injury on brain MRI. His primary mentor in this proposal will be Dr. Edward Chang, a neuroscientist and leader in human neurophysiology research. His co-mentors will include Dr. Brandon Westover, an authority in machine learning applied to critical care EEG, and Dr. Donna Ferriero, an accomplished translational and neuroimaging investigator in hypoxic-ischemic brain injury. Additional mentoring in quantitative neuroimaging (Dr. Srikantan Nagarajan) and biostatistics (Dr. Charles McCulloch) will be essential components of his training.
These aims are expected to establish early non-invasive predictive biomarkers of neurological recovery and seizure control that may: 1) Guide patient selection for clinical trials enrichment and 2) Serve as target to therapeutic interventions after hypoxic-ischemic brain injury. By leveraging the deep expertise of a cross-disciplinary group of world-class mentors and the unparalleled innovation environments of the University of California, San Francisco and the Bay Area, Dr. Amorim will be ideally positioned to uncover fundamental knowledge about epileptogenesis after acute brain injury as well as spearhead clinical trials focused on improving outcomes meaningful to cardiac arrest patients.
Cardiac arrest impacts the lives of 500,000 Americans every year, and nearly half of patients surviving the initial resuscitation will develop seizures or seizure-like brain activity as a complication of hypoxic-ischemic brain injury. We aim to reduce secondary brain injury and neurological disability from seizures after cardiac arrest by personalizing seizure treatment using EEG and brain MRI biomarkers of neuro-recovery. We expect that the outcome of the proposed studies will provide critical knowledge about epileptogenesis after hypoxic-ischemic brain injury andguide the development of goal-directed seizure treatment and patient selection in future clinical trials.
