The Predictive Model of Sudden Cardiac Death in Anomalous Aortic Origin of Coronary Artery (AAOCA) is a patient-specific computational modeling approach to predict ischemia risk in individuals with anomalous coronaries. Anomalous coronaries are variations or abnormalities in the anatomy of the coronary arteries. These anomalies can differ in presentation and severity, with some increasing the risk of heart problems, such as myocardial ischemia (reduced blood flow to the heart muscle), arrhythmias or sudden cardiac arrest. According to The Cleveland Clinic, up to 1% of the population has an anomalous coronary artery, and most cases are not dangerous.

This predictive model utilizes morphological risk factors derived from advanced imaging data to offer a validated method for risk stratification, determining the need for surgery, selecting the type of surgery, assessing the effectiveness of surgery, and evaluating residual ischemia post-surgery.

Because there are no effective risk stratification approaches for AAOCA individuals, predicting these life-threatening events is challenging. AAOCA is a significant cause of sudden death in children, and current understanding of the mechanisms leading to ischemia and sudden cardiac death (SCD) is limited. According to the Nora Eccles Harrison Cardiovascular Research and Training Institute, "SCD is one of the most significant causes of natural deaths globally. Annually, just over 300,000 US adult deaths are a result of sudden cardiac death. Roughly half of all cardiovascular disease deaths are from SCD." The proposed model addresses these gaps, potentially shifting the AAOCA field from uncertainty to clinical solutions.

RINCH has filed a provisional application (63/502,524) for this technology. The inventors are planning additional refinement of the methodology and a clinical trial to validate the model in a prospective patient population. This technology is jointly owned with Georgia Institute of Technology.