This technology is a software program that incorporates electroanatomic data to identify optimal regions in the myocardium for curative ablation targeting of cardiac arrhythmias.
Cardiac arrhythmia is the most common cause of sudden death in the United States. However, catheter ablation—the standard curative operation—is an inefficient procedure that relies upon manual visual inspection by the operator. This dependence on human interpretation leads to prolonged procedure times and reduced ablation success, resulting in increased risk of complications and disease persistence. Therefore, there is a need for an automated system that can rapidly and accurately identify the locations of cardiac isthmuses for the long-term treatment of arrhythmia.
This software is a machine learning-guided approach to model the locations of arrhythmia isthmuses. Electroanatomic data with electrical signal features and anatomical information obtained from previously successful ablation procedures are used to construct and train the model. Once trained, this algorithm can be used to predict the presence of arrhythmia isthmuses in patients based off data acquired using traditional mapping techniques. As such, this technology can be used to improve ablation targeting for cardiac arrythmias.
This technology has been validated using a patient dataset.
Christine Hendon, Ph.D. Deepak Saluja, MD
Patent Pending
IR CU22127
Licensing Contact: Dovina Qu
