Identification of ablation gaps

A system for assisting in catheter-based cardiac ablation by predicting procedural success and identifying ablation targets based on patient-specific data, the system comprising:

• a memory storing computer-readable instructions;
• and
• one or more processors in communication with an intracardiac catheter,
• wherein the computer-readable instructions:
• when collectively executed by the one or more processors cause the system to:
• receive patient-specific data comprising (i) time-series biometric data acquired during mapping and ablation procedures using the intracardiac catheter and (ii) corresponding procedural outcome data that include recurrence status or need for redo procedures;
• generate procedure performance metrics from the patient-specific data, the procedure performance metrics characterizing features of successful and unsuccessful ablation procedures;
• during a current ablation procedure, determine a success prediction for the procedure by applying a trained predictive model to real-time biometric signals received from the intracardiac catheter, the success prediction being based on the generated procedure performance metrics;
• and
• generate and display an ablation recommendation that includes a predicted likelihood of procedural success and a spatial location on a cardiac anatomical model representing a recommended site for additional ablation.

A non-transitory computer readable storage medium storing instructions for assisting in catheter-based cardiac ablation by predicting procedural success and identifying ablation targets based on patient-specific data, the instructions when executed by a processor of a surgical console, cause the surgical console to perform a method comprising:

• receiving patient-specific data comprising (i) time-series biometric data acquired during mapping and ablation procedures using an intracardiac catheter, and (ii) corresponding procedural outcome data including recurrence status or need for redo procedures;
• generating procedure performance metrics based on the patient-specific data, the performance metrics characterizing features of successful and unsuccessful ablation procedures;
• determining, during a current ablation procedure, a success prediction for the catheter-based cardiac ablation by applying a trained predictive model to real-time biometric signals received from the intracardiac catheter, the prediction based on the previously generated performance metrics;
• and
• generating and displaying an ablation recommendation comprising a predicted likelihood of procedural success and a spatial location on a cardiac anatomical model representing a recommended site for additional ablation.