Using Patient-Specific Modeling of the Heart for Prediction of Optimal Targets for Catheter Ablation of Ventricular Tachycardia in Patients with Myocardial Infarction or Fibrosis and ICDs

Unmet Need
Ventricular tachycardia (VT) is a heart rhythm disorder that affects hundreds of thousands of Americans every year. VT is defined as an irregular accelerated heart rate due to abnormal electrical signaling in the heart’s lower chambers. Implantable Cardioverter Defibrillators (ICDs) can protect high-risk patients from sudden cardiac arrest due to known/sustained VT by administering a controlled electrical shock when they detect a heart is beating much too quickly. As a means to reduce painful and unnecessary ICD shocks, catheter ablation is often a required adjunctive therapy for patients with VT. Despite significant clinical advances in techniques for VT ablation, success rates remain limited and a new technique for ICD patients is in high demand.

Technology Overview
New technologies have provided a non-invasive technique to identify optimal ablation in VT patients using 3D electrophysiological heart simulation via a reconstructed heart model. However, the approach uses MRI image mapping to model patients’ hearts and thus cannot be applied to people with ICDs as the implant creates an artifact in MRI images. The proposed technology overcomes this issue by estimating the image area affected by the artifact and includes it in the reconstructed 3D ventricular model. In addition, the technology includes a system to compare the predicted ablation sites to the clinical sites when used in a retrospective setting. This new ablation mechanism raises efficacy, shortens the duration of the procedure, and prevents excessive tissue damage during the procedure.

Stage of Development
The inventors have used this technique to perform both retrospective and prospective human studies.

Publications
A Prakosa, et al. Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia. Nature Biomed. Eng. 2, 732-740 (2018).

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