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Related Experiment Video

Updated: Jun 4, 2026

Ablation of Ischemic Ventricular Tachycardia Using a Multipolar Catheter and 3-dimensional Mapping System for High-density Electro-anatomical Reconstruction

Ablation of Ischemic Ventricular Tachycardia Using a Multipolar Catheter and 3-dimensional Mapping System for High-density Electro-anatomical Reconstruction

Published on: January 31, 2019

A data-driven computational methodology for assessing ventricular ablation procedures.

Filippo Caruso Lombardi^1,2, Anna Crispino³, Bich Lien Nguyen⁴

¹Gran Sasso Science Institute (GSSI), Viale Luigi Rendina 26, 67100, L'Aquila, Italy.

Biomechanics and Modeling in Mechanobiology

|June 3, 2026

Summary

This summary is machine-generated.

Computational modeling aids in understanding and treating ventricular tachycardia after heart attacks. This framework uses patient data to create personalized models, improving ablation strategies for better patient outcomes.

Keywords:

Cardiac ablation Computational electrophysiology Electroanatomical mapping GPU acceleration Patient-specific modeling Ventricular tachycardia

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Last Updated: Jun 4, 2026

Ablation of Ischemic Ventricular Tachycardia Using a Multipolar Catheter and 3-dimensional Mapping System for High-density Electro-anatomical Reconstruction

Ablation of Ischemic Ventricular Tachycardia Using a Multipolar Catheter and 3-dimensional Mapping System for High-density Electro-anatomical Reconstruction

Published on: January 31, 2019

Robotic Ablation of Atrial Fibrillation

Robotic Ablation of Atrial Fibrillation

Published on: May 29, 2015

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

Area of Science:

Biomedical Engineering
Computational Cardiology
Medical Imaging

Background:

Ventricular tachycardia (VT) post-myocardial infarction (MI) presents complex reentrant circuits.
Conventional electroanatomical mapping faces challenges in characterizing these VT substrates.
Computational modeling offers a complementary approach to understand conduction dynamics.

Purpose of the Study:

To develop a data-driven computational framework for retrospective analysis of post-MI VT.
To integrate patient-specific electroanatomical mapping data for personalized modeling.
To evaluate the impact of radiofrequency ablation and explore alternative strategies.

Main Methods:

Integrated patient-specific electroanatomical mapping data (activation times, voltage, electrograms).
Developed a personalized computational model using a viability-based scalar field.
Introduced a novel calibration for local tissue conductivity estimation.
Simulated arrhythmia inducibility, sustainability, and evaluated ablation impact (lesion size, transmurality).
Utilized a GPU-accelerated monodomain solver for rapid execution.

Main Results:

The framework accurately reproduced observed activation patterns.
Successfully simulated arrhythmia inducibility and sustainability.
Retrospectively evaluated clinical radiofrequency ablation effectiveness.
Explored in silico alternative ablation strategies for minimized lesion volume.
Demonstrated compatibility with clinical practices for substrate interpretation and ablation planning.

Conclusions:

The presented computational framework provides a reproducible and clinically guided approach for post-MI VT analysis.
Personalized modeling integrating patient-specific data enhances understanding of VT substrates.
The tool supports retrospective evaluation and prospective planning of ablation strategies, optimizing outcomes.