# Computer-aided characterization of the arrhythmogenic substrate after myocardial infarction

## TL;DR

This review discusses how computer-aided techniques are improving the understanding and treatment of arrhythmias after heart attacks.

## Contribution

The paper highlights recent advances in integrating imaging, mapping, and AI for arrhythmogenic substrate analysis in post-myocardial infarction VT.

## Key findings

- High-resolution imaging and invasive mapping reveal structural and electrophysiological details of arrhythmogenic substrates.
- Computational simulations help understand how structural and functional changes lead to arrhythmias.
- AI improves risk stratification and ablation outcomes through automated analysis of substrate features.

## Abstract

Ventricular tachycardia (VT) and ventricular fibrillation remain major contributors to sudden cardiac death, with current therapies limited by our incomplete understanding of the arrhythmogenic substrate. This narrative review explores recent developments in computer-aided techniques for characterizing the arrhythmogenic substrate, focusing on post-myocardial infarction VT. High-resolution cardiac imaging now enables detailed visualization of structural abnormalities, including heterogeneous scar architecture and fatty infiltration. Sophisticated invasive mapping techniques provide insights into local electrophysiological properties, while novel non-invasive mapping approaches offer complementary views of global electrical patterns. Integration of these modalities through computational simulations allows for mechanistic insights into arrhythmia initiation and maintenance, particularly in post-myocardial infarction VT, where structural and functional substrates interact in complex ways. Emerging artificial intelligence applications enhance substrate analysis through automated feature extraction and pattern recognition, enabling more sophisticated risk stratification. These computer-aided approaches are advancing from research tools to clinical applications, with early evidence suggesting improved ablation outcomes and better risk prediction. However, significant challenges remain in validation, standardization, and clinical implementation of these innovations. This narrative review highlights recent methodological advances and clinical applications of computer-aided substrate characterization, and conceptualizes future directions towards personalized arrhythmia management, also beyond post-infarction VTs.

Graphical Abstract