Cardiac MRI Oversampling in Heart Digital Twins Improves Preprocedure Ventricular Tachycardia Identification in Postinfarction Patients

Abstract

Background

Ventricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients after myocardial infarction. Radiofrequency catheter ablation (RFA) is a modestly effective treatment of VT, but it has limitations and risks. Cardiac magnetic resonance (CMR)–based heart digital twins have emerged as a useful tool for identifying VT circuits for RFA treatment planning. However, the CMR resolution used to reconstruct these digital twins may impact VT circuit predictions, leading to incorrect RFA treatment planning.

Objectives

This study sought to predict RFA targets in the arrhythmogenic substrate using heart digital twins reconstructed from both clinical and high-resolution 2-dimensional CMR datasets and compare the predictions.

Methods

High-resolution (1.35 × 1.35 × 3 mm), or oversampled resolution (Ov-Res), short-axis late gadolinium–enhanced CMR was acquired by combining 2 subsequent clinical resolution (Clin-Res) (1.35 × 1.35 × 6 mm) short-axis late gadolinium–enhanced CMR scans from 6 post–myocardial infarction patients undergoing VT ablation and used to reconstruct a total of 3 digital twins (1 Ov-Res, 2 Clin-Res) for each patient. Rapid pacing was used to assess VT circuits and identify the optimal ablation targets in each digital twin. VT circuits predicted by the digital twins were compared with intraprocedural electroanatomic mapping data and used to identify emergent VT.

Results

The Ov-Res digital twins reduced partial volume effects and better predicted unique VT circuits compared with the Clin-Res digital twins (66.6% vs 54.5%; P < 0.01). Only the Ov-Res digital twin successfully identified emergent VT after a failed initial ablation.

Conclusions

Digital twin infarct geometry and VT circuit predictions depend on the magnetic resonance resolution. Ov-Res digital twins better predict VT circuits and emergent VT, which may improve RFA outcomes.