Evidence map›Paper›PMID 42079966›Full record

ArticleJTCVS open2026

Artificial-intelligence electrocardiography and computed tomography mapping to guide surgical ablation of ventricular arrhythmias.

Kevin Sung, Gert Victor Pretorius, Joelle M Coletta, Mark J Kearns, Ian Glenn, Gregory K Feld, Michael M Madani, David E Krummen, Gordon Ho

Abstract read
In one paragraph

Article in JTCVS open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Kevin SungDivision of Cardiology, Section of Cardiac Electrophysiology, University of California San Diego, La Jolla, Calif.
Gert Victor PretoriusDivision of Cardiothoracic Surgery, University of California San Diego, La Jolla, Calif.
Joelle M ColettaDivision of Cardiothoracic Surgery, Veterans Affairs Medical Center San Diego, San Diego, Calif.
Mark J KearnsDivision of Cardiothoracic Surgery, University of California San Diego, La Jolla, Calif.
Ian GlennDivision of Cardiothoracic Surgery, University of California San Diego, La Jolla, Calif.
Gregory K FeldDivision of Cardiology, Section of Cardiac Electrophysiology, University of California San Diego, La Jolla, Calif.
Michael M MadaniDivision of Cardiothoracic Surgery, University of California San Diego, La Jolla, Calif.
David E KrummenDivision of Cardiology, Section of Cardiac Electrophysiology, University of California San Diego, La Jolla, Calif.
Gordon HoDivision of Cardiology, Section of Cardiac Electrophysiology, University of California San Diego, La Jolla, Calif.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Surgical arrhythmia ablation is challenging as a result of arrhythmia induction and mapping limitations in the operating room. We hypothesized that a novel preoperative workflow involving artificial intelligence (AI) electrocardiographic (ECG) and computed tomography (CT) analysis to localize arrhythmia sources and identifying myocardial scar would facilitate surgical arrhythmia ablation. Methods: We conducted a feasibility study at 2 institutions under institutional review board-approved protocols. ECG recordings of target arrhythmias were analyzed to localize ventricular tachycardia (VT) and premature ventricular complex (PVC) sources. Concurrently, cardiac CT studies underwent AI analysis to identify myocardial scar. The results were combined into a 3-dimensional model for surgical ablation planning. The primary end point was the composite of death from any cause, VT storm, sustained VT, appropriate implantable cardioverter-defibrillator shock, and (for patients who underwent PVC ablation) PVC burden reduction less than 50% at 1-year follow-up. Results: Of the 13 patients enrolled (9 PVC ablation and 4 VT ablation procedures), concomitant surgeries included mitral valve repair (4 patients, 31%), left ventricular assist device implantation (n, 3, 23%), and bypass surgery (n, 2, 15%). At a median of 1-year follow-up, 11 of 13 (84.6%) patients were free from the primary end point. PVC burden decreased from an average of 22.1 ± 15.9% to 2.6 ± 2.30% ( Conclusions: AI-based cardiac CT analysis and ECG arrhythmia mapping are feasible and facilitate surgical arrhythmia ablation, yielding significant reductions in arrhythmia burden compared with baseline. Additional studies are required to validate these findings in larger populations.

Indexed as

cardiothoracic surgerycatheter ablationECGelectroanatomic mappingPVCssurgical ablationventricular tachycardia

Identifiers

PMID42079966
PMCPMC13131197

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.