Efficient Patient-Specific Simulations of Ventricular Tachycardia Based on Computed Tomography-Defined Wall Thickness Heterogeneity.
action potential duration
imaging
ischemic scar
simulation
ventricular tachycardia
Journal
JACC. Clinical electrophysiology
ISSN: 2405-5018
Titre abrégé: JACC Clin Electrophysiol
Pays: United States
ID NLM: 101656995
Informations de publication
Date de publication:
14 Sep 2023
14 Sep 2023
Historique:
received:
31
10
2022
revised:
20
07
2023
accepted:
02
08
2023
medline:
7
10
2023
pubmed:
7
10
2023
entrez:
7
10
2023
Statut:
aheadofprint
Résumé
Electrophysiological mapping of ventricular tachycardia (VT) is tedious and poorly reproducible. Substrate analysis on imaging cannot explicitly display VT circuits. This study sought to introduce a computed tomography-based model personalization approach, allowing for the simulation of postinfarction VT in a clinically compatible time frame. In 10 patients (age 65 ± 11 years, 9 male) referred for post-VT ablation, computed tomography-derived wall thickness maps were registered to 25 electroanatomical maps (sinus rhythm, paced, and VT). The relationship between wall thickness and electrophysiological characteristics (activation-recovery interval) was analyzed. Wall thickness was then employed to parameterize a fast and tractable organ-scale wave propagation model. Pacing protocols were simulated from multiple sites to test VT induction in silico. In silico VTs were compared to VT circuits mapped clinically. Clinically, 6 different VTs could be induced with detailed maps in 9 patients. The proposed model allowed for fast simulation (median: 6 min/pacing site). Simulations of steady pacing (600 milliseconds) from 100 different sites/patient never triggered any arrhythmia. Applying S1-S2 or S1-S2-S3 induction schemes allowed for the induction of in silico VTs in the 9 of 10 patients who were clinically inducible. The patient who was not inducible clinically was also noninducible in silico. A total of 42 different VTs were simulated (4.2 ± 2 per patient). Six in silico VTs matched a VT circuit mapped clinically. The proposed framework allows for personalized simulations in a matter of hours. In 6 of 9 patients, simulations show re-entrant patterns matching intracardiac recordings.
Sections du résumé
BACKGROUND
BACKGROUND
Electrophysiological mapping of ventricular tachycardia (VT) is tedious and poorly reproducible. Substrate analysis on imaging cannot explicitly display VT circuits.
OBJECTIVES
OBJECTIVE
This study sought to introduce a computed tomography-based model personalization approach, allowing for the simulation of postinfarction VT in a clinically compatible time frame.
METHODS
METHODS
In 10 patients (age 65 ± 11 years, 9 male) referred for post-VT ablation, computed tomography-derived wall thickness maps were registered to 25 electroanatomical maps (sinus rhythm, paced, and VT). The relationship between wall thickness and electrophysiological characteristics (activation-recovery interval) was analyzed. Wall thickness was then employed to parameterize a fast and tractable organ-scale wave propagation model. Pacing protocols were simulated from multiple sites to test VT induction in silico. In silico VTs were compared to VT circuits mapped clinically.
RESULTS
RESULTS
Clinically, 6 different VTs could be induced with detailed maps in 9 patients. The proposed model allowed for fast simulation (median: 6 min/pacing site). Simulations of steady pacing (600 milliseconds) from 100 different sites/patient never triggered any arrhythmia. Applying S1-S2 or S1-S2-S3 induction schemes allowed for the induction of in silico VTs in the 9 of 10 patients who were clinically inducible. The patient who was not inducible clinically was also noninducible in silico. A total of 42 different VTs were simulated (4.2 ± 2 per patient). Six in silico VTs matched a VT circuit mapped clinically.
CONCLUSIONS
CONCLUSIONS
The proposed framework allows for personalized simulations in a matter of hours. In 6 of 9 patients, simulations show re-entrant patterns matching intracardiac recordings.
Identifiants
pubmed: 37804259
pii: S2405-500X(23)00621-7
doi: 10.1016/j.jacep.2023.08.008
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Funding Support and Author Disclosures This study received financial support from the French government as part of the “Investments of the Future” program managed by the National Research Agency (ANR-10-IAHU-04). The authors have reported that they have no relationships relevant to the contents of this paper to disclose.