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Updated: Aug 4, 2026
Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Published on: January 8, 2013
Efficient Patient-Specific Simulations of Ventricular Tachycardia Based on Computed Tomography-Defined Wall Thickness
Nicolas Cedilnik1, Mihaela Pop2, Josselin Duchateau3
1Université Côte d'Azur, Epione, Inria, Sophia-Antipolis, France; Institut Hospitalo-Universitaire Liryc, Bordeaux, France.
Background:
Electrophysiological mapping of ventricular tachycardia (VT) is tedious and poorly reproducible. Substrate analysis on imaging cannot explicitly display VT circuits.
Objectives:
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:
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:
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:
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.
