Quantifying variabilities in cardiac digital twin models of the electrocardiogram

TL;DR

This study investigates how uncertainties in anatomical and electrical parameters affect the accuracy of cardiac digital twin models in replicating ECG signals, finding that key ECG features are relatively robust.

Contribution

It provides a comprehensive analysis of the impact of various uncertainties on ECG morphology in cardiac digital twins, highlighting their robustness.

Findings

ECG features are resilient to anatomical and electrical variability.

Residual beat-to-beat variability is narrow, indicating stable ECG morphology.

Calibration methods effectively replicate key ECG features despite uncertainties.

Abstract

Cardiac digital twins (CDTs) of human cardiac electrophysiology (EP) are digital replicas of patient hearts that match like-for-like clinical observations. The electrocardiogram (ECG), as the most prevalent non-invasive observation of cardiac electrophysiology, is considered an ideal target for CDT calibration. Recent advanced CDT calibration methods have demonstrated their ability to minimize discrepancies between simulated and measured ECG signals, effectively replicating all key morphological features relevant to diagnostics. However, due to the inherent nature of clinical data acquisition and CDT model generation pipelines, discrepancies inevitably arise between the real physical electrophysiology in a patient and the simulated virtual electrophysiology in a CDT. In this study, we aim to qualitatively and quantitatively analyze the impact of these uncertainties on ECG morphology and diagnostic markers. We analyze residual beat-to-beat variability in ECG recordings obtained from healthy subjects and patients. Using a biophysically detailed and anatomically accurate computational model of whole-heart electrophysiology combined with a detailed torso model calibrated to closely replicate measured ECG signals, we vary anatomical factors (heart location, orientation, size), heterogeneity in electrical conductivities in the heart and torso, and electrode placements across ECG leads to assess their qualitative impact on ECG morphology. Our study demonstrates that diagnostically relevant ECG features and overall morphology appear relatively robust against the investigated uncertainties. This resilience is consistent with the narrow distribution of ECG due to residual beat-to-beat variability observed in both healthy subjects and patients.