Sensitivity of ECG QRS Complexes to His-Purkinje Structure in Computational Heart Models

TL;DR

This study investigates how structural variations in the His-Purkinje system influence ECG QRS complex morphology using computational models, revealing that minor anatomical differences generally have limited impact on QRS features.

Contribution

It systematically analyzes the effects of multiple HPS parameters on QRS morphology and identifies key interactions affecting ECG features in computational heart models.

Findings

Most minor HPS variations minimally affect QRS features

Certain parameter combinations can cause abnormal QRS morphologies

Interactions among HPS parameters significantly influence QRS timing

Abstract

Cardiac digital twins (CDT) are emerging as a potentially transformative tool in cardiology. A critical yet understudied determinant of CDT accuracy is the His-Purkinje system (HPS), which influences ventricular depolarization and shapes the QRS complex of the electrocardiogram (ECG). Here, we quantify how structural variations in the HPS alter QRS morphology and identify which parameters drive this variability. We generated HPS structures using a fractal-tree, rule-based algorithm, systematically varying nine model parameters and assessing their effects on ten QRS-related metrics. We conducted a Sobol sensitivity analysis to quantify direct and interaction-driven contributions of each parameter to observed variability. Our results suggest that most minor changes in HPS structure exert minimal influence on individual QRS features; however, certain parameter combinations can produce abnormal QRS morphologies. Wave durations and peak amplitudes of the QRS complex exhibit low sensitivity to individual HPS parameter variations; however, we found that specific parameter combinations can result in interactions that significantly alter these aspects of QRS morphology. We found that certain HPS structures can cause premature QRS formation, obscuring P-wave formation. QRS timing variability was primarily driven by interactions among branch and fascicle angles and branch repulsivity, though other parameters also showed notable interaction effects. In addition to interactions, individual variations in the number of branches in the HPS also affected QRS timing. While future models should account for these potential sources of variability, this study indicates that minor anatomical differences between a healthy patient's HPS and that of a generic model are unlikely to significantly impact model fidelity or clinical interpretation when both systems are physiologically normal.