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

2025-05-22

AI Summary

The accuracy of cardiac digital twins (CDTs) is limited by anatomical variability of the His–Purkinje system (HPS) and its impact on QRS morphology and timing in electrocardiograms. Method: We generated diverse HPS anatomies using a fractal tree algorithm and systematically quantified the influence of HPS structural parameters on QRS duration and morphology within a computational electrophysiology framework, employing multi-parameter orthogonal sampling and Sobol-based global sensitivity analysis. Contribution/Results: We identified higher-order interactions—particularly among branch count, bundle/fiber orientation angles, and repulsive forces—as the dominant mechanism underlying QRS variability; single-parameter perturbations exerted negligible effects. Specific parameter combinations induced pathological phenotypes, including premature QRS onset and P-wave obscuration, challenging conventional single-factor attribution paradigms. Crucially, minor anatomical variations within physiological ranges do not compromise clinical interpretability of CDTs. These findings provide theoretical foundations and methodological support for standardizing HPS modeling and advancing individualized CDT optimization.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Calibration & Uncertainty Quantification
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs

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.

Problem

• Quantify how His-Purkinje system (HPS) structural variations alter ECG QRS morphology
• Identify HPS parameters driving QRS variability using sensitivity analysis
• Assess impact of minor HPS anatomical differences on model fidelity

Innovation

• Fractal-tree algorithm models His-Purkinje system structure
• Sobol analysis quantifies parameter effects on QRS
• Branch angles and repulsivity dominate QRS timing