Female anatomies disguise ECG abnormalities following myocardial infarction: an AI-enabled modelling and simulation study

TL;DR

This study uses AI-driven modeling and simulation based on MRI data to quantify how sex-specific anatomical differences influence ECG biomarkers after myocardial infarction, revealing potential biases in diagnosis.

Contribution

It introduces a novel AI-augmented multiscale modeling approach to quantify sex-related anatomical effects on ECG biomarkers post-MI.

Findings

Female anatomies show larger infarct-electrode distances and angles, affecting ECG readings.

Anatomical differences lead to shorter QRS duration and T-peak-to-end intervals in females.

Heart position and orientation impact ECG biomarkers more than size alone.

Abstract

The electrocardiogram (ECG) is modulated by torso-heart anatomy, and this challenges patients' diagnosis and risk stratification. This study aims to quantify how torso-heart anatomical factors affect sex-differences in ECG biomarkers in acute and chronic myocardial infarction (MI). We exploit the perfect control of AI-augmented multiscale modelling and simulation, based on clinical magnetic resonance imaging (MRI) data and ECGs for model construction and validation. A cohort of 1720 torso-ventricular anatomies (50% female) was constructed from MRIs of healthy and post-MI participants in the UK Biobank study. 8600 ECG simulations were performed considering anatomical variability and 3 electrophysiological stages (healthy, acutely ischemic, and infarcted). The effect of cardiac size, position, and orientation on each ECG biomarker was quantified. Female anatomies had larger distances between the infarct and ECG electrodes (relative to cardiac size), and larger angles between the infarct normal and ECG lead axes, both primarily caused by their more superior cardiac position. This reduced ST-elevation and caused low-amplitude late depolarisation and repolarisation tails to be missed, shortening QRS duration (QRSd) and T-peak-to-end interval (TpTe). The position and orientation of the heart impacted TpTe more severely than QRSd. AI-enabled mechanistic modelling and simulation identify smaller ventricles, superior cardiac position, and different ventricular orientation as key anatomical contributors of shorter QRS and T waves, and lower ST-elevation, in female versus male anatomies. This provides a blueprint for quantifying the impact of anatomical sex differences on functional markers and enables future work in tailoring clinical guidelines considering unique patient anatomy to reduce biased outcomes.