Influence of Myocardial Infarction on QRS Properties: A Simulation Study
This work addresses the challenge of non-intuitively predicting MI effects on electrocardiograms for clinical diagnosis, though it is incremental as it builds on existing simulation methods.
The study systematically simulated 17 post-myocardial infarction scenarios to investigate how infarct properties affect QRS morphology, finding that QRS can identify MI and suggesting feasibility for inverse reconstruction of infarct regions from QRS data.
The interplay between structural and electrical changes in the heart after myocardial infarction (MI) plays a key role in the initiation and maintenance of arrhythmia. The anatomical and electrophysiological properties of scar, border zone, and normal myocardium modify the electrocardiographic morphology, which is routinely analysed in clinical settings. However, the influence of various MI properties on the QRS is not intuitively predictable.In this work, we have systematically investigated the effects of 17 post-MI scenarios, varying the location, size, transmural extent, and conductive level of scarring and border zone area, on the forward-calculated QRS. Additionally, we have compared the contributions of different QRS score criteria for quantifying post-MI pathophysiology.The propagation of electrical activity in the ventricles is simulated via a Eikonal model on a unified coordinate system.The analysis has been performed on 49 subjects, and the results imply that the QRS is capable of identifying MI, suggesting the feasibility of inversely reconstructing infarct regions from QRS.There exist sensitivity variations of different QRS criteria for identifying 17 MI scenarios, which is informative for solving the inverse problem.