Aims: Non-invasive fetal electrocardiography (fECG) is a promising clinical tool yet extracting and interpreting the fetal signal remains challenging. This study performed sensitivity analysis (SA) of a maternal-fetal ventricular electrophysiology (EP) model to identify which pregnancy-related parameters most strongly influence fECG morphology.
Methods: The anatomical model was reconstructed from one maternal-fetal MRI at 38 gestational weeks. Ventricular activity was simulated for 5 seconds using the pseudo-bidomain formulation, coupling the adult ToR-ORd-dynCl and fetal-adjusted ten Tusscher-Panfilov ionic models (maternal/fetal heart rate of 60/134 bpm) with a fascicular-based model for the His-Purkinje system (HPS). Abdominal signals were recorded at four electrode locations and the fECG was extracted using independent component analysis (namely, multi-channel FastICA). SA considered 29 inputs – fetal myocardial conductivities, fetal ionic conductances, fetal HPS root locations, and the conductivity of the amniotic fluid, blood pools, maternal organs, and subcutaneous fat – varied independently (±50% or within physiological bounds). Sensitivities were quantified from finite-difference slopes between bound simulations, and normalised indices ranked parameter influence across all seven outputs considered.
Results: Fetal myocardial and blood pool conductivities were the primary determinants of QRS amplitude and duration. Ionic conductances, particularly the inward rectifier potassium current, dominated T-wave amplitude and QTc. Sodium channel conductance was the strongest driver of overall morphology changes, accounting for 48% and 68% of total normalised sensitivity pre- and post-extraction, respectively. Among fetal HPS parameters, only the apico-basal coordinates had non-negligible effects.
Conclusion: This study identified 18 of 29 parameters with negligible influence on the fECG, which can therefore be fixed, reducing model complexity for calibration. This is a necessary step toward patient-specific calibration from clinically acquired fECG, as only a limited number of parameters can realistically be constrained. Generalisability across gestational age, fetal position and orientation will require a larger virtual cohort.