Accuracy of electromyometrial imaging of uterine contractions in clinical environment

Abstract Clinically, uterine contractions are monitored with tocodynamometers or intrauterine pressure catheters. In the research setting, electromyography (EMG), which detects electrical activity of the uterus from a few electrodes on the abdomen, is feasible, can provide more accurate data than these other methods, and may be useful for predicting preterm birth. However, EMG lacks sufficient spatial resolution and coverage to reveal where uterine contractions originate, how they propagate, and whether preterm contractions differ between women who do and do not progress to preterm delivery. To address those limitations, electromyometrial imaging (EMMI) was recently developed and validated to non-invasively assess three-dimensional (3D) electrical activation patterns on the entire uterine surface in pregnant sheep. EMMI uses magnetic resonance imaging to obtain subject-specific body-uterus geometry and collects uterine EMG data from up to 256 electrodes on the body surface. EMMI software then solves an ill-posed inverse computation to combine the two datasets and generate maps of electrical activity on the entire 3D uterine surface. Here, we assessed the feasibility to clinically translate EMMI by evaluating EMMI's accuracy under the unavoidable geometrical alterations and electrical noise contamination in a clinical environment. We developed a hybrid experimental-simulation platform to model the effects of fetal kicks, contractions, fetal/maternal movements, and noise contamination caused by maternal respiration and environmental electrical activity. Our data indicate that EMMI can accurately image uterine electrical activity in the presence of geometrical deformations and electrical noise, suggesting that EMMI can be reliably translated to non-invasively image 3D uterine electrical activation in pregnant women.