Date of Award

Spring 5-2020

Author's School

McKelvey School of Engineering

Author's Department

Biomedical Engineering

Degree Name

Doctor of Philosophy (PhD)

Degree Type



Clinically, uterine contraction and labor progression are monitored via tocodynamometers (TOCO) or intrauterine pressure catheters (IUPC). However, these clinical tools measure the crude pressure information and have limit specificity and accuracy in differentiating the contractions, whether they are functional or dysfunctional for delivery. Although electromyography/electrohysterography can measure uterine electrical activity using a few electrodes on the abdomen, this method lacks sufficient spatial resolution and coverage and thus cannot accurately measure the exact location of electrical initiation and location-specific propagation patterns of uterine contractions.

To comprehensively assess three-dimensional uterine electrical activation patterns, in this work, we develop a noninvasive imaging modality, electromyometrial imaging (EMMI), which combines detailed body surface electrical recordings with body-uterus geometry derived from magnetic resonance images to image the three-dimensional uterine contractions at high spatial and temporal resolutions. We first use a sheep model to assess the validity of the biophysical and mathematical model underlying EMMI. The reconstruction accuracy of EMMI is evaluated by comparing the electrical activation patterns reconstructed from EMMI with those measured with electrodes placed directly on the uterine surface. The robustness of EMMI is demonstrated with a simulation study by assessing the reconstruction accuracy under the condition with a Gaussian-distributed geometrical/electrical noise adding to the electrical signals and the body-uterus geometries. The validation study indicates that EMMI can noninvasively, safely, accurately, robustly, and feasibly image three-dimensional uterine electrical activation during contractions in sheep and suggests that similar results might be obtained in the clinical setting.

Then, we assess 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 develop 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. This work indicates 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 noninvasively image 3D uterine electrical activation in pregnant women.

Based on the supports from the validation studies in the sheep model, we next translate EMMI for use in pregnant women to characterize the 3D spatiotemporal activation dynamics of human uterine contractions in the clinical environment. By imaging twenty-five contractions from patients at different phases of first stage labor, we find that partial myometrium is activated during the uterine contractions measured at the early stage of the labor. The percentage of the activated myometrium contributing to the uterine contraction measured by TOCO or IUPC clinically increases as the labor progresses. Other EMMI-derived activation parameters, including activation duration, synchronization ratio, and slow conduction ratio, characterize the various activation dynamics within the activated myometrium and align closely with labor progression. We find that the early activated uterine sites are different from contraction to contraction, suggesting the absence of a fixed, cardiac-like pacemaker in the uterus. Similar to the negative correlation between activation time and action potential duration reported in normal myocardium activation, we find that the earlier activated myometrium has longer activation duration in our patients. Our preliminary findings suggest EMMI holds promise to provide new insights into human myometrium electrical maturation and improve the clinical management of human labor.

After the analysis of the whole EMG bursts with EMMI, we then develop a spike-based analysis method to assess the dynamic propagation patterns of the action potentials during an EMG burst. We analyze 25 independent EMG bursts, including 18667 activation maps of the action potentials, acquiring from 3 nulliparous patients during active labor. Then we use a k-means clustering, Markov chain modeling, and the linear modeling to assess central electrical propagation patterns and the variety of the dominant propagation patterns at different labor phases. This work shows an increase of propagation pattern from the inferior to superior exists when the labor is near to delivery, which may enable further investigations of the underlying mechanism of the uterine contractions and improve the understanding of the labor progress.

At last, we develop a spatial-dependent (SP) regularization method that considers both body-uterus eccentricity and EMG noise to improve the reconstruction accuracy of EMMI. Current EMMI software uses a zero-order Tikhonov method with a mean composite residual and smoothing operator (CRESO) to stabilize the underlying ill-posed inverse computation. However, this method is empirical and implements a global regularization parameter over all uterine sites, which is sub-optimal for EMMI given the severe eccentricity of body-uterus geometry. We use electrical signals simulated with spherical and realistic geometry models to compare the reconstruction accuracy of the SP method to those of the CRESO and the L-Curve methods. The SP method reconstructs electrograms and potential maps more accurately than the other methods, especially in cases of high eccentricity and noise contamination. Thus, the SP method should facilitate the clinical use of EMMI and can be used to improve the accuracy of other electrical imaging modalities, such as Electrocardiographic Imaging.


English (en)


Anders E. Carlsson; Yong Wang

Committee Members

Sarah K. England Shankar Mukherji Mikhail Tikhonov

Available for download on Saturday, June 25, 2050