By studying the electrical activity that causes childbirth contractions, researchers have developed a multiscale model they believe may aid in predicting preterm delivery.
Arye Nehorai, professor of electrical engineering and chair of the department of electrical & systems engineering at Washington University in St. Louis, and his team have developed the first 3D multiscale mathematical model of the electrophysiology of a woman’s contractions as they begin from a single cell to the myometrium, or uterine tissue, into the uterus.
“We know that the cell starts the electrical activity, but nothing is known about the positions or numbers or how they interact in different places in the uterus,” Nehorai says. “In addition, we don’t yet know the directions of the fibers in the myometrium, which is important because the electricity propagates along the muscle fibers, and that direction varies among women.”
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Using a special instrument at the University of Arkansas, the researchers applied sensors to the abdomen of 25 pregnant women. The instrument has 151 magnetometers that measure the strength of the magnetic field in the abdomen as a result of the electrical activity from a contraction. From those measurements, the team created a mathematical model that precisely replicated the electrical activity in the uterus during a contraction.
Next, the team plans to use data associated with preterm and term labor to determine what parameters can predict between the preterm and term, Nehorai says. In addition, they will take the measurements from the machine and estimate the electrical activity and the position, number, and distribution of the electrical sources in the uterus.
“Our ultimate goal is to share this with obstetricians and gynecologists so they can take measurements and make a prediction of whether a woman will have preterm or term labor,” Nehorai says. “Creating a realistic, multiscale forward model of uterine contractions will allow us to better interpret the data of magnetomyography measurements and, therefore, shed light on the prediction of preterm labor.”
The results appear in the journal PLOS ONE.
