(Greyerbaby, Pixabay)
1 June 2016. A medical engineering team developed a computer model that measures muscle activity at various levels in the uterus and can help predict preterm birth. Researchers from Washington University in St. Louis, with colleagues from University of Arkansas in Little Rock, describe the model in a PLoS One article appearing at the end of March.
The team from the lab of electrical engineering professor Arye Nehorai at Washington University is seeking to provide obstetricians and gynecologists with better ways of predicting a preterm or full term pregnancy. Preterm birth, before 37 weeks of pregnancy, increases the risk of serious health problems for infants and high continuing medical costs for families. A number of past and current mathematical models of pregnancy measure electrical and physiological factors of muscles in the uterus, while more recent models track activity at the levels of individual cells and tissues, as well as organs.
The new model represents the electrophysiology of uterine contractions, beginning at the level of individual cells in uterine tissue known as myometrium, which according to the authors, represents many unanswered questions for physicians. “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,” says Nehorai in a university statement. “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.”
In previous work Nehorai and colleagues developed a computer model of uterine contractions that account for these multiple activity levels, which while helpful, still in the authors’ opinion oversimplifies the shape and structure of the uterus, and thus reduces its predictive value. The new model offers a more realistic model that measures activity at multiple levels, while incorporating MRI images rather than assuming an arbitrary shape of the uterus.
The new model also makes possible simulation of data from sensitive fetal monitoring equipment, known as a Squid Array for Reproductive Assessment, or SARA, first developed at University of Arkansas in Little Rock. SARA measures electrical signals from magnetic fields in the uterus, some quite weak, with 151 sensors. Colleagues at Arkansas-Little Rock provided SARA data for the model.
The team tested the model against real magnetomyography or MMG data, which show the model simulates magnetic field patterns at different stages of uterine contractions. These data, say the authors, make it possible to test different conditions and scenarios for the pregnancy with the model. In addition, their tests revealed factors such as orientation of the muscle fibers in the uterus that affect magnetic field patterns and electrical signals from the uterus.
The authors plan to add more complete data on uterine muscle activity with MRI images, and introduce electrochemical factors at the cellular level that can influence pregnancies. The team also plans to simulate the full contraction in their simulations, matched to real patient data.
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