NIH grants $3.7 million to develop more accurate algorithms for tracking fetal development

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Fetal growth is used as a marker of health and well-being in unborn babies as well as children. But, the tools that are currently available to differentiate between a small, healthy fetus and a fetus that is small due to pathologic causes have significant limitations. What if they were improved? Would it save the health care system resources spent monitoring women who might need medical intervention because their fetuses might just be small and healthy? Would it help some women avoid the anxiety such intervention brings?

Those are the questions being addressed by Edward Chien, MD, a physician in the Division of Maternal-Fetal Medicine at Women & Infants Hospital of Rhode Island and an assistant professor of obstetrics and gynecology at The Warren Alpert Medical School of Brown University. Dr. Chien recently joined the "The National Standard for Normal Fetal Growth" study designed to develop more accurate algorithms for tracking fetal development and predicting which fetuses are abnormally small and unhealthy. He will serve as the primary investigator on this $3.7-million, two-year grant from the National Institutes of Health (NIH).

Beginning in the next few months, his team will recruit up to 700 pregnant women with low risk for prenatal complications, as well as women pregnant with twins. Because the study will evaluate growth patterns by race and ethnicity, they will recruit specific numbers of Caucasian, Asian, African American and Hispanic women. They will also recruit a specific number of obese women to study the effect of maternal obesity on fetal health and growth.

About 10% of babies born in this country are small. Like children or adults, not all of these babies are unhealthy. This study seeks to identify those individuals who are small and healthy from those who are unhealthy.

"Growth is a longitudinal measure. We hope to develop an algorithm that will look at fetal size, fetal growth and changes in the body during pregnancy, offering a standard for fetal anthropometric parameters throughout gestation," Dr. Chien explained. "This project will evaluate growth trajectories which will help to identify pathologic versus normal growth patterns in both singletons and twins."

To develop the algorithm, the researchers will use standard two-dimensional ultrasounds as well as more sophisticated three-dimensional ultrasounds during pregnancy and compare the predictions against newborn weight to see if there are characteristics visible on the ultrasounds that could be used to more accurately predict the baby's size. Current algorithms for determining newborn size can be off by up to 15%, or as much as one to two pounds.

"We know that growth restricted (small and unhealthy) babies have more complications, such as learning and physical disabilities, and they are more likely to die in utero and after birth. But it is important for us to be able to identify those babies who are smaller but healthy so we can utilize resources for monitoring complicated pregnancies. We expend a significant amount of resources on small but healthy fetuses," Dr. Chien added.

The study will also seek to discern why some babies have growth problems and others do not. Researchers will look at maternal body mass index (BMI), prenatal weight gain and nutritional habits as indicators.

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