Research highlights AI’s potential to help doctors detect congenital heart defects

Congenital heart defects (abnormalities of the heart that are present at birth) are the most common type of birth defect and, according to the Centers for Disease Control and Prevention, about 1 in 4 babies born with a heart defect has a diagnosis that is severe enough to require surgery or other medical intervention within the first year of life. Despite advances in prenatal care, the detection rate of congenital heart defects during routine ultrasounds remains suboptimal.

In a new study to be presented today at the Society for Maternal-Fetal Medicine’s (SMFM) annual meeting, The Pregnancy Meeting, researchers will unveil findings that suggest that AI can help clinicians better detect congenital heart defects on routine prenatal ultrasounds.

In the study, a group of physicians with experience ranging from one to 30+ years reviewed 200 ultrasounds. A total of 14 OB-GYNs and maternal-fetal medicine subspecialists reviewed each ultrasound, both with and without the use of an AI-based software program. The data were compared to determine whether the clinicians’ ability to detect cases suspicious for congenital heart defects improved with the assistance of the software.

Regardless of a physician’s years of experience or subspecialty training, results showed that the AI system significantly improved a clinician’s ability to detect cases suspicious for congenital heart defects.

Secondarily, results also found clinicians’ confidence level in detecting congenital heart defects improved and it took them less time to determine whether a case was suspicious or not.

“At least half of prenatal ultrasounds in the United States are being looked at by non-specialists, medical professionals—including OB-GYNs—who may not be trained in prenatal ultrasound. That accounts for why the ability to detect congenital heart defects is still quite low, even in developed countries like the U.S.,” says the study’s lead author Jennifer Lam-Rachlin, MD, a maternal-fetal medicine subspecialist.

Lam-Rachlin is the director of fetal echocardiography at Carnegie Imaging for Women and assistant clinical professor in the Raquel and Jaime Gilinski Department of Obstetrics, Gynecology and Reproductive Science at the Icahn School of Medicine at Mount Sinai West in New York City.

“Our findings show that the AI-based software significantly improved detection of ultrasounds that were suspicious for congenital heart defects not only among OB-GYNs but also among maternal-fetal medicine subspecialists. This has a tremendous impact in terms of neonatal outcomes and has the potential to change clinical practice.”

“Most congenital heart defects occur in pregnancies that are considered low risk, which means the pregnant person is most likely being seen by an OB-GYN versus a maternal-fetal medicine subspecialist who has more experience in detecting congenital heart defects,” says Christophe Gardella, Ph.D., chief technical officer for BrightHeart, the Paris-based manufacturer of the AI-based software.

“We built our AI software with experts to help elevate the detection rate, even among non-specialists, and drive earlier diagnosis to improve outcomes.”

Congenital heart defects (abnormalities of the heart that are present at birth) are the most common type of birth defect and, according to the Centers for Disease Control and Prevention, about 1 in 4 babies born with a heart defect has a diagnosis that is severe enough to require surgery or other medical intervention within the first year of life. Despite advances in prenatal care, the detection rate of congenital heart defects during routine ultrasounds remains suboptimal.

In a new study to be presented today at the Society for Maternal-Fetal Medicine’s (SMFM) annual meeting, The Pregnancy Meeting, researchers will unveil findings that suggest that AI can help clinicians better detect congenital heart defects on routine prenatal ultrasounds.

In the study, a group of physicians with experience ranging from one to 30+ years reviewed 200 ultrasounds. A total of 14 OB-GYNs and maternal-fetal medicine subspecialists reviewed each ultrasound, both with and without the use of an AI-based software program. The data were compared to determine whether the clinicians’ ability to detect cases suspicious for congenital heart defects improved with the assistance of the software.

Regardless of a physician’s years of experience or subspecialty training, results showed that the AI system significantly improved a clinician’s ability to detect cases suspicious for congenital heart defects.

Secondarily, results also found clinicians’ confidence level in detecting congenital heart defects improved and it took them less time to determine whether a case was suspicious or not.

“At least half of prenatal ultrasounds in the United States are being looked at by non-specialists, medical professionals—including OB-GYNs—who may not be trained in prenatal ultrasound. That accounts for why the ability to detect congenital heart defects is still quite low, even in developed countries like the U.S.,” says the study’s lead author Jennifer Lam-Rachlin, MD, a maternal-fetal medicine subspecialist.

Lam-Rachlin is the director of fetal echocardiography at Carnegie Imaging for Women and assistant clinical professor in the Raquel and Jaime Gilinski Department of Obstetrics, Gynecology and Reproductive Science at the Icahn School of Medicine at Mount Sinai West in New York City.

“Our findings show that the AI-based software significantly improved detection of ultrasounds that were suspicious for congenital heart defects not only among OB-GYNs but also among maternal-fetal medicine subspecialists. This has a tremendous impact in terms of neonatal outcomes and has the potential to change clinical practice.”

“Most congenital heart defects occur in pregnancies that are considered low risk, which means the pregnant person is most likely being seen by an OB-GYN versus a maternal-fetal medicine subspecialist who has more experience in detecting congenital heart defects,” says Christophe Gardella, Ph.D., chief technical officer for BrightHeart, the Paris-based manufacturer of the AI-based software.

“We built our AI software with experts to help elevate the detection rate, even among non-specialists, and drive earlier diagnosis to improve outcomes.”