Peer-Reviewed Publication
Obstet Gynecol2026;147(1):97-107.January 1, 2026Journal Article
Artificial Intelligence for the Detection of Fetal Ultrasound Findings Concerning for Major Congenital Heart Defects.
Carolyn M Zelop1, Jennifer Lam-Rachlin, Alisa Arunamata, Rajesh Punn, Sarina K Behera, Matthias Lachaud, Nadine David, Greggory R DeVore, Andrei Rebarber, Nathan S Fox, Marjorie Gayanilo, Sara Garmel, Philippe Boukobza, Pierre Uzan, Hervé Joly, Romain Girardot, Laurence Cohen, Bertrand Stos, Malo De Boisredon, Eric Askinazi, Valentin Thorey, Christophe Gardella, Marilyne Levy, Miwa Geiger
1Maternal Fetal Medicine, Valley Health System, Paramus, New Jersey; the NYU School of Medicine, the Maternal Fetal Medicine Division Mount Sinai West, Icahn School of Medicine at Mount Sinai, Carnegie Imaging for Women PLLC, and the Division of Pediatric Cardiology, Icahn School of Medicine at Mount Sinai Hospital, New York, New York; the Division of Pediatric Cardiology, Department of Pediatrics, Stanford University School of Medicine, and Pediatric Cardiology, Palo Alto Medical Foundation, Sutter Health, Palo Alto, and the Fetal Diagnostic Center of Pasadena, Pasadena, California; the University Grenoble Alpes, Fetal and Pediatric Cardiology, CHU Grenoble Alpes, Grenoble, the Medical Training Center, Rouen, CEDEF - Centre Européen de Diagnostic et d'Exploration de la Femme, Le Chesnay, Groupe IMEF - Imagerie Médicale de l'Est Francilien, Rosny-sous-Bois, CARPEDIOL - Cardiologie Pédiatrique, fœtale et congénitale adulte de L'Ouest Lyonnais, Ecully; UDCFN - Unité de Dépistage de Cardiopathies Foetales et Néonatales, Bordeaux, ETCC - Exploration et Traitement des Cardiopathies Congénitales, Massy, and UE3C - Unité d'explorations cardiologiques - Cardiopathies Congénitales, Cardiology, Hopital universitaire Necker-Enfants malades, and BrightHeart, Paris, France; and Maternal Fetal Medicine, Michigan Perinatal Associates and Corewell Health, Dearborn, Michigan.
Abstract
OBJECTIVE: To evaluate the performance of an artificial intelligence (AI)-based software to identify second-trimester fetal ultrasound examinations suspicious for congenital heart defects.
METHODS: The software analyzes all grayscale two-dimensional ultrasound cine clips of an examination to evaluate eight morphologic findings associated with severe congenital heart defects. A data set of 877 exa…
Create a free account to keep reading
Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.
Want unlimited research access? See Pro plans