Enhancing Fetal Cardiac Imaging With Artificial Intelligence: A Review of the Current Evidence and Future Directions.

Journal: Clinical obstetrics and gynecology
Published Date: Dec 23, 2025

Abstract

Congenital heart disease (CHD) is the most common major birth anomaly and a key cause of neonatal mortality. While early diagnosis improves outcomes, prenatal detection remains inconsistent. Artificial intelligence (AI) offers scalable solutions through automation of view acquisition, image interpretation, and functional assessment. AI has shown expert-level performance in view classification, CHD detection, and cardiac biometry. Tools like Fetal Intelligent Navigation Echocardiography, though not AI, enhance consistency and efficiency. Emerging AI modalities, including generative AI, self-supervised learning, and NLP-driven report automation, expand possibilities. Ongoing research is essential to ensure safe, equitable integration of AI into clinical workflows for improved CHD diagnosis worldwide.

Authors

  • Juliana G Martins
    Department of Obstetrics and Gynecology, Macon and Joan Brock Virginia Health Sciences at ODU, Norfolk, Virginia.
  • Rebecca Horgan
    Macon & Joan Brock Virginia Heath Sciences at Old Dominion University, Norfolk, Virginia; the Department of Obstetrics and Gynecology, Koç University School of Medicine, and the Faculty of Engineering, Computer Science and Engineering, Koç University, Istanbul, Turkey.
  • Elena Sinkovskaya

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