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

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.