Derren D.C.H. Rampengan, Nuril Farid Abshori, Sri Andala, Michael Owen Hogipranata, Muhammad Iqhrammullah
Background: Prenatal diagnosis of congenital heart disease (CHD) relies on imaging, yet its global research landscape remains unmapped. Objective: To conduct a global scientometric analysis of prenatal CHD diagnosis, emphasizing imaging-related trends, hotspots, and collaborations. Methods: Publications from January 1st, 2000, to November 23rd, 2025, were retrieved from Scopus. Bibliometric data, such as annual number of publications, document types, publication venues, diagnostic modalities, lesion focus, keywords, thematic evolution, and international collaborations were assessed. Polynomial modeling and Bradford's Law were used to evaluate growth and journal concentration. Results: A total of 7312 publications were identified, peaking at 544 in 2023, with a third-order polynomial showing excellent trend fit (R2 = 0.983). Original research dominated (75.1%), followed by reviews (13.2%). Fetal echocardiography emerged as the dominant modality, with diagnostic interest largely driven by hypoplastic left heart syndrome and a steadily increasing focus on coarctation, alongside intermittent attention to single-ventricle physiology. A broad shift in the research hotspots was observed from structural imaging toward genomics, functional prognostication, and AI-supported decision making. Thematic evolution confirmed this transition, highlighting growing integration of genetic risk profiling, physiological assessment, and precision planning for in-utero intervention. Global collaboration patterns were dominated by high-income countries, particularly New Zealand, Japan, Australia, and Korea. Conclusion: Imaging research on prenatal CHD has experienced significant progress, with fetal echocardiography becoming the central diagnostic platform and recent shifts toward genomics, physiological prognostication, and emerging AI-assisted decision tools. Although global collaboration is strong, it remains dominated by high-income hubs, with LMIC participation growing but still peripheral. © 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Medical Doctor Program, Faculty of Medicine, Universitas Sam Ratulangi, Manado, Indonesia; Faculty of Medicine and Health Sciences, Maulana Malik Ibrahim Islamic State University Malang, Malang, Indonesia; Department of Nursing, STIKes Muhammadiyah Lhokseumawe, Lhokseumawe, Indonesia; Medical Doctor Program, Faculty of Medicine, Brawijaya University, Malang, Indonesia; Postgraduate Program of Public Health, Universitas Muhammadiyah Aceh, Banda Aceh, Indonesia
