Artificial Intelligence as an Add-On Instrument in Fetal Ultrasound; Sonographers' and Obstetricians' Expectations.
Authors
Affiliations (3)
Affiliations (3)
- Department of Obstetrics and Gynecology, Division of Fetal Medicine, Leiden University Medical Center, Leiden, the Netherlands.
- Department of Medicine, Division of Cardiology, University of California San Francisco, San Francisco, California, USA.
- Department of Pediatrics, Division of Cardiology, University of California San Francisco, San Francisco, California, USA.
Abstract
Artificial intelligence applications (AIA) in fetal ultrasound are rapidly evolving, yet their integration into routine clinical practice remains limited. This study explores the attitudes, expectations and concerns of obstetric sonographers and gynecologists regarding AIA as a diagnostic aid during fetal anomaly scans. An online survey was distributed to sonographers, midwives, gynecologists and fetal medicine consultants performing screening and diagnostic fetal ultrasounds in the Netherlands. The survey included demographics, current use of artificial intelligence (AI), and 22 attitudinal statements rated on acceptance, efficiency, safety, and quality. Respondents were grouped by age, AI experience, and scan type. Among 151 respondents, 47% were sonographers performing standard anomaly screening and 49% were performing diagnostic anomaly scans at tertiary-level centers. AI was already used by 62%, primarily for automated biometry. Overall, 87% supported AIA use, yet 86% emphasized retaining final clinical authority. Concerns about data security (10%) and software manipulation (12%) were minimal. While 73% of the surveyed respondents believed AIA can improve scan completeness, only 39% expect workload reduction and 70% expect improved anomaly detection. Obstetric sonographers generally support AIA integration, anticipating a positive impact on screening outcomes. However, human decision-making remains essential. These insights may guide future implementation strategies and offer momentum to influence referral practices.