Standardized 2D Ultrasound Sequences for Fetal Cardiac Screening: A Platform for AI Integration

The precise and consistent identification of fetal cardiac structures and functional flows is essential for the early diagnosis of congenital heart defects (CHDs), yet interobserver variability remains a significant challenge in clinical practice. Although fetal cardiac magnetic resonance imaging (MRI) has emerged as a valuable adjunct in selected cases, its routine use remains limited by long acquisition times, motion artifacts, and restricted availability in many centers. This underscores the need to optimize ultrasound-based techniques that can reduce reliance on MRI while still providing comprehensive and reproducible fetal cardiac assessment. This article presents a study investigating the reliability of a layered imaging approach combined with standardized B-mode and color Doppler ultrasound protocols to improve interobserver agreement in image interpretation among experts in fetal echocardiography.

A dataset comprising 209 B-mode and 205 color Doppler recordings acquired during midgestational anomaly scans (mean gestational age: 21.2 weeks) was systematically evaluated by five expert supervisors. Interobserver agreement was quantified using the prevalence-adjusted bias-adjusted kappa (PABAK) coefficient. To evaluate consistency across anatomical layers, one-way ANOVA was employed, followed by post hoc analysis where applicable.

Most anatomical structures and functional features were consistently identified across observers, certain structures posed challenges, likely owing to their smaller size, lower visibility, or greater variability in presentation.

By integrating structured imaging sequences with advanced statistical methodologies, this study explored the potential of improving diagnostic accuracy and standardization in fetal cardiac assessments, offering insights into the development of more reliable protocols for clinical applications and future research.