A Single-center Cross-sectional Study Comparing Two Image Acquisition Modalities for Second-trimester Pregnancy Screening Ultrasound

What this Trial Is About

Researchers are investigating the use of artificial intelligence (AI) to assist in second-trimester pregnancy screening ultrasounds, which are critical for assessing fetal growth and identifying structural abnormalities. The study compares the quality of images captured manually by sonographers to those automatically acquired and validated by an AI system called Live View Assist. This research aims to determine if AI-assisted imaging can match the quality standards set by the French College of Fetal Ultrasound while potentially improving efficiency and standardization during routine obstetric monitoring. The study has two groups: one where sonographers manually acquire 22 mandatory and up to 4 additional ultrasound images following standardized protocols, and another where the Live View Assist system automatically captures 20 mandatory images and possibly 2 complementary ones in real time. This AI system recognizes and freezes required fetal views, automatically validating images according to reference standards, which may reduce operator variability and save time. Participants will undergo their routine second-trimester ultrasound between 20 and 24 weeks gestation. The study evaluates image quality based on acceptability criteria over an average period of six months. Researchers will assess whether the AI tool's images meet quality standards compared to manual acquisition. This includes examining feasibility, time efficiency, and impacts on sonographers' workload. Women involved will provide informed consent and be monitored under standard clinical conditions throughout their participation.

Study Comparing Two Image Acquisition Modalities for Second-trimester Pregnancy Screening Ultrasound (Echo-IA)