Prospective Evaluation of an AI Diagnostic Ultrasound Tool for Fetal Weight Estimation

Condition(s) studied

Investigational drug(s) / intervention(s)

AI ultrasound diagnostic tool for fetal weight estimation: Participants will undergo study-specific transabdominal ultrasound acquisition using standardized abdominal sweeps of the gravid abdomen, guided by external maternal landmarks and saved as cineloop videos. The cineloop videos will be analyzed by a locked deep-learning AI diagnostic tool to generate an estimated fetal weight. The AI-generated estimate will be compared with specialist-performed fetal biometry and actual birth weight to evaluate diagnostic accuracy. The AI output is for research evaluation only and will not direct clinical management during the study.

Study summary

Purpose: The primary objective of this study is to assess the diagnostic accuracy of an AI-enabled ultrasound tool for estimating fetal weight Participants: 1,000 pregnant individuals Procedures (methods): This prospective diagnostic accuracy study will enroll 1,000 pregnant individuals within one week of anticipated delivery. At a single visit, each participant will undergo two ultrasound assessments: (1) standardized sweeps for AI analysis (performed by both specialist and nonspecialist users), (2) specialist-performed fetal biometry.

Eligibility

Primary outcome measure(s)

• Difference in Mean Absolute Percent Error (MAPE) in fetal weight estimation — Within 1 week of delivery, 24-42 weeks of gestation
  Mean of pairwise differences in absolute percent error between the AI diagnostic tool (index test) and specialist biometry (clinical reference standard), compared against actual birthweight (ground truth).

Trial sites (5)

Other trials for the same condition