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

NCT07661433 | Recruiting FDA Device

• 2 other identifiers: 25-317422-4067
• Study Type: observational
• Target: 1,000
• Locations: 4 countries
• Sites: 5

Brief 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.

Conditions

Fetal Weight; Machine Learning; Pregnancy - Prenatal Testing; Pregnancy

Outcome Measures

Primary Outcomes (1)

• Difference in Mean Absolute Percent Error (MAPE) in fetal weight estimation

  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).

  Within 1 week of delivery, 24-42 weeks of gestation

Secondary Outcomes (1)

• Proportion of fetal weight estimates within 10% of actual birthweight

  Within 1 week of delivery, 24-42 weeks of gestation

Study Arms (1)

Pregnant Women within One Week of Delivery

Participants receive a standardized ultrasound sweep protocol and specialist-performed fetal biometry.

Diagnostic Test: AI ultrasound diagnostic tool for fetal weight estimation

Interventions

AI ultrasound diagnostic tool for fetal weight estimation DIAGNOSTIC_TEST

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.

Pregnant Women within One Week of Delivery

Eligibility Criteria

• Age: 18 Years+
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

1,000 pregnant individuals

You may qualify if:

• years of age or older
• Viable intrauterine pregnancy
• Delivery expected within one week of study procedures between 24 0/7 and 42 6/7 weeks, including participants with a scheduled induction or cesarean delivery on a known date, or those admitted in spontaneous labor
• Ability and willingness to provide written informed consent
• Willingness to comply with all study procedures

You may not qualify if:

• Maternal body mass index ≥ 40 kg/m\^2
• Multiple gestation (i.e., twins or higher order)
• Known major fetal malformation or anomaly
• Any maternal condition (medical, psychological, or social) that, in the opinion of the study team, may interfere with study participation or data integrity.

Sponsors & Collaborators

• University of North Carolina, Chapel Hill: lead
• Bill and Melinda Gates Foundation: collaborator

Study Sites (5)

Ochsner Health

New Orleans, Louisiana, 70115, United States

NOT YET RECRUITING

University of North Carolina

Chapel Hill, North Carolina, 27516, United States

RECRUITING

University of Saskatchewan

Saskatoon, Saskatchewan, Canada

NOT YET RECRUITING

University of Rwanda

Kigali, Rwanda

NOT YET RECRUITING

University Teaching Hospital

Lusaka, Zambia

NOT YET RECRUITING

MeSH Terms

Conditions

Fetal Weight

Condition Hierarchy (Ancestors)

Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Officials

• Jeffrey Stringer, MD

  University of North Carolina, Chapel Hill

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Jeffrey R Stringer, MD

CONTACT

919-962-4717; jeff_stringer@unc.edu

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 16, 2026
• First Posted: June 22, 2026
• Study Start: June 29, 2026
• Primary Completion (Estimated): December 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: July 8, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF
• Time Frame: beginning 9 and continuing for 36 months following publication
• Access Criteria: Investigator has approved IRB, IEC, or REB and an executed data use/sharing agreement with UNC

Locations

US (2); RW (1); CA (1); ZA (1)