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

Z 32503 - Prospective Evaluation of an AI Diagnostic Ultrasound Tool for Fetal Weight Estimation

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Pregnancy; Machine Learning; Fetal Weight; Pregnancy - Prenatal Testing
• Intervention / Treatment: Diagnostic test: AI ultrasound diagnostic tool for fetal weight estimation

• Study Type: Observational
• Enrollment (Estimated): 1000

Contacts and Locations

• Study Contact: Name: Jeffrey R Stringer, MD; Phone Number: 919-962-4717; Email: jeff_stringer@unc.edu

Study Locations

• Canada
  • Saskatchewan
    • Saskatoon, Saskatchewan, Canada
      • University of Saskatchewan
      • Contact: Scott Adams, MD, PhD; Phone Number: (306) 655-2402; Email: scott.adams@usask.ca
• Rwanda
  • Kigali, Rwanda
    • University of Rwanda
    • Contact: Stephen Rulisa, MD, PhD; Phone Number: +250788571436; Email: s.rulisa@gmail.com
• United States
  • Louisiana
    • New Orleans, Louisiana, United States, 70115
      • Ochsner Health
      • Contact: Will Williams, MD; Phone Number: 504-842-5574; Email: frank.williams2@ochsner.org
  • North Carolina
    • Chapel Hill, North Carolina, United States, 27516
      • University of North Carolina
      • Contact: Katelyn J Rittenhouse, MD; Phone Number: 919-966-5281; Email: katelyn_rittenhouse@med.unc.edu
      • Contact: Jeffrey S.A. Stringer, MD; Phone Number: 919-966-5281; Email: jeffrey_stringer@med.unc.edu
• Zambia
  • Lusaka, Zambia
    • University Teaching Hospital
    • Contact: Margaret Kasaro, MBChB, MMed, MSc; Phone Number: +260963223210; Email: margaret.kasaro@unclusaka.org

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

1,000 pregnant individuals

Description

Inclusion Criteria:

• 18 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

Exclusion Criteria:

• 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.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

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; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
Proportion of fetal weight estimates within 10% of actual birthweight	Between-method difference in the proportion of estimates within 10% of actual birthweight (ground truth) for the AI diagnostic tool (index test) versus specialist biometry (clinical reference standard).	Within 1 week of delivery, 24-42 weeks of gestation

Collaborators and Investigators

• Sponsor: University of North Carolina, Chapel Hill
• Collaborators: Bill and Melinda Gates Foundation
• Investigators: Principal Investigator: Jeffrey Stringer, MD, University of North Carolina, Chapel Hill

Study record dates

Study Major Dates

• Study Start (Estimated): June 1, 2026
• Primary Completion (Estimated): December 1, 2026
• Study Completion (Estimated): December 1, 2026

Study Registration Dates

• First Submitted: June 16, 2026
• First Submitted That Met QC Criteria: June 16, 2026
• First Posted (Actual): June 22, 2026

Study Record Updates

• Last Update Posted (Actual): June 25, 2026
• Last Update Submitted That Met QC Criteria: June 22, 2026
• Last Verified: June 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Body Weight; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Fetal Weight
• Other Study ID Numbers: 25-3174; 22-4067 (Other Grant/Funding Number: Bill and Melinda Gates)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Deidentified individual data that supports the results will be shared beginning 9 and continuing for 36 months following publication provided the investigator who proposes to use the data has approval from an Institutional Review Board (IRB), Independent Ethics Committee (IEC), or Research Ethics Board (REB), as applicable, and executes a data use/sharing agreement with UNC.
• IPD Sharing Time Frame: beginning 9 and continuing for 36 months following publication
• IPD Sharing Access Criteria: Investigator has approved IRB, IEC, or REB and an executed data use/sharing agreement with UNC
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; ICF

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes