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NCT Number: NCT07661433

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.

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Key information

Conditions

Fetal Weight Body Weight Machine Learning Pathological Conditions, Signs and Symptoms Pregnancy Pregnancy - Prenatal Testing Signs and Symptoms

Age range

18 year and older

Sex eligibility

Female

Study type

Observational

Primary location

University of Saskatchewan, Saskatoon, Saskatchewan, Canada

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Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

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.

Primary outcomes

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

    Time frame: 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).

Secondary outcomes

  1. Proportion of fetal weight estimates within 10% of actual birthweight

    Time frame: Within 1 week of delivery, 24-42 weeks of gestation

    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).

Study contacts

Contact information is provided by the study sponsor or research team.

Jeffrey R Stringer, MD

CONTACT

[email protected]

919-962-4717

Sponsors and collaborators

Lead sponsor

University of North Carolina, Chapel Hill

Other

Collaborators

  • Bill and Melinda Gates Foundation

Registry information

Official study title

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

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Jun 22, 2026
Registry last updated
Jul 8, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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