Fetal WeightkrittenhouseNCT07661433
Prospective Evaluation of an AI Diagnostic Ultrasound Tool for Fetal Weight Estimation
A study testing AI ultrasound diagnostic tool for fetal weight estimation in people with Fetal Weight and Pregnancy, run by University of North Carolina, Chapel Hill at 6 sites in 4 countries.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Fetal Weight, Pregnancy, Machine Learning
- What is being tested?
- AI ultrasound diagnostic tool for fetal weight estimation
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,000 participants
- Where
- 6 sitesin 4 countries
- Study dates
- 29 Jun 2026to Dec 2026
- Phase
- Interventional
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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.
Trial locations and contacts
6 sites in 4 countries. Contact the study team or a site near you to ask about taking part.
6 sites in 4 countries
United States3 sites, 3 recruiting
- Recruiting
University of North Carolina
Chapel Hill, North Carolina, 27516
Katelyn J Rittenhouse, MD, 919-966-5281, katelyn_rittenhouse@med.unc.edu
Jeffrey S.A. Stringer, MD, 919-966-5281, jeffrey_stringer@med.unc.edu
- Not yet recruiting
The Ohio State University
Columbus, Ohio, 43210
Kartik Venkatesh, MD, PhD, 614-293-4276, kartik.venkatesh@osumc.edu
- Not yet recruiting
Ochsner Health
New Orleans, Louisiana, 70115
Will Williams, MD, 504-842-5574, frank.williams2@ochsner.org
Canada1 site, 1 recruiting
- Not yet recruiting
University of Saskatchewan
Saskatoon, Saskatchewan
Scott Adams, MD, PhD, (306) 655-2402, scott.adams@usask.ca
Rwanda1 site, 1 recruiting
- Not yet recruiting
University of Rwanda
Kigali
Stephen Rulisa, MD, PhD, +250788571436, s.rulisa@gmail.com
Zambia1 site, 1 recruiting
- Recruiting
University Teaching Hospital
Lusaka
Margaret Kasaro, MBChB, MMed, MSc, +260963223210, margaret.kasaro@unclusaka.org
About this study
Official title: 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.
- Being tested
- AI ultrasound diagnostic tool for fetal weight estimation
- Medical subject headings
- Fetal Weight
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI ultrasound diagnostic tool for fetal weight estimationDiagnostic 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.
| Study group | Role | What they receive |
|---|---|---|
| Fetal weight estimation by AI vs. specialist biometry | Experimental | Participants receive a standardized ultrasound sweep protocol and specialist-performed fetal biometry within one week of delivery Receives: Diagnostic Test: AI ultrasound diagnostic tool for fetal weight estimation |
What is being measured
The primary outcome is the main question the study is designed to answer.
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).
Measured: Within 1 week of delivery, 24-42 weeks of gestation
Secondary outcomes (1)
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).
Measured: Within 1 week of delivery, 24-42 weeks of gestation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Jun 2026
- Study start29 Jun 2026
- Primary completionDec 2026 (estimated)
- Study completionDec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Fetal WeightStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of North Carolina, Chapel Hill
- Sponsor type
- University, hospital or other
- Collaborators
- Bill and Melinda Gates Foundation, NCInnovation
- Responsible party
- Sponsor
- Investigators
- Katelyn J Rittenhouse, MD, Principal investigator, University of North Carolina, Chapel Hill
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07661433
- Sponsor's protocol ID
- 25-3174
- Other IDs
- 22-4067, 802481-2821, #73
- Acronym
- krittenhouse
- Status last verified
- Jun 2026
- First submitted
- 16 Jun 2026
- Last updated
- 6 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- Yes: 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.