Clinical Validation of an Artificial Intelligence System for De-termining Fetal Lie and Position in 3rd Trimester

NCT07754071 | Recruiting

• 1 other identifier: P-2019-3101
• Study Type: observational
• Target: 150
• Locations: 1 country
• Sites: 3

Brief Summary

This prospective clinical validation study aims to evaluate the diagnostic performance of an artificial intelligence (AI)-based navigational support system for determining fetal lie and presentation during third-trimester ultrasound examinations. Following routine clinical assessment by an expert clinician, three blind ultrasound sweeps will be obtained from each participant. The AI system will generate predictions of fetal lie and presentation from each sweep, which will be compared with the expert clinician's assessment as the reference standard. The study will also explore clinician perceptions of the system's usability and potential clinical value.

Conditions

Pregnancy; Fetal Presentation; Breech Fetal Presentation; Cephalic Fetal Presentation

Keywords

fetal lie; fetal presentation; obstetric ultrasound; artificial intelligence; AI-assisted ultrasound; Navigation system; blind ultrasound sweep; third trimester pregnancy; clinical validation; Diagnostic accuracy; fetal orientation

Outcome Measures

Primary Outcomes (1)

• Diagnostic accuracy of the AI navigational support system for determining fetal lie and presentation.

  Overall proportion of correct AI predictions of fetal lie and presentation compared with expert clinician assessment (reference standard).

  During the study ultrasound examination (approximately 5 minutes).

Secondary Outcomes (1)

• Agreement between AI predictions and expert clinician assessment.

  During the study ultrasound examination.

Study Arms (1)

Prospective Clinical Validation Cohort

Pregnant women with singleton pregnancies in the third trimester (≥28+0 weeks' gestation) undergoing obstetric ultrasound examination. Participants undergo three blind ultrasound sweeps, and AI-generated predictions of fetal lie and presentation are compared with expert clinician assessment.

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Pregnant women with singleton pregnancies attending third-trimester ultrasound examinations at the Fetal Medicine Department, Rigshospitalet, Slagelse Hospital, or Hillerød Hospital.

You may qualify if:

• Pregnant women aged ≥18 years.
• Singleton pregnancy.
• Gestational age ≥28+0 weeks.
• Fetus in longitudinal lie (cephalic or breech presentation) as determined by the routine clinical ultrasound examination.
• Able to understand Danish or English.
• Able and willing to provide written informed consent.

You may not qualify if:

• Multiple pregnancy.
• Fetus in transverse lie.
• Inability to provide written informed consent.

Sponsors & Collaborators

• Copenhagen Academy for Medical Education and Simulation: lead
• Rigshospitalet, Denmark: collaborator

Study Sites (3)

Nordsjællands Hospital, Department of Obstetrics and Gynecology

Hillerød, Capital Region, 3400, Denmark

NOT YET RECRUITING

Rigshospitalet - Department of Obstetrics and Gynecology

Copenhagen, København Ø, 2100, Denmark

RECRUITING

Slagelse Hospital, Department of Obstetrics and Gynecology

Slagelse, 3450, Denmark

NOT YET RECRUITING

MeSH Terms

Conditions

Breech Presentation

Condition Hierarchy (Ancestors)

Obstetric Labor Complications; Pregnancy Complications; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases

Central Study Contacts

Mary Le Ngo, MD, MD

CONTACT

+45 20773779; mary.van.anh.le.ngo.01@regionh.dk

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Medical doctor

Study Record Dates

• First Submitted: August 4, 2026
• First Posted: August 10, 2026
• Study Start: September 11, 2025
• Primary Completion (Estimated): October 1, 2026
• Study Completion (Estimated): October 1, 2026
• Last Updated: August 10, 2026

Record last verified: 2026-08

Data Sharing

• IPD Sharing: Will not share

Locations

DK (3)