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NCT Number: NCT07754071

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

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.

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Key information

Age range

18 year–70 year

Sex eligibility

Female

Study type

Observational

Primary location

Nordsjællands Hospital, Department of Obstetrics and Gynecology, Hillerød, Capital Region, Denmark

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About this study

Accurate assessment of fetal lie and presentation during the third trimester is essential for obstetric management and delivery planning. Ultrasound is the gold standard for determining fetal orientation; however, the examination is highly operator-dependent and requires considerable experience to correctly identify fetal anatomy and orientation. Artificial intelligence (AI)-based navigational support systems have the potential to assist clinicians by providing real-time guidance during ultrasound examinations and improving the consistency of fetal orientation assessment.

The purpose of this study is to prospectively validate an AI-based navigational support system for determining fetal lie and presentation during routine third-trimester ultrasound examinations. The system analyzes blind ultrasound sweeps acquired along the maternal midline and automatically predicts fetal lie and presentation. AI-generated predictions will be compared with expert clinician assessment, which serves as the reference standard.

Eligible pregnant women attending third-trimester ultrasound examinations at the Fetal Medicine Department, Rigshospitalet, Slagelse - or Hillerød hospital, will be invited to participate. Following written informed consent, an expert clinician will first determine fetal lie and presentation as part of the routine ultrasound examination. The same clinician will subsequently acquire three blind ultrasound sweeps along the maternal midline. The AI navigational support system will analyze each sweep and generate predictions of fetal lie and presentation. All examinations will be completed within 5-10 minutes to minimize changes in fetal orientation between the clinical assessment and AI evaluation.

The primary objective is to evaluate the diagnostic performance of the AI system by comparing AI-generated predictions with expert clinician assessment. Primary outcome measures include overall diagnostic accuracy and agreement,

These findings will provide additional insight into the feasibility of implementing AI-assisted navigational support in routine obstetric ultrasound practice.

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • 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.

Exclusion criteria

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

Treatment and study plan

Primary outcomes

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

    Time frame: During the study ultrasound examination (approximately 5 minutes).

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

Secondary outcomes

  1. Agreement between AI predictions and expert clinician assessment.

    Time frame: During the study ultrasound examination.

    Agreement will be evaluated using Cohen's kappa coefficient.

Study contacts

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

Mary Le Ngo, MD, MD

CONTACT

[email protected]

+45 20773779

Sponsors and collaborators

Lead sponsor

Copenhagen Academy for Medical Education and Simulation

Other

Collaborators

  • Rigshospitalet, Denmark

Registry information

Official study title

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

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Aug 10, 2026
Registry last updated
Aug 10, 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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