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

4. august 2026 opdateret af: Mary Le Ngo, Copenhagen Academy for Medical Education and Simulation

Clinical Validation of an Artificial Intelligence System for Determining 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.

Studieoversigt

Status

Rekruttering

Betingelser

Detaljeret beskrivelse

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.

Undersøgelsestype

Observationel

Tilmelding (Anslået)

150

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

Studiesteder

      • Slagelse, Danmark, 3450
        • Ikke rekrutterer endnu
        • Slagelse Hospital, Department of Obstetrics and Gynecology
        • Kontakt:
    • Capital Region
      • Hillerød, Capital Region, Danmark, 3400
        • Ikke rekrutterer endnu
        • Nordsjællands Hospital, Department of Obstetrics and Gynecology
        • Kontakt:
    • København Ø
      • Copenhagen, København Ø, Danmark, 2100
        • Rekruttering
        • Rigshospitalet - Department of Obstetrics and Gynecology
        • Kontakt:

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ingen

Prøveudtagningsmetode

Ikke-sandsynlighedsprøve

Studiebefolkning

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

Beskrivelse

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.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

Kohorter og interventioner

Gruppe / kohorte
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.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Diagnostic accuracy of the AI navigational support system for determining fetal lie and presentation.
Tidsramme: 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).
During the study ultrasound examination (approximately 5 minutes).

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Agreement between AI predictions and expert clinician assessment.
Tidsramme: During the study ultrasound examination.
Agreement will be evaluated using Cohen's kappa coefficient.
During the study ultrasound examination.

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Samarbejdspartnere

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

11. september 2025

Primær færdiggørelse (Anslået)

1. oktober 2026

Studieafslutning (Anslået)

1. oktober 2026

Datoer for studieregistrering

Først indsendt

4. august 2026

Først indsendt, der opfyldte QC-kriterier

4. august 2026

Først opslået (Faktiske)

10. august 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

10. august 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

4. august 2026

Sidst verificeret

1. august 2026

Mere information

Begreber relateret til denne undersøgelse

Andre undersøgelses-id-numre

  • P-2019-3101

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

IPD-planbeskrivelse

Individual participant data will not be made publicly available because the dataset contains identifiable medical imaging data and is subject to Danish data protection regulations (GDPR).

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