- ICH GCP
- Registre américain des essais cliniques
- Essai clinique NCT07754071
Clinical Validation of an Artificial Intelligence System for De-termining Fetal Lie and Position in 3rd Trimester
Clinical Validation of an Artificial Intelligence System for Determining Fetal Lie and Position in 3rd Trimester
Aperçu de l'étude
Statut
Description détaillée
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.
Type d'étude
Inscription (Estimé)
Contacts et emplacements
Coordonnées de l'étude
- Nom: Mary Le Ngo, MD, MD
- Numéro de téléphone: +45 20773779
- E-mail: mary.van.anh.le.ngo.01@regionh.dk
Lieux d'étude
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Slagelse, Danemark, 3450
- Pas encore de recrutement
- Slagelse Hospital, Department of Obstetrics and Gynecology
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Contact:
- Kathinka Nyborg, MD
- Numéro de téléphone: 20773779
- E-mail: kany@regionsjaelland.dk
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Capital Region
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Hillerød, Capital Region, Danemark, 3400
- Pas encore de recrutement
- Nordsjællands Hospital, Department of Obstetrics and Gynecology
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Contact:
- Gitte Hedermann, Associate Professor
- Numéro de téléphone: +2520773779
- E-mail: gitte.hedermann.christensen@regionh.dk
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København Ø
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Copenhagen, København Ø, Danemark, 2100
- Recrutement
- Rigshospitalet - Department of Obstetrics and Gynecology
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Contact:
- Martin Tolsgaard, professor,, Medical doctor, Ph.D
- Numéro de téléphone: +4520773779
- E-mail: martin.groennebaek.tolsgaard@regionh.dk
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Critères de participation
Critère d'éligibilité
Âges éligibles pour étudier
- Adulte
- Adulte plus âgé
Accepte les volontaires sains
Méthode d'échantillonnage
Population étudiée
La description
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.
Plan d'étude
Comment l'étude est-elle conçue ?
Détails de conception
Cohortes et interventions
Groupe / Cohorte |
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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.
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Que mesure l'étude ?
Principaux critères de jugement
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
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Diagnostic accuracy of the AI navigational support system for determining fetal lie and presentation.
Délai: During the study ultrasound examination (approximately 5 minutes).
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Overall proportion of correct AI predictions of fetal lie and presentation compared with expert clinician assessment (reference standard).
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During the study ultrasound examination (approximately 5 minutes).
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Mesures de résultats secondaires
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
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Agreement between AI predictions and expert clinician assessment.
Délai: During the study ultrasound examination.
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Agreement will be evaluated using Cohen's kappa coefficient.
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During the study ultrasound examination.
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Collaborateurs et enquêteurs
Collaborateurs
Dates d'enregistrement des études
Dates principales de l'étude
Début de l'étude (Réel)
Achèvement primaire (Estimé)
Achèvement de l'étude (Estimé)
Dates d'inscription aux études
Première soumission
Première soumission répondant aux critères de contrôle qualité
Première publication (Réel)
Mises à jour des dossiers d'étude
Dernière mise à jour publiée (Réel)
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière vérification
Plus d'information
Termes liés à cette étude
Mots clés
Termes MeSH pertinents supplémentaires
Autres numéros d'identification d'étude
- P-2019-3101
Plan pour les données individuelles des participants (IPD)
Prévoyez-vous de partager les données individuelles des participants (DPI) ?
Description du régime IPD
Informations sur les médicaments et les dispositifs, documents d'étude
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