The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexFemale
Age18+
SponsorRigshospitalet, Denmark
About this trial
This study prospectively evaluates whether the performance of an already-developed artificial intelligence (AI) model for predicting spontaneous preterm birth changes when cervical ultrasound images are obtained using different ultrasound image settings.
The primary research question is whether the AI model performs differently across images acquired with different imaging settings.
Eligibility criteria
Qualifiers
Pregnant women aged ≥18 years
Attending routine second-trimester scan (and scheduled transvaginal cervical assessment per local protocol/workflow)
Disqualifiers
Absence of transvaginal cervical assessment at the second-trimester scan
Missing follow-up data on pregnancy outcome (gestational age at delivery)
Inadequate image quality or missing required cervical ultrasound image
Trial design
Treatments tested in this trial
- Cervical ultrasound image acquisition
Treatment groups
2,000 Participants
are divided into 1 treatment groupSponsors and collaborators
Rigshospitalet, Denmark
Lead sponsor
Department of Computer Science, University of Copenhagen, Denmark
Collaborator
Technical University of Denmark
Collaborator
Sundhedsdonationer
Collaborator
Source ClinicalTrials.gov