The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice

Recruiting now

Conditions studied: Preterm Birth, Artificial Intelligence (AI) in Diagnosis

In brief

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.

Key facts

Study ID

NCT07598097

Run by

Rigshospitalet, Denmark

People needed

2000

Starts

2026-03-11

Expected to finish

2027-02-01

Last updated by the study team

2026-05-20

Who can join

Age: 18 and older. Sex: female. Healthy volunteers: not accepted.

You may qualify if…

• Pregnant women aged ≥18 years
• Attending routine second-trimester scan (and scheduled transvaginal cervical assessment per local protocol/workflow)

You may not qualify if…

• 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

Where it is running

• Rigshospitalet, Copenhagen Univeristy Hospital — Copenhagen, Denmark (enrolling)

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.