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

Sponsor
Rigshospitalet, Denmark
Study ID
NCT07598097
Status
Recruiting
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Conditions

  • Artificial Intelligence (AI) in Diagnosis
  • Preterm Birth

Eligibility Criteria

Sex
FEMALE
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Cervical ultrasound image acquisition — OTHER
    Acquisition of cervical ultrasound images with variation in image acquisition parameters.

Study Details

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 Dates

First listed
May 20, 2026
Start date
Mar 11, 2026
Status verified
May 2026
Primary completion
Jan 31, 2027
Completion
Feb 28, 2027

Study Design

Enrollment
2,000 participants (estimated)

Arms

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

Primary Outcome Measure

Spontaneous preterm birth <37+0 weeks [ Time Frame: At delivery. ]

Central Contacts

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