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RecruitingNCT07598097Updated May 20, 2026

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

An observational study in Preterm Birth and Artificial Intelligence (AI) in Diagnosis, sponsored by Rigshospitalet, Denmark. Recruiting at 1 site in Denmark. Open to female participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-05-20.

Sponsored by Rigshospitalet, Denmark · Observational

From the registry’s dates

  • Started Mar 2026; still recruiting 6 months later.
Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
2,000
Ages
18 Years and older
Sex
Female
01

Study summary

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.

02

Conditions studied

  • Preterm Birth
  • Artificial Intelligence (AI) in Diagnosis

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Keywords

  • Preterm birth
  • Premature birth
  • Artificial intelligence
  • Deep learning
  • Image acquisition
  • Diagnostic accuracy
  • Cervical ultrasound
  • Prospective validation
03

In context

Premature Birth

2,554 studies on the registry are indexed under Premature Birth; 498 are open to participants now.

This study's planned enrollment of 2,000 is above the median of 112 across 777 observational studies indexed under Premature Birth.

Browse Premature Birth studies →

Lead sponsor

Rigshospitalet, Denmark is the lead sponsor of 1,017 studies on the registry; 183 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
Female
Sampling method
Non-probability sample

Study population

Pregnant women attending routine second-trimester scan at Rigshospitalet from March to September, 2026.

Inclusion criteria

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

Exclusion criteria

Exclusion Criteria:

  • 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
05

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
2,000 participants (estimated)
Patient registry
No

Groups and cohorts

  • 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).

    Other: Cervical ultrasound image acquisition

Interventions

  • OtherCervical ultrasound image acquisition

    Acquisition of cervical ultrasound images with variation in image acquisition parameters.

06

What researchers measure

Primary outcomes

  1. Spontaneous preterm birth <37+0 weeks

    Birth \<37+0 weeks after spontaneous onset of labor (with or without preterm prelabor rupture of membranes \[PPROM\]), regardless of mode of delivery, and excluding medically indicated (iatrogenic) preterm births without spontaneous onset.

    Time frame: At delivery.

Secondary outcomes

  1. Spontaneous preterm birth <34+0 and <32+0 weeks

    Time frame: At delivery.

Other outcomes

  1. Any preterm birth (including medically indicated)

    Time frame: At delivery.

  2. Time-to-delivery from scan

    Time frame: From second-trimester scan until delivery.

07

Study locations

1 of 1 sites recruiting
08

References and documents

Individual participant data

Plan to share: Undecided

No publications or documents are linked to this record.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on May 20, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07598097
Lead sponsor
Rigshospitalet, Denmark
Collaborators
Department of Computer Science, University of Copenhagen, Denmark, Technical University of Denmark, Sundhedsdonationer
Responsible party
Emilie Pi Fogtmann Sejer (Principal Investigator, Rigshospitalet, Denmark) — Principal investigator
First posted
May 20, 2026
Start date
Mar 11, 2026
Primary completion
Jan 2027 (estimated)
Completion
Feb 2027 (estimated)
Last update
May 20, 2026

Study contacts

Emilie Pi F Sejer, MD
Contact
emilie.pi.fogtmann.sejer.01@regionh.dk
0045 28890690
Martin G Tolsgaard, MD, PhD, DMSc
study chair · Department of Obstetrics and Gynecology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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