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Use of Artificial Intelligence for the ultrasound assessment of fetal biometry - Comparison of automated to manual measurement of estimated fetal weight

Use of Artificial Intelligence for the ultrasound assessment of fetal biometry - Comparison of automated to manual measurement of estimated fetal weight

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00036779
Enrollment
1000
Registered
2025-05-07
Start date
2025-06-01
Completion date
Unknown
Last updated
2025-10-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Fetal biometry in pregnancy

Interventions

Group 1: All pregnant patients admitted to the hospital up to 3 days before delivery.

Sponsors

Uniklinikum Frankfurt
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: Singleton, monochorionic diamnotic (MCDA) and dichorionic diamniotic (DCDA) twin pregnancies between 28+0 and 42+0 weeks of gestation

Exclusion criteria

Exclusion criteria: Monochorionic monoamniotic twin pregnancies Indication for immediate delivery Major fetal structural anomalies or aneuploidies Oligohydramnios/anhydramnios Unable to give informed consent

Design outcomes

Primary

MeasureTime frame
The primary objective of this study is to assess the accuracy of automated AI-assisted measurement of EFW versus measurement of EFW performed manually by trained clinicians on ultrasound, within 3 days before delivery, in comparison to birthweight.

Secondary

MeasureTime frame
The secondary objectives of this study include: - Comparison of fetal biometry (BPD, HC, AC, FL) in singleton and twin pregnancies between automated AI-assisted and manual biometric measurements. - Comparison of the accuracy of manual biometric measurements with birthweight performed by operators with different levels of experience, and subanalysis of the AI- assisted biometric measurements based on operator experience. - Determination of factors influencing the accuracy and duration of ultrasound estimation of fetal weight compared between AI-assisted automated ultrasound measurement technique and manual ultrasound measurements (e.g. maternal body mass index (BMI), ethnicity, etc).

Countries

Australia, France, Germany, Italy, Spain, United Kingdom, United States

Contacts

Public ContactEileen Deuster

Universitätsklinikum Frankfurt

eileen@deuster.eu+4915203369112

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026