Assessing Demographic Biases in Deep Learning Model for Fetal Growth Estimation in Clinical Practice. Patients Eligible for Inclusion Are Women with a Gestational Age Between 24-42 Weeks Undergoing a Third-trimester Growth Scan. the Image Data from the Scan Are Used to Calculate Fetal Weight.

NCT06314178 | Completed

• 1 other identifier: p-2024-15469
• Study Type: observational
• Target: 185
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study is to compare a new artificial intelligence (AI) feedback tool with the traditional method for estimating fetal weight during ultrasound scans on pregnant women between 24-42 weeks of gestation. The study aims to investigate the presence of demographic bias in the AI model. The demographic factors examined in the study include Body Mass Index (BMI), the number of births, fetal age, mother\'s age, fetal sex, and the presence of preeclampsia. Moreover, the study will compare the accuracy of the AI model and the Hadlock model, a fetal growth formula, in estimating fetal weight. Participants will have their ultrasound scans pseudonymized and securely stored on password-protected removable drives, ensuring their identity and privacy are maintained. Afterward, the ultrasound data will be sent to the Technical University of Denmark (DTU), where the AI model will analyze the images to estimate fetal weight.

Conditions

Pregnancy Complications

Outcome Measures

Primary Outcomes (1)

• Demographic biases

  The primary objective is to investigate potential demographic biases inherent in the deep learning model developed for estimating fetal growth in clinical practice. This is achieved by comparing the relative error between fetal weight at scan time (this value is extrapolated from the birth weight using the Marsal growth curve) and estimations from the Hadlock formula and the deep learning model.

  From enrollment to the birth of the child

Secondary Outcomes (1)

• Comparing the accuracy of the Hadlock formula and the AI model

  From enrollment to the birth of the child

Study Arms (1)

Pregnant women between 24-42 weeks of gestation

No interventions

Eligibility Criteria

• Gender Eligibility Details: Pregnant women between 24-42 weeks of gestation.
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Department of Prenatal Examinations at Rigshospitalet, Copenhagen, Denmark.

You may qualify if:

• Women with gestational age between 24-42 weeks undergoing a third-trimester growth scan.

You may not qualify if:

• Women with multiple pregnancies.

Sponsors & Collaborators

• Copenhagen Academy for Medical Education and Simulation: lead

Study Sites (1)

Copenhagen University Hospital, Rigshospitalet

Copenhagen, Denmark

Location

Related Publications (1)

• Salomon LJ, Alfirevic Z, Da Silva Costa F, Deter RL, Figueras F, Ghi T, Glanc P, Khalil A, Lee W, Napolitano R, Papageorghiou A, Sotiriadis A, Stirnemann J, Toi A, Yeo G. ISUOG Practice Guidelines: ultrasound assessment of fetal biometry and growth. Ultrasound Obstet Gynecol. 2019 Jun;53(6):715-723. doi: 10.1002/uog.20272.

  PMID: 31169958 BACKGROUND

MeSH Terms

Conditions

Pregnancy Complications

Condition Hierarchy (Ancestors)

Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: March 6, 2024
• First Posted: March 15, 2024
• Study Start: July 1, 2024
• Primary Completion: August 30, 2024
• Study Completion: November 30, 2024
• Last Updated: December 4, 2024

Record last verified: 2024-12

Locations

DK (1)