A Comparative Study of AI Methods for Fetal Diagnostic Accuracy in Ultrasound

Copenhagen Academy for Medical Education and Simulation

Status: Not yet enrolling

Conditions: Fetal Growth Retardation; Fetal Growth; Fetal Macrosomia

Study type: Observational

Funder types: Other

Identifiers

NCT06268392

CT-2023-11-20-001

Details and patient eligibility

About

This study serves as a supplemental investigation to the randomized controlled SCAN-AID study (NCT0632187). This study will evaluate and compare the fetal growth estimation outcomes of AI-supported groups, expert sonographers, and control groups using a secondary AI predictive model.

Full description

The goal of this study is to compare the effects of two distinct AI methods on fetal ultrasound diagnostic accuracy. It serves as a supplementary investigation to the SCAN-AID study (NCT NCT06232187). This study aims will compare the diagnostic accuracy of two types of AI methods.

From the SCAN-AID study ultrasound novices were randomized into one of three groups with different levels of AI support: control group, AI feedback group 1 where the participants are presented with basic black box AI feedback, and AI feedback group 2 where the participants are presented with a more detailed explainable AI feedback. All the participants are tasked to perform an ultrasound fetal weight estimation (EFW) on pregnant women at gestational age 30-37. The outcomes were than compared to the expert sonographers measurements.

In this study an operator independent AI method that predicts the fetal weight is used on the SCAN-AID ultrasound examinations. .

Enrollment: 150 estimated patients

Sex: Female

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion and exclusion criteria

Pregnant women:

Inclusion Criteria:

• Singelton pregnant.
• Gestational age: 30-38 weeks
• Maternal age < 40 years

Exclusion Criteria:

• Oligo hydramnion
• Severe fetal anomaly e.g. fetal heart anomaly, omphalocele etc.
• Severe fetal macrosomia or growth restriction.

Trial design

150 participants in 4 patient groups

Expert sonographer

Description:

Expert sonographers ultrasound examination.

Control Group (CG)

Description:

Control group ultrasound examination with no AI support.

Feedback group 1 (FG1)

Description:

Feedback group 1 ultrasound examination with basic black box AI support.

Feedback group 2 (FG2)

Description:

Feedback group 2 ultrasound examination with detailed explainable AI support.