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Clinical Data Collection for Obstetric Ultrasound Algorithms

Prospective Clinical Data Collection for Developing Machine Learning-assisted Obstetric Ultrasound (MOBUS) Screening Algorithms

Status
Not yet recruiting
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06742229
Acronym
MOBUS
Enrollment
700
Registered
2024-12-19
Start date
2024-12-20
Completion date
2025-12-30
Last updated
2024-12-19

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

Conditions

Pregnancy

Keywords

Obstetrics, Gynecology, Artificial Intelligence, Machine Learning

Brief summary

The goal of this clinical trial is to * Collect ultrasound data from pregnant and non-pregnant individuals presenting to multiple study sites. * Use the collected data and ultrasound images to train and validate Artificial intelligence algorithms developed by the Sponsor Consented participants will be asked to take part in a research ultrasound scan

Detailed description

In this study pregnant and no pregnant subjects will be recruited from Obstetrics and Gynecology clinics/hospitals or from Maternal and Fetal Medicine centers. The pregnant subjects will be in Group 1 and non pregnant subjects will be in Group 2. Pregnant subjects are only recruited if they are scheduled for an obstetric standard of care scan . Both the group will undergo research scan, which is a sweep protocol using handheld FDA approved ultrasound device like Vscan. Patient chart history (no PHI), standard of care scan ultrasound images (no PHI), and research scan ultrasound images (no PHI) would be obtained from Group 1 subjects. Patient history (no PHI), research ultrasound images (no PHI) would be obtained from Group 2 subjects The data collected from this study will be used by the sponsor to develop algorithms for screening various fetal health parameters such as gestational age, placenta location, fetal heart rate, number of fetuses, fetal positions etc Th

Interventions

DEVICEResearch Ultrasound scan

Both the study groups will be asked to undergo a research scan performed by an FDA approved ultrasound device

Sponsors

Caption Health, Inc.
Lead SponsorINDUSTRY

Study design

Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE

Intervention model description

Two groups- Group 1 Pregnant and Group 2 Non Pregnant. From Group 1-Pregnant group we will obtain their standard of care scans along with the research scan whereas Non pregnant group will have only research scans

Eligibility

Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

Pregnant group (Group 1) 1. Participants aged 18 years or older at time of consent. 2. Participants with confirmed pregnancy (positive HCG urine test strip and/or a documented obstetric ultrasound scan. 3. Participants who are scheduled for or referred for a standard-of-care clinical obstetric ultrasound examination. 4. Participants who provide written consent. Non-pregnant group (Group 2) 1. Participants aged 18 years or older at time of consent. 2. Participants who are not actively pregnant (confirmed using an HCG urine test strip). 3. Participants who provide written informed consent.

Exclusion criteria

\- 1. Participants for whom participating in this study would delay or compromise care in any way. 2\. Participants who are not able to understand or provide written consent.

Design outcomes

Primary

MeasureTime frameDescription
Research sweep Ultrasound Images (Vscan ) from the participants will be assessed for quality of images and comparing with patient chart history9 monthsAll the participant's research ultrasound image will be obtained. This image will be checked for image quality on various stages of pregnancy as well as for non pregnant subjects. These images will be used to develop algorithms for measuring gestational age, placenta location etc.

Countries

United States

Contacts

Primary ContactReshma Rajan-Joy, PhD
reshma.rajan-joy@gehealthcare.com445-221-3076
Backup ContactYngvil Thomas
yngvil.thomas@gehealthcare.com312-316-5632

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026