Clinical Performance Evaluation of the Artificial Intelligence (AI)/ Machine Learning (ML) Technologies Utilized by the Origin Medical EXAM ASSISTANT

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Total Enrollment

551 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-03-19

Study Completion Date

2025-05-19

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

A multicenter study will be conducted to assess the role of the AI/ML technologies of Origin Medical EXAM ASSISTANT (OMEA) in interpreting first-trimester fetal ultrasound examinations (11 weeks 0 days - 13 weeks 6 days). The performance of the AI-based system will be compared against the ground truth provided by an independent reading panel of maternal-fetal medicine physicians.

Related Clinical Trials

Explore similar clinical trials based on study characteristics and research focus.

SELF-GYN1 (Sonograms Enable Looking Forward- Get Your iNformation 1 Trial)

NCT05443698

Fertility Risk

COMPLETED NA

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

Pregnancy Complications

COMPLETED

Human-AI Collaborative Intelligence for Improving Fetal Flow Management

NCT06371859

Healthy

RECRUITING NA

Optimization of Fetal Biometry With 3D Ultrasound and Image Recognition

NCT03812471

Pregnancy Related

COMPLETED NA

BIOmetric MEasurements in Diagnostics: Comparison of EXperts and IA-assisted Residents

NCT06892327

Pregnancy

COMPLETED

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Study Brief:

A multicenter, prospective observational study shall be conducted for the performance assessment and validation of the AI/ML technologies used in OMEA for the automated assessment of the first-trimester standard fetal ultrasound examinations. A prospective dataset of at least n=289 fetal ultrasound examinations shall be collected from pregnant participants with 11 weeks 0 days to 13 weeks 6 days weeks of gestational age (first trimester).

Study Objectives:

This study aims to evaluate the performance of the Artificial Intelligence (AI) / Machine Learning (ML) technologies utilized in OMEA for the:

1. Automated detection of standard diagnostic views in accordance with practice guidelines;
2. Automated verification of quality criteria required for the interpretation of diagnostic views in accordance with practice guidelines;

Note: Quality criteria can pertain to the following:
1. Presence/Absence of anatomical landmarks/structures identified within the diagnostic views detected
2. Verification of imaging parameters (e.g., magnification)
3. Verification of clinical features (e.g., orientation of the fetus)
3. Automated caliper placements to obtain measurements in accordance with practice guidelines;

Compliance with HIPAA Guidelines:

All data obtained will be de-identified according to the Health Insurance Portability and Accountability Act (HIPAA) guidelines. The sponsor will be responsible for the storage, management, and security of the de-identified data collected. To protect patient privacy, all data collected for the study undergoes de-identification, ensuring the removal of any identifiable patient information. Each data entry is assigned a unique patient number, which serves as the sole identifier for the study. The link between patient numbers and patient identifiers is securely maintained and accessible only to the principal investigator (PI) and research staff at the study site location. This link is strictly confidential and is not shared with other individuals involved in the study. Its purpose is solely for the site's reference, enabling follow-up with medical records if required. By implementing these measures, the study maintains a high level of confidentiality, safeguarding patient identities while allowing for essential record-keeping and potential future reference.

Sample Size Considerations:

Approximately 500 participants will be recruited for the study, the details of which will be captured in a statistical analysis plan that will be submitted to the FDA.

Study Design and Workflow:

The data for the study is collected in line with the Data Collection Plan and the predefined inclusion and exclusion criteria. The ARDMS performing the routine first-trimester ultrasound scan will be trained on the Image Acquisition Protocol and the Maternal Fetal Medicine (MFM)/reading physicians performing clinical benchmarking will be guided through the Reading Physician Training Manual for ensuring standardized data capture and clinical benchmarking processes for evaluating the standalone performance of the AI/ML technologies used in OMEA. All the above mentioned documents will be submitted to the FDA as part of the premarket submission review.

Phase 1: Data Capture:

At each study site, informed consent will be provided and obtained from eligible participants, and the following information will be collected.

Patient Details:

1. Fetal gestational age
2. Maternal age
3. Maternal BMI
4. Race/Ethnicity
5. Confirmation of diagnosis of fetal anomaly/syndrome prior to the study exam and post the study exam

Site Details:

1. Site location
2. Sonographer name
3. Ultrasound scanner manufacturer and series

Images and cines captured on the ultrasound machine (IUS): Registered diagnostic medical sonographers shall conduct routine first-trimester scans as per the Image Acquisition Protocol.

Images and cines captured through the capture card (ICC): A screen capture/recording of the entire exam performed by the sonographer as per the Image Acquisition Protocol will be obtained, and the images/cines required for the study that correspond to IUS will be obtained. The independent research coordinator from Origin Medical for the study will review the screen recording and identify the frame/cine for each diagnostic view (ICC) that corresponds to IUS based time stamps.

An independent quality reviewer from Origin Medical will verify whether the corresponding pair (i.e., captured on an ultrasound machine vs. obtained through screen recording) of frames/cine for each diagnostic view has been extracted or not.

Phase 2: Clinical Benchmarking and Statistical Analysis

All images/cines (IUS) from all patient exams that meet the study eligibility criteria will be pooled and randomized to prepare the ground truth by an independent Reading Panel (MFM physicians).

AI/ML technologies of OMEA interpretation of ICC The frozen AL/ML technologies used in OMEA shall interpret the images/cines (ICC).

For the sake of clarity, the ICC refers to the images/cines extracted from screen recordings using a capture card that correspond to the same images/cines as obtained by the ARDMS on the ultrasound machine.

The following tasks shall be performed by the AI/ML technologies on ICC:

1. Automated detection of standard diagnostic views;
2. Automated verification of quality criteria required for interpretation of diagnostic views ;
3. Automated caliper placements to obtain fetal measurements;

The performance of the AI/ML technologies used in the OMEA (on all ICC images/ cines that meet the study eligibility criteria) shall be compared against the ground truth for statistical analysis, i.e., against the majority consensus obtained from the Reading Panel for detection of diagnostic views, verification of quality criteria, performing fetal biometry measurements and ACEP grading of the images/cines.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

To Validate the Clinical Performance of AI/ML Technologies in First-trimester Pregnant Participants First Trimester Pregnancy

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

OTHER

Study Time Perspective

CROSS_SECTIONAL

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Images and cines captured on the ultrasound machine (IUS)

American registered diagnostic medical sonographers (ARDMS; single operator/ultrasound scan room) shall conduct routine first-trimester scans as per the Image Acquisition Protocol for the FDA Study.

Note: Patient exams that do not meet the study eligibility criteria, as identified or observed by the ARDMS, will be excluded at this stage. The exclusion criteria identified or observed by the sonographer are as follows:

1. Intrauterine fetal demise
2. Multiple gestations
3. Incorrect GA identified
4. Sonographer identifies structural abnormalities
5. Inability to continue the exam by the sonographer/patient Only the image frames and cine(s) from exams that satisfy the study inclusion criteria will be collected.

Images and cines captured through the capture card (ICC)

Intervention Type DEVICE

A screen capture/recording of the entire exam performed by the ARDMS as per the Image Acquisition Protocol for the FDA Study will be obtained, and the images/cines required for the study that correspond to IUS shall be obtained. The independent research coordinator for the study will review the screen recording and identify the frame/cine for each diagnostic view (ICC) that corresponds to IUS based on the time stamps.

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

Images and cines captured through the capture card (ICC)

A screen capture/recording of the entire exam performed by the ARDMS as per the Image Acquisition Protocol for the FDA Study will be obtained, and the images/cines required for the study that correspond to IUS shall be obtained. The independent research coordinator for the study will review the screen recording and identify the frame/cine for each diagnostic view (ICC) that corresponds to IUS based on the time stamps.

Intervention Type DEVICE

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

1. Maternal age ≥ 18 years
2. BMI \< 40 kg/m2
3. Live non-anomalous singleton pregnancies
4. Gestational age between 11 weeks + 0 days and 13 weeks + 6 days, as determined by:

Last menstrual period (LMP) or, Ultrasound report if the the LMP date is uncertain Note: Gestational age determination follows standard American College of Obstetricians and Gynecologists (ACOG) guidelines.
5. Informed consent is obtained from the participant
6. Exams obtained as per the Image Acquisition Protocol

Exclusion Criteria

1. Multiple Pregnancies
2. Cases with fetal demise or other fetal abnormalities observed/suspected after the ultrasound examination
3. Cases of planned diagnostic ultrasound follow-up exams within 2 weeks for known or suspected abnormality after the current ultrasound examination for the study

Minimum Eligible Age

18 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

Yes