Prospective Multicenter Study to Evaluate the Performance of the Artificial Intelligence (AI)/ Machine Learning (ML) Technologies Utilized by the Origin Medical EXAM ASSISTANT
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 551
- 试验地点
- 8
- 主要终点
- To assess whether the AI/ML technologies used in OMEA can achieve an acceptable sensitivity for identifying the diagnostic view
研究概览
简要总结
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.
详细描述
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:
- Automated detection of standard diagnostic views in accordance with practice guidelines;
- Automated verification of quality criteria required for the interpretation of diagnostic views in accordance with practice guidelines;
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- Female
- 接受健康志愿者
- 是
入选标准
- •Maternal age ≥ 18 years
- •BMI < 40 kg/m2
- •Live non-anomalous singleton pregnancies
- •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.
- •Informed consent is obtained from the participant
- •Exams obtained as per the Image Acquisition Protocol
排除标准
- •Multiple Pregnancies
- •Cases with fetal demise or other fetal abnormalities observed/suspected after the ultrasound examination
- •Cases of planned diagnostic ultrasound follow-up exams within 2 weeks for known or suspected abnormality after the current ultrasound examination for the study
结局指标
主要结局
To assess whether the AI/ML technologies used in OMEA can achieve an acceptable sensitivity for identifying the diagnostic view
时间窗: 11 weeks 0 days to 13 weeks 6 days
The overall sensitivity and two-sided 95% confidence interval (CI) will be determined using data pooled across diagnostic views. Note: The participant is assessed for the primary outcome on the same day of enrollment.
To assess whether the AI/ML technologies used in OMEA can achieve an acceptable sensitivity and consistency for verifying the quality criteria of a given image
时间窗: 11 weeks 0 days to 13 weeks 6 days
The overall sensitivity and two-sided 95% confidence interval (CI) will be determined using data pooled across diagnostic views for quality criteria. Note: The participant is assessed for the primary outcome on the same day of enrollment.
To evaluate the performance of the OMEA AI/ML technologies with respect to facilitating the determination of quantitative measure of crown-rump length (CRL) and nuchal translucency (NT), complementary evaluations of agreement will be performed.
时间窗: 11 weeks 0 days to 13 weeks 6 days
The agreement and consistency of the AI/ML technologies used in OMEA to obtain quantitative measurements (i.e., CRL and NT) compared to the MFM physician average will be analyzed by applying Deming regression and Bland-Altman analysis. Note: The participant is assessed for the primary outcome on the same day of enrollment.
次要结局
- To assess the sensitivity and specificity for the detection of each of the individual diagnostic view of each of the individual quality criteria within each diagnostic view.(11 weeks 0 days to 13 week 6 days)