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Clinical Validation of an Artificial Intelligence System for De-termining Fetal Lie and Position in 3rd Trimester

2026年8月4日 更新者：Mary Le Ngo、Copenhagen Academy for Medical Education and Simulation

Clinical Validation of an Artificial Intelligence System for Determining Fetal Lie and Position in 3rd Trimester

This prospective clinical validation study aims to evaluate the diagnostic performance of an artificial intelligence (AI)-based navigational support system for determining fetal lie and presentation during third-trimester ultrasound examinations. Following routine clinical assessment by an expert clinician, three blind ultrasound sweeps will be obtained from each participant. The AI system will generate predictions of fetal lie and presentation from each sweep, which will be compared with the expert clinician's assessment as the reference standard. The study will also explore clinician perceptions of the system's usability and potential clinical value.

研究概览

地位

招聘中

条件

详细说明

Accurate assessment of fetal lie and presentation during the third trimester is essential for obstetric management and delivery planning. Ultrasound is the gold standard for determining fetal orientation; however, the examination is highly operator-dependent and requires considerable experience to correctly identify fetal anatomy and orientation. Artificial intelligence (AI)-based navigational support systems have the potential to assist clinicians by providing real-time guidance during ultrasound examinations and improving the consistency of fetal orientation assessment.

The purpose of this study is to prospectively validate an AI-based navigational support system for determining fetal lie and presentation during routine third-trimester ultrasound examinations. The system analyzes blind ultrasound sweeps acquired along the maternal midline and automatically predicts fetal lie and presentation. AI-generated predictions will be compared with expert clinician assessment, which serves as the reference standard.

Eligible pregnant women attending third-trimester ultrasound examinations at the Fetal Medicine Department, Rigshospitalet, Slagelse - or Hillerød hospital, will be invited to participate. Following written informed consent, an expert clinician will first determine fetal lie and presentation as part of the routine ultrasound examination. The same clinician will subsequently acquire three blind ultrasound sweeps along the maternal midline. The AI navigational support system will analyze each sweep and generate predictions of fetal lie and presentation. All examinations will be completed within 5-10 minutes to minimize changes in fetal orientation between the clinical assessment and AI evaluation.

The primary objective is to evaluate the diagnostic performance of the AI system by comparing AI-generated predictions with expert clinician assessment. Primary outcome measures include overall diagnostic accuracy and agreement,

These findings will provide additional insight into the feasibility of implementing AI-assisted navigational support in routine obstetric ultrasound practice.

研究类型

观察性的

注册 (估计的)

150

联系人和位置

本节提供了进行研究的人员的详细联系信息，以及有关进行该研究的地点的信息。

学习联系方式

学习地点

  • 丹麦
      • Slagelse、丹麦、3450
        • 尚未招聘
        • Slagelse Hospital, Department of Obstetrics and Gynecology
        • 接触：
    • Capital Region
      • Hillerød、Capital Region、丹麦、3400
        • 尚未招聘
        • Nordsjællands Hospital, Department of Obstetrics and Gynecology
        • 接触：
    • København Ø
      • Copenhagen、København Ø、丹麦、2100
        • 招聘中
        • Rigshospitalet - Department of Obstetrics and Gynecology
        • 接触：

参与标准

研究人员寻找符合特定描述的人，称为资格标准。这些标准的一些例子是一个人的一般健康状况或先前的治疗。

资格标准

适合学习的年龄

  • 成人
  • 年长者

接受健康志愿者

不

取样方法

非概率样本

研究人群

Pregnant women with singleton pregnancies attending third-trimester ultrasound examinations at the Fetal Medicine Department, Rigshospitalet, Slagelse Hospital, or Hillerød Hospital.

描述

Inclusion Criteria:

  • Pregnant women aged ≥18 years.
  • Singleton pregnancy.
  • Gestational age ≥28+0 weeks.
  • Fetus in longitudinal lie (cephalic or breech presentation) as determined by the routine clinical ultrasound examination.
  • Able to understand Danish or English.
  • Able and willing to provide written informed consent.

Exclusion Criteria:

  • Multiple pregnancy.
  • Fetus in transverse lie.
  • Inability to provide written informed consent.

学习计划

本节提供研究计划的详细信息，包括研究的设计方式和研究的衡量标准。

研究是如何设计的？

设计细节

队列和干预

团体/队列
Prospective Clinical Validation Cohort
Pregnant women with singleton pregnancies in the third trimester (≥28+0 weeks' gestation) undergoing obstetric ultrasound examination. Participants undergo three blind ultrasound sweeps, and AI-generated predictions of fetal lie and presentation are compared with expert clinician assessment.

研究衡量的是什么？

主要结果指标

结果测量
措施说明
大体时间
Diagnostic accuracy of the AI navigational support system for determining fetal lie and presentation.
大体时间：During the study ultrasound examination (approximately 5 minutes).
Overall proportion of correct AI predictions of fetal lie and presentation compared with expert clinician assessment (reference standard).
During the study ultrasound examination (approximately 5 minutes).

次要结果测量

结果测量
措施说明
大体时间
Agreement between AI predictions and expert clinician assessment.
大体时间：During the study ultrasound examination.
Agreement will be evaluated using Cohen's kappa coefficient.
During the study ultrasound examination.

合作者和调查者

在这里您可以找到参与这项研究的人员和组织。

赞助

Copenhagen Academy for Medical Education and Simulation

合作者

Rigshospitalet, Denmark

研究记录日期

这些日期跟踪向 ClinicalTrials.gov 提交研究记录和摘要结果的进度。研究记录和报告的结果由国家医学图书馆 (NLM) 审查，以确保它们在发布到公共网站之前符合特定的质量控制标准。

研究主要日期

学习开始 (实际的)

2025年9月11日

初级完成 (估计的)

2026年10月1日

研究完成 (估计的)

2026年10月1日

研究注册日期

首次提交

2026年8月4日

首先提交符合 QC 标准的

2026年8月4日

首次发布 (实际的)

2026年8月10日

研究记录更新

最后更新发布 (实际的)

2026年8月10日

上次提交的符合 QC 标准的更新

2026年8月4日

最后验证

2026年8月1日

更多信息

与本研究相关的术语

关键字

其他相关的 MeSH 术语

其他研究编号

  • P-2019-3101

计划个人参与者数据 (IPD)

计划共享个人参与者数据 (IPD)？

不

IPD 计划说明

Individual participant data will not be made publicly available because the dataset contains identifiable medical imaging data and is subject to Danish data protection regulations (GDPR).

药物和器械信息、研究文件

研究美国 FDA 监管的药品

不

研究美国 FDA 监管的设备产品

不

此信息直接从 clinicaltrials.gov 网站检索，没有任何更改。如果您有任何更改、删除或更新研究详细信息的请求，请联系 register@clinicaltrials.gov. clinicaltrials.gov 上实施更改，我们的网站上也会自动更新.

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