NCT05779436招募中不适用
Real-Time Cholangioscopy Artificial Intelligence Evaluation of Biliary Strictures
适应症
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- Mayo Clinic
- 入组人数
- 100
- 试验地点
- 2
- 主要终点
- POC-CNN Model AUC
研究概览
简要总结
The purpose of this study is to demonstrate the feasibility and validity of a previously developed peroral cholangioscopy (POC) convolutional neural network (CNN) to determine the etiology of biliary strictures when used in real-time.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age ≥ 18 years old
- •Anticipation that patient may undergo POC during an endoscopic retrograde cholangioscopy
- •Pregnant patients can be included in the study. Use of the POC-CNN does not convey any new risk to the patient nor fetus.
- •Non-English speaking subjects will be included in the study. Consent for the procedure itself is always done with the assistance of an interpreter via telephone or video. Use of the POC-CNN will be discussed with all patients via this interpreter during the procedure consent.
排除标准
- •Age <18 years old
- •No indication that cholangioscopy will be performed during endoscopic retrograde cholangiopancreatography (ERCP)
研究组 & 干预措施
Patients undergoing cholangioscopy for evaluation biliary stricture
结局指标
主要结局
POC-CNN Model AUC
时间窗: Patients will be considered negative for malignancy only with 12 months of negative follow-up or definitive negative surgical histology.
Area Under the Curve (AUC) analysis for POC-CNN for classification of malignant biliary stricture
次要结局
- Test characteristics of POC-CNN(Patients will be considered negative for malignancy only with 12 months of negative follow-up or definitive negative surgical histology.)
研究者
Vinay Chandrasekhara
Principal Investigator
Mayo Clinic
研究点 (2)
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