跳至主要内容
临床试验/NCT06981052
NCT06981052已完成不适用

Prospective Evaluation of an Endoscopic Ultrasound (EUS)-Based Artificial Intelligence to Assist in the Deployment of Lumen Apposing Metal Stents for Gallbladder Drainage

University of Massachusetts, Worcester1 个研究点 分布在 1 个国家目标入组 38 人开始时间: 2025年5月12日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
发起方
入组人数
38
试验地点
1
主要终点
Accuracy of the EUS AI system in providing a recommendation (i.e. whether it is safe or not to drain the gallbladder)

研究概览

简要总结

Lumen apposing metal stents are now being used to help patients who suffer from cholecystitis (infection of the gallbladder), especially in cases where patients are not candidates for surgery. Lumen apposing metal stents are effective for draining the gallbladder, however, placement is technically challenging. Scientists have developed an artificial intelligence to aid doctors in the deployment of these stents into the gallbladder. The aim of this study is test the performance of an artificial intelligence in providing physicians accurate information for gallbladder drainage.

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
是

入选标准

  • •Age ≥ 18 years old
  • •Anticipation that patient may undergo endoscopic ultrasound
  • •Gallbladder present

排除标准

  • •Cholecystectomy
  • •No indication for endoscopic ultrasound

研究组 & 干预措施

Patients with gallbladders undergoing AI evaluation for stent deployment

结局指标

主要结局

Accuracy of the EUS AI system in providing a recommendation (i.e. whether it is safe or not to drain the gallbladder)

时间窗: Day 1

An expert endoscopist will perform the endoscopic ultrasound procedure. When the gallbladder comes into view the expert will comment as to whether they believe that the gallbladder is safe to drain. The expert will be blinded to the AI computers interpretation of the view of the gallbladder. A second observer will record what the AI recommended at the time of the blinded expert. The expert will be considered the "gold standard" and the outcome will be accuracy of the AI in mimicking the experts recommendations.

次要结局

未报告次要终点

研究者

发起方
University of Massachusetts, Worcester
申办方类型
Other
责任方
Principal Investigator
主要研究者

Neil Marya

Assistant Clinical Professor of Medicine

University of Massachusetts, Worcester

研究点 (1)

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