Development and Validation of an Artificial Intelligence System for Automatic Evaluation of the Extent of Intestinal Metaplasia
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 600
- 试验地点
- 1
- 主要终点
- The specificity of AI model to assess the degree of intestinal metaplasia in an endoscopic picture
研究概览
简要总结
Gastric intestinal metaplasia(GIM) is an important stage in the gastric cancer(GC). With technical advance of image-enhanced endoscopy (IEE), studies have demonstrated IEE has high accuracy for diagnosis of GIM. The endoscopic grading system (EGGIM), a new endoscopic risk scoring system for GC, have been shown to accurately identify a wide range of patients with GIM. However, the high diagnostic accuracy of GIM using IEE and EGGIM assessments performed all require much experience, which limits the application of EGGIM. The investigators aim to design a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores.
详细描述
Globally, gastric cancer is the fifth most prevalent malignancy and the third leading cause of cancer mortality. Gastric intestinal metaplasia (GIM) is an intermediate precancerous gastric lesion in the gastric cancer cascade. Studies have shown that the 5-year cumulative incidence of gastric cancer in IM patients ranges from 5.3% to 9.8% . With technical advance of image-enhanced endoscopy (IEE), studies have demonstrated IEE has high accuracy for diagnosis of GIM. The endoscopic grading system (EGGIM), a new endoscopic risk scoring system for GC, have been shown to accurately identify a wide range of patients with GIM. However, The high diagnostic accuracy of GIM using IEE and EGGIM assessments performed all require much experience, which limits the application of EGGIM. The investigators aim to design a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •patients aged 18-80 years who undergo the IEE examination
排除标准
- •patients with severe cardiac, cerebral, pulmonary or renal dysfunction or psychiatric disorders who cannot participate in gastroscopy
- •patients with previous surgical procedures on the stomach
- •patients who refuse to sign the informed consent form
结局指标
主要结局
The specificity of AI model to assess the degree of intestinal metaplasia in an endoscopic picture
时间窗: 2 years
The specificity of AI model to assess the degree of intestinal metaplasia in an endoscopic picture
The accuracy of AI model to assess the degree of intestinal metaplasia in an endoscopic picture
时间窗: 2 years
The accuracy of AI model to assess the degree of intestinal metaplasia in an endoscopic picture
The sensitivity of AI model to assess the degree of intestinal metaplasia in an endoscopic picture
时间窗: 2 years
The sensitivity of AI model to assess the degree of intestinal metaplasia in an
次要结局
- Accuracy of the experienced endoscopists to assess the degree of intestinal metaplasia(2 years)
- Accuracy of the inexperienced endoscopists to assess the degree of intestinal metaplasia(2 years)
- Inter-observer agreement among experienced endoscopists in identifying the degree of intestinal metaplasia(2 years)
- Inter-observer agreement among inexperienced endoscopists in identifying degree of intestinal metaplasia(2 years)
研究者
Yanqing Li
Vice President of Qilu Hospital
Shandong University