Automatic Evaluation of the Severity of Gastric Intestinal Metaplasia With Pathology Artificial Intelligence Diagnosis System: a Diagnostic Test
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 150
- 试验地点
- 1
- 主要终点
- The diagnostic performance of AI model to assess the severity of intestinal metaplasia
研究概览
简要总结
The OLGIM staging system is highly recommended for a comprehensive assessment of GIM severity to evaluate patients' gastric cancer risk. However, its need to take at least 4 biopsies is not clinically feasible due to a serious shortage of pathologists compared with the large number of gastric cancer screening population.
We plan to develop a Digital Pathology artificial intelligence diagnosis system (DPAIDS), to automatically identify tumor areas in whole slide images(WSI) and quickly and accurately quantify the severity of intestinal metaplasia according to the proportion of intestinal metaplasia areas.
详细描述
Gastric cancer is the fifth most prevalent malignancy and the third most deadly worldwide, and intestinal metaplasia (IM) is a common precancerous state that is closely associated with gastric carcinogenesis .The OLGIM staging system is highly recommended for a comprehensive assessment of GIM severity to evaluate patients' gastric cancer risk. However, its need to take at least four biopsies is not clinically feasible due to a serious shortage of pathologists compared with the large number of gastric cancer screening population. Developing automated screening methods can reduce the heavy diagnostic workload. With advances in digital pathology scanning devices and deep learning technologies, whole-slide images (WSI) have been used to develop automated cancer diagnostic systems.
We plan to develop a Digital Pathology artificial intelligence diagnosis system (DPAIDS), to automatically identify tumor areas in whole slide images(WSI) and quickly and accurately quantify the severity of intestinal metaplasia according to the proportion of intestinal metaplasia areas. Then biopsies will be prospectively collected and prepared as WSI for model validation.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 40 Years 至 75 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •patients aged 40-75 years who undergo the gastroscopy examination and biopsy
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 with contraindications to biopsy
- •patients who refuse to sign the informed consent form
结局指标
主要结局
The diagnostic performance of AI model to assess the severity of intestinal metaplasia
时间窗: 2 years
The diagnostic performance of AI model to assess the severity of intestinal metaplasia in a single biopsy tissue slide: Accuracy, sensitivity, and specificity
次要结局
- Accuracy of digital pathological AI models to identify glands, mucosal epithelium, and intestinal metaplasia in non-neoplastic areas(2 years)
- Accuracy of the digital pathological AI model to identify tumor regions(2 years)
研究者
Yanqing Li
Vice President of Qilu Hospital
Shandong University