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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Whole slide images of gastric biopsy specimens | Whole slide images of gastric biopsy specimens |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| The diagnosis of Artificial Intelligence and pathologists | Diagnostic Test | Pathologists and AI will assess the severity of intestinal metaplasia and judge the tumor area of whole slide images of gastric biopsy specimens independently. In addition, the pathologists can not see the diagnosis of AI. |
| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic performance of AI model to assess the severity of intestinal metaplasia | The diagnostic performance of AI model to assess the severity of intestinal metaplasia in a single biopsy tissue slide: Accuracy, sensitivity, and specificity | 2 years |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of the digital pathological AI model to identify tumor regions | Accuracy of the digital pathological AI model in identifying tumor regions in the whole slide images | 2 years |
| Accuracy of digital pathological AI models to identify glands, mucosal epithelium, and intestinal metaplasia in non-neoplastic areas |
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Inclusion Criteria:
Exclusion Criteria:
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Consecutive patients who receive the gastrointestinal endoscopy examination and screened that fulfill the eligibility criteria at Qilu Hospital, Shandong University will be enrolled into the study
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yanqing Li, MD, PhD | Contact | 0531182169385 | liyanqing@sdu.edu.cn |
| Name | Affiliation | Role |
|---|---|---|
| Yanqing Li, MD, PhD | Qilu Hospital of Shandong University | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Department of Gastroenterology, Qilu Hospital, Shandong University | Recruiting | Jinan | Shandong | 250012 | China |
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Biopsies from the gastric antrum and body will be prospectively collected and prepared as whole slide images for histology examination and model validation.
|
Accuracy of digital pathological AI models to identify glands, mucosal epithelium, and intestinal metaplasia in non-neoplastic areas |
| 2 years |
| ID | Term |
|---|---|
| D013274 | Stomach Neoplasms |
| ID | Term |
|---|---|
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D013272 | Stomach Diseases |
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