Automatic Evaluation of the Severity of Gastric Intestinal Metaplasia With Pathology Artificial Intelligence Diagnosis System

• Sponsor: Shandong University (Other)
• Overall Status: Recruiting
• CT.gov ID: NCT05447221
• Collaborator: (none)
• Enrollment: 150
• Location: 1
• Anticipated Duration (Months): 18
• Patients Per Site Per Month: 8.3

Study Details

Study Description

Brief Summary

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.

Condition or Disease	Intervention/Treatment	Phase
Gastric Intestinal Metaplasia; Artificial Intelligence; Pathology; Gastric Cancer	Diagnostic Test: The diagnosis of Artificial Intelligence and pathologists

Detailed Description

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.

Study Design

• Study Type: Observational
• Anticipated Enrollment: 150 participants
• Observational Model: Other
• Time Perspective: Prospective
• Official Title: Automatic Evaluation of the Severity of Gastric Intestinal Metaplasia With Pathology Artificial Intelligence Diagnosis System: a Diagnostic Test
• Anticipated Study Start Date: Jul 1, 2022
• Anticipated Primary Completion Date: Dec 31, 2023
• Anticipated Study Completion Date: Dec 31, 2023

Arms and Interventions

Arm	Intervention/Treatment
Whole slide images of gastric biopsy specimens Whole slide images of gastric biopsy specimens	Diagnostic Test: The diagnosis of Artificial Intelligence and pathologists; 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.

Outcome Measures

Primary Outcome Measures

1. The diagnostic performance of AI model to assess the severity of intestinal metaplasia [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

Secondary Outcome Measures

1. Accuracy of the digital pathological AI model to identify tumor regions [2 years]

   Accuracy of the digital pathological AI model in identifying tumor regions in the whole slide images

2. Accuracy of digital pathological AI models to identify glands, mucosal epithelium, and intestinal metaplasia in non-neoplastic areas [2 years]

   Accuracy of digital pathological AI models to identify glands, mucosal epithelium, and intestinal metaplasia in non-neoplastic areas

Eligibility Criteria

Criteria

• Ages Eligible for Study: 40 Years to 75 Years
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No

Inclusion Criteria:

• patients aged 40-75 years who undergo the gastroscopy examination and biopsy

Exclusion Criteria:

• 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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Department of Gastroenterology, Qilu Hospital, Shandong University	Jinan	Shandong	China	250012

Sponsors and Collaborators

• Shandong University

Investigators

• Study Chair: Yanqing Li, MD, PhD, Qilu Hospital, Shandong University

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

• Responsible Party: Yanqing Li, Vice President of Qilu Hospital, Shandong University
• ClinicalTrials.gov Identifier: NCT05447221
• Other Study ID Numbers: 2022-SDU-QILU-110
• First Posted: Jul 7, 2022
• Last Update Posted: Jul 7, 2022
• Last Verified: Jul 1, 2022

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No
• Keywords provided by Yanqing Li, Vice President of Qilu Hospital, Shandong University: gastric cancer; Gastric Intestinal Metaplasia; Digital Pathology; Whole Slide Image
• Additional relevant MeSH terms: Stomach Neoplasms; Metaplasia

Study Results

No Results Posted as of Jul 7, 2022