Ignite Creation Date:
2025-12-26 @ 10:57 AM
Ignite Modification Date:
2025-12-29 @ 1:49 PM
Study NCT ID:
NCT05464108
Status:
COMPLETED
Last Update Posted:
2024-12-03
First Post:
2022-07-08
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Validation the Artificial Intelligence System for Automatic Evaluation of the Extent of Intestinal Metaplasia
Sponsor:
Shandong University
Organization:
Study Overview
Official Title:
Validation the Artificial Intelligence System for Automatic Evaluation of the Extent of
Status:
COMPLETED
Status Verified Date:
2023-12
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. But its clinical application is limited for at least biopsy samples. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. The investigators designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores.
Detailed Description:
Gastric intestinal metaplasia(GIM) is an important stage in the gastric cancer(GC). The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. However, its need to take at least 4 biopsies is not clinically feasible. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. An EGGIM score of 5 was the best cut off value for identifying OLGIM stage III/IV patients. The investigators have designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?: