Ignite Creation Date:
2024-05-06 @ 5:51 PM
Last Modification Date:
2024-10-26 @ 2:37 PM
Study NCT ID:
NCT05459610
Status:
UNKNOWN
Last Update Posted:
2022-07-15
First Post:
2022-07-08
Brief Title:
Automatic Evaluation of the Extent of Intestinal Metaplasia With Artificial Intelligence
Sponsor:
Shandong University
Organization:
Shandong University
Study Overview
Official Title:
Development and Validation of an Artificial Intelligence System for Automatic Evaluation of the Extent of Intestinal Metaplasia
Status:
UNKNOWN
Status Verified Date:
2022-07
Last Known Status:
RECRUITING
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:
Gastric intestinal metaplasiaGIM is an important stage in the gastric cancerGC 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
Detailed Description:
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 53 to 98 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
Study Oversight
Has Oversight DMC:
None
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?:
None
Is an FDA AA801 Violation?:
None