Ignite Creation Date:
2025-12-25 @ 1:47 AM
Ignite Modification Date:
2025-12-26 @ 4:52 AM
Study NCT ID:
NCT06969794
Status:
COMPLETED
Last Update Posted:
2025-05-14
First Post:
2025-04-25
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Single-center, Randomized, Superiority Pivotal Clinical Study to Evaluate the Efficacy of Artificial Intelligence-based Upper Gastrointestinal Endoscopy Image
Sponsor:
Chuncheon Sacred Heart Hospital
Organization:
Study Overview
Official Title:
Single-center, Single Group, Randomized, Superiority Pivotal Clinical Study to Evaluate the Efficacy and Safety of Artificial Intelligence-based Upper Gastrointestinal Endoscopy Image Diagnosis Aid Software
Status:
COMPLETED
Status Verified Date:
2025-05
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:
We will conduct a single-center retrospective study at a university hospital. A total of 3,385 gastroscopic white-light images from patients with pathologically confirmed findings will be analyzed. The AI software will automatically identify images as non-neoplastic or neoplastic (low-grade dysplasia, high-grade dysplasia, early gastric cancer with mucosal or submucosal invasion, or advanced gastric cancer) and highlighted lesion locations. Two experienced endoscopists will independently review the same image set without AI assistance for comparison. Primary outcomes are sensitivity and specificity of the AI in detecting gastric neoplasms (by category and overall), and the localization accuracy measured by the localization receiver operating characteristic (LROC) curve area. Secondary outcomes is includes comparison of the AI's diagnostic performance with that of endoscopists.
Detailed Description:
We will conduct a single-center retrospective study at a university hospital. A total of 3,385 gastroscopic white-light images from patients with pathologically confirmed findings will be analyzed. The AI software will automatically identify images as non-neoplastic or neoplastic (low-grade dysplasia, high-grade dysplasia, early gastric cancer with mucosal or submucosal invasion, or advanced gastric cancer) and highlighted lesion locations. Two experienced endoscopists will independently review the same image set without AI assistance for comparison. Primary outcomes are sensitivity and specificity of the AI in detecting gastric neoplasms (by category and overall), and the localization accuracy measured by the localization receiver operating characteristic (LROC) curve area. Secondary outcomes is includes comparison of the AI's diagnostic performance with that of endoscopists.
Inclusion criteria:
Age 19 or older At least one gastric lesion biopsied with a definitive pathological diagnosis Availability of high-quality white-light endoscopy images of the lesion and surrounding mucosa
Exclusion criteria:
Poor-quality images (e.g., out of focus or obscured) Lack of histopathological confirmation of the lesion
Each image will be paired with a reference standard diagnosis based on the pathology result for that lesion or region.
Inclusion criteria:
Age 19 or older At least one gastric lesion biopsied with a definitive pathological diagnosis Availability of high-quality white-light endoscopy images of the lesion and surrounding mucosa
Exclusion criteria:
Poor-quality images (e.g., out of focus or obscured) Lack of histopathological confirmation of the lesion
Each image will be paired with a reference standard diagnosis based on the pathology result for that lesion or region.
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?:
None
Is an FDA AA801 Violation?: