NCT06317103

Brief Summary

The purpose of this clinical trial is to prove that the prediction capability of 'WAYMED endo' is superior to that of the endoscopists in classifying EGC based on the depth of invasion categories in gastro-endoscopic images. The computer-aided detection·diagnosis software is an Artificial Intelligence (AI) software used to assist medical specialists in diagnostic decisions by automatically classifying EGC based on the depth of invasion categories in gastro-endoscopic images and displaying the results and possibilities on the User Interface (UI).

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
653

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Aug 2023

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

August 22, 2023

Completed
Same day until next milestone

Primary Completion

Last participant's last visit for primary outcome

August 22, 2023

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

August 22, 2023

Completed
7 months until next milestone

First Submitted

Initial submission to the registry

March 5, 2024

Completed
14 days until next milestone

First Posted

Study publicly available on registry

March 19, 2024

Completed
Last Updated

March 19, 2024

Status Verified

March 1, 2024

Enrollment Period

Same day

First QC Date

March 5, 2024

Last Update Submit

March 14, 2024

Conditions

Keywords

The depth of invasion categories for EGC (mucosal invasion, submucosal invasion)

Outcome Measures

Primary Outcomes (2)

  • Clinical Sensitivity in classifying early gastric cancer (EGC) based on the depth of invasion (%)

    The probability of being classified as "Mucosa (mucosal invasion)", based on the depth of invasion categories for early gastric cancer, among gastro-endoscopic images confirmed as "Mucosa" through the results of pathologic examination.

    3 months

  • Clinical Specificity in classifying early gastric cancer (EGC) based on the depth of invasion (%)

    The probability of being classified as "Submucosa (submucosal invasion)", based on the depth of invasion categories for early gastric cancer, among gastro-endoscopic images confirmed as "Submucosa" through the results of pathologic examination.

    3 months

Secondary Outcomes (1)

  • Accuracy in classifying the depth of invasion categories ("Mucosa" or "Submucosa") for early gastric cancer (%)

    3 months

Study Arms (2)

Trial group

The gastro-endoscopic images in this group are classified as "Mucosa" or "Submucosa" by WADYMED endo.

Device: WADYMED endo

Control group

The gastro-endoscopic images in this group are interpreted as "Mucosa" or "Submucosa" by the endoscopists.

Other: Control group (the endoscopists)

Interventions

Classification of the gastro-endoscopic images as "Mucosa" or "Submucosa" by WADYMED endo (Gastric cancer image, computer aided detection/diagnosis software)

Trial group

Interpretation of the gastro-endoscopic images as "Mucosa" or "Submucosa" by the endoscopists

Control group

Eligibility Criteria

Age19 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Gastro-endoscopic images of early gastric cancer patients who underwent EGD

You may qualify if:

  • \. Patients aged 19 years or older who underwent EGD 2. Confirmed the presence of gastric cancer through the Electronic Medical Record (EMR), including reports of EGD or pathology
  • M ("Mucosa (mucosal invasion)"): Medical data of early gastric cancer patients with confirmed "Mucosa" for the depth of invasion category in the EMR.
  • SM ("Submucosa (submucosal invasion)"): Medical data of early gastric cancer patients with confirmed "Submucosa" for the depth of invasion category in the EMR.

You may not qualify if:

  • Absence of pathological results for the lesion
  • History of gastrectomy

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Yonsei University Gangnam Severance Hospital

Seoul, South Korea

Location

MeSH Terms

Conditions

Stomach Neoplasms

Interventions

Control Groups

Condition Hierarchy (Ancestors)

Gastrointestinal NeoplasmsDigestive System NeoplasmsNeoplasms by SiteNeoplasmsDigestive System DiseasesGastrointestinal DiseasesStomach Diseases

Intervention Hierarchy (Ancestors)

Epidemiologic Research DesignEpidemiologic MethodsInvestigative TechniquesResearch DesignMethods

Study Officials

  • Jie-Hyun Kim

    Yonsei University Gangnam Severance Hospital

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
observational
Observational Model
CASE CONTROL
Time Perspective
RETROSPECTIVE
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

March 5, 2024

First Posted

March 19, 2024

Study Start

August 22, 2023

Primary Completion

August 22, 2023

Study Completion

August 22, 2023

Last Updated

March 19, 2024

Record last verified: 2024-03

Locations