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Feasibility test of an artificial intelligence-based confocal microscope for the evaluation of fresh tissue samples during endoscopic submucosal dissection in gastric cancer

Feasibility test of an artificial intelligence-based confocal microscope for the evaluation of fresh tissue samples during endoscopic submucosal dissection in gastric cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0009623
Enrollment
50
Registered
2024-07-10
Start date
2024-07-08
Completion date
Unknown
Last updated
2024-07-23

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

None listed

Sponsors

Ajou University Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Men and women over 19 years of age who undergo ESD treatment for the treatment of early gastric cancer

Exclusion criteria

Exclusion criteria: Patients whose ESD specimens were larger than 5cm in diameter or were divided into multiple sections, and patients who withdrew their consent.

Design outcomes

Primary

MeasureTime frame
Evaluation of images taken with confocal fluorescence microscopy of fresh specimen tissue obtained on the day of EDS procedure

Secondary

MeasureTime frame
Analysis of the degree of agreement between AI readings on confocal fluorescence microscopy images and the results of final pathological diagnosis;Analysis of the degree of agreement between the reading of pathology on confocal fluorescence microscopy images and the reading results of final pathology diagnosis

Countries

Korea, Republic of

Contacts

Public Contactsomi Heo

Ajou University

somisclt@naver.com+82-31-219-5342

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 4, 2026