Evaluation of 'WAYMED Endo CL CS' for Automated Detection and Diagnosis of Colorectal Adenoma and Non-Adenoma Lesions

The Effectiveness of the Computer-aided Detection/Diagnosis Software, 'WAYMED Endo CL CS', Which Assists Medical Specialists by Automatically Analyzing Colorectal Endoscopic Images With Confirmed Adenoma or Non-Adenoma Lesions, Detecting the Lesion, and Providing Probabilities as to Whether the Lesion Belongs to the Adenoma or Non-Adenoma Group: A Single-center, Single Arm, Retrospective, Superiority, Single-blind, and Pivotal Clinical Trial

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07470827

Enrollment

1178

Registered

2026-03-13

Start date

2024-09-01

Completion date

2026-12-01

Last updated

2026-03-13

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

Conditions

Adenoma, Carcinoma, Colorectal Adenoma, Hyperplastic Polyp, Non-Adenoma, Sessile Serrated Lesion

Keywords

Colorectal Endoscopy, Adenoma, Non-Adenoma, Artificial Intelligence, Computer-Aided Diagnosis (CADx), Colorectal Cancer Screening

Brief summary

The purpose of this clinical trial is to evaluate the effectiveness of the computer-aided diagnosis (CADx) software, 'WAYMED endo CL CS', which assists medical specialists by automatically analyzing colorectal endoscopic images, identifying lesions, and providing probability values to classify them as Adenoma or Non-Adenoma. This pivotal trial is designed to confirm that 'WAYMED endo CL CS' can support clinicians in diagnostic decision-making by improving the classification of colorectal lesions.

Detailed description

This clinical trial aims to assess the clinical sensitivity and specificity of 'WAYMED endo CL CS' in detecting colorectal lesions and classifying them into Adenoma (colorectal cancer, adenoma) or Non-Adenoma(Hyperplastics, etc) groups. The trial is designed as a retrospective, single-center, single-arm, single-blind, superiority, and pivotal study. Colorectal endoscopic images and corresponding histopathology results are retrospectively collected from adult patients. Images meeting all inclusion/exclusion criteria are enrolled. Each lesion is annotated and verified by a Reference Standard Establishment Committee, which consists of experienced endoscopy specialists. The investigational software is applied to the enrolled images to automatically detect and classify the lesions, while the reference standard serves as the comparator. The primary endpoints include clinical sensitivity (%) and specificity (%) of 'WAYMED endo CL CS' in distinguishing Adenoma from Non-Adenoma lesions. The secondary endpoint is the overall diagnostic accuracy (%). This study is intended to provide confirmatory clinical evidence required for regulatory approval of 'WAYMED endo CL CS' as a computer-aided diagnosis (CADx) software for colorectal endoscopy.

Interventions

DEVICEWAYMED endo CL CS

Classification of colorectal endoscopic images as "Adenoma" or "Non-Adenoma" by WAYMED endo CL CS (Computer-aided diagnosis software for colorectal endoscopy).

OTHERReference standard review

Colorectal endoscopic images are independently reviewed by expert endoscopists and confirmed with histopathology to establish the reference standard.

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

19 Years to No maximum

Healthy volunteers

Inclusion criteria

1. Adult patients (≥19 years) with colorectal endoscopic images showing one lesion. 2. Histopathology confirming the lesion as Adenoma (colorectal cancer, adenoma) or Non-Adenoma (sessile serrated lesion, hyperplastic polyp).

Exclusion criteria

1. Images previously used for training or internal validation of the investigational software. 2. History of colectomy. 3. Diagnosed with inflammatory bowel disease (e.g., ulcerative colitis, Crohn's disease) or neuroendocrine tumor. 4. Poor image quality (blurred, incomplete lesion capture). 5. Images with multiple lesions or fewer than two images per lesion. 6. Determined by the investigator to be inappropriate for inclusion.

Design outcomes

Primary

Measure	Time frame	Description
Clinical Sensitivity in classifying colorectal lesions (%)	6 months	The probability of being classified as "Adenoma" among colorectal endoscopic images confirmed as "Adenoma" through histopathology.
Clinical Specificity in classifying colorectal lesions (%)	6 months	The probability of being classified as "Non-Adenoma" among colorectal endoscopic images confirmed as "Non-Adenoma" through histopathology.

Secondary

Measure	Time frame	Description
Diagnostic Accuracy in classifying colorectal lesions (%)	6 months	The overall probability of correctly classifying colorectal lesions as either "Adenoma" or "Non-Adenoma" compared with histopathology.

Countries

South Korea

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Mar 14, 2026