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Clinical Study on the Diagnosis of Colorectal Lesions by Real-time Artificial Intelligence Assisted Endocytoscopy Combined With Narrow Band Imaging

NCT06982885 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2025-08-07

No results posted yet for this study

Summary

Colorectal cancer (colorectal cancer, CRC) is the third most common malignant tumor globally and the second leading cause of cancer-related deaths. Colonoscopy is considered the preferred method for screening colorectal cancer; early detection and removal of colorectal neoplasms can significantly reduce the incidence and mortality of colorectal cancer. To improve the diagnostic accuracy of endoscopy in colorectal lesions, many endoscopic techniques have been applied clinically, such as image-enhanced endoscopy, including narrow band imaging (narrow-band imaging, NBI), magnifying endoscopy, chromoendoscopy, confocal laser endoscopy, and endocytoscopy (EC). However, with the increasing number of endoscopic resections, the costs associated with the pathological diagnosis of resected specimens have risen year by year. In clinical practice, some non-neoplastic colorectal lesions may not require resection, so it is important to differentiate the nature of lesions during colonoscopy.

Endocytoscopy is an ultra-high magnification endoscope that, when combined with chemical staining and narrowband imaging techniques, allows the endoscopist to observe the nuclear morphology of colorectal lesions, the shape of glands, and the morphology of microvessels through the naked eye. This approach avoids the need for pathological examination, achieving the goal of real-time biopsy in vivo. However, the accuracy of endocytoscopic image interpretation requires extensive experience to improve judgment, and there is a certain degree of subjectivity and error in the endoscopist's assessment process. Therefore, to address this issue, clinical applications have proposed using artificial intelligence (AI) for computer-aided diagnosis. The investigator's center has previously developed an AI-assisted diagnostic system based on endocytoscopy with NBI to assist in determining the nature of colorectal lesions. However, forward-looking clinical studies are still lacking to verify the effectiveness of this AI-assisted system. Thus, the investigator aim to conduct such clinical research to validate the clinical efficacy of this AI.

Conditions

  • Endocytoscopy

Interventions

DIAGNOSTIC_TEST

artificial intelligence

Artificial intelligence assisted diagnostic system was used to diagnose colorectal lesions

Sponsors & Collaborators

  • The First Hospital of Jilin University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-05-19
Primary Completion
2025-12-31
Completion
2025-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06982885 on ClinicalTrials.gov