Real-time AI-assisted Endocyroscopy for the Diagnosis of Colorectal Lesions

NCT06791395 | Completed

• 1 other identifier: 25K013-001
• Study Type: observational
• Target: 570
• Locations: 1 country
• Sites: 3

Brief Summary

Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death worldwide. Colonoscopy is considered the preferred method of screening for colorectal cancer, and early and resection detection of colorectal neoplastic lesions can significantly reduce colorectal cancer morbidity and mortality. In order to improve the diagnostic accuracy of endoscopy for colorectal lesions, many endoscopic techniques, such as image-enhanced endoscopy, including narrow band imaging (narrow-band imaging, NBI), magnifying endoscopy, pigment endoscopy, confocal laser endoscopy, and endocytoscopy(EC), are applied clinically. However, with the increasing number of endoscopic resection, the costs associated with the pathological diagnosis of endoscopic resection and resection specimens increase year by year. In clinical practice, some non-neoplastic colorectal lesions may not require resection, so it is important to identify the nature of the lesion during colonoscopy. Leveraging deep neural networks, AI systems support both computer-aided detection (CADe) and computer-aided classification (CADx). CADe specifically focuses on identifying polyps in colonoscopy, with the goal of reducing adenoma miss rates. Hovever, CADx can predict the pathology of the lesion based on the surface condition of the lesion. Endocytoscopy is a kind of ultra-high magnification endoscopy. But it is not something that can be easily mastered by endoscopic doctors. The investigators have previously developed an artificial intelligence system that can assist in endocytoscopy. The investigators plan to conduct a prospective, multicenter clinical trial to verify the accuracy of this CADx in predicting the histological characteristics of colorectal lesions during real-time endocytoscopy.

Conditions

Colorectal Polyp; Colorectal Neoplasms

Outcome Measures

Primary Outcomes (1)

• To evaluate the diagnostic performance of the CAD-stained in diagnosing neoplastic lesions in a clinical setting.

  The diagnostic performance will be calculated for comparison with final histology as the gold standard for diagnosis

  11 months

Secondary Outcomes (4)

• To evaluate the diagnostic performance of the CAD-NBI in diagnosing neoplastic lesions in a clinical setting.

  11 months

• To compare the diagnostic performance of CAD-NBI and CAD-stained in colorectal neoplastic lesions different colorectal lesions.

  11 months

• To evaluate the diagnostic performance of CAD-NBI and CAD-stained in the diagnosis of neoplastic DRSPs with high confidence

  11 months

• To evaluate the agreement of post-polypectomy surveillance intervals based on CAD-NBI and CAD-stained predictions with histopathological diagnosis

  11 months

Study Arms (1)

Patients with one or more colorectao lesion detected

During colonoscopy, the endoscopist inspect for the presence of colorectal lesions as per routine clinical practice with the CADx turned off. When a colorectal lesion is encountered, the endoscopist will make a prediction on the histology based on the endoscopic diagnosis. Following this, the CADx will be triggered and display the endoscopic image captured by the endoscopist. and the endoscopist will take note of the CADx prediction for the same image. In addition, other lesion features such as the size and location will be recorded, which is similar to what is performed in routine clinical practice. The lesion will be endoscopic resected or surgery and sent for pathological examination, which will form the "gold standard" for the diagnosis of polyp histology.

Diagnostic Test: Computer-aided diagnosis (CADx) support tool

Interventions

Computer-aided diagnosis (CADx) support tool DIAGNOSTIC_TEST

The CADx support tool will display the prediction results when the endoscopists press the keys on the fixed keyboard. This is performed after the endoscopists first makes an optical prediction of colorectal lesion histology using endocytoscopy as described. The CADx support tool will make a prediction of colorectal lesion histology.

Patients with one or more colorectao lesion detected

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with one or more colorectal lesions detected during endocytoscopy will be included in the study. The rest of the inclusion and exclusion criteria are as described.

You may qualify if:

• Patients who have at least one colorectal lesion detected during endocytoscopy
• Consent obtained for the study

You may not qualify if:

• lesions lacking high-quality images;
• Inflammatory bowel disease, familial adenomatous polyposis and other special diseases;
• Submucosal tumors;
• Pathological diagnosis of inflammatory polyps, Peutz-Jeghers polyps, juvenile polyps, lymphoma and other special pathological types.

Sponsors & Collaborators

• The First Hospital of Jilin University: lead
• Meihekou Central Hospital: collaborator
• Shandong Second Provincial General Hospital: collaborator

Study Sites (3)

The First Hospital of Jilin University

Changchun, Jilin, 130021, China

Location

Meihekou Central Hospital

Meihekou, Jilin, 135000, China

Location

Shandong Second Provincial General Hospital

Jinan, Shandong, 250000, China

Location

Biospecimen

Retention: SAMPLES WITH DNA

Histological specimens obtained after endoscopic or surgical treatment of colorectal lesions

MeSH Terms

Conditions

Colorectal Neoplasms

Interventions

Diagnosis, Computer-Assisted

Condition Hierarchy (Ancestors)

Intestinal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Rectal Diseases

Intervention Hierarchy (Ancestors)

Diagnosis

Study Officials

• Hong Xu, Docror

  The First Hospital of Jilin University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director, Head of Gastroenterology and Endoscopy Center, Principal Investigator, Clinical Professor

Study Record Dates

• First Submitted: January 20, 2025
• First Posted: January 24, 2025
• Study Start: February 5, 2025
• Primary Completion: December 29, 2025
• Study Completion: December 29, 2025
• Last Updated: April 13, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

CN (3)