Clinical Efficacy Evaluation of a Computer-aided Colonoscopy as Compared With the Standard Colonoscopy.

Colorectal Cancer Clinical Trial

Official title:

Clinical Efficacy Evaluation of a Computer-aided Colonoscopy as Compared With the Standard Colonoscopy.

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05240625
• Other study ID #: 202112052DIPC
• Status: Recruiting
• Phase: N/A
• Start date: March 1, 2022
• Est. completion date: December 31, 2025

Study information

• Verified date: January 2024
• Source: National Taiwan University Hospital
• Contact: Han-Mo Chiu, MD, PhD
• Phone: +886-2-23123456
• Email: hanmochiu[@]ntu.edu.tw
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Colonoscopy is clinically used as the gold standard for detection of colorectal cancer (CRC) and removal of adenomatous polyps of the colon and rectum. Evidence has shown that CRC could be prevented by colonoscopic removal of adenomatous polyps. Despite the success of colonoscopy in reducing cancer-related deaths, there exists a disappointing level of adenomas missed at colonoscopy. In recent years, emerging artificial intelligence (AI) and computer-aided detection (CADe) technology has been shown to improve ADR. Based on a meta-analysis, ADR was demonstrated to be significantly higher in the CADe groups than in the standard colonoscopy groups, representing a relative risk of 25.2%.

In this study, performance of colonoscopy with or without aid of CADe will be compared in terms of quality indicators. The adenoma detection rate (ADR), which is the proportion of average-risk patients undergoing screening colonoscopy in whom an adenoma is found, is regarded as a robust measure of colonoscopy performance quality that correlates with subsequent cancer risk. Thus, ADR is taken as the primary outcome of this study. The target population includes individuals who are undergoing screening, diagnostic, or surveillance colonoscopy.

Description:

This multiple-site study aims to evaluate whether a computer-aided detection (CADe) device can assist in adenoma detection rate (ADR) when compared with the current standard-of-care procedure. The subject CADe device used in this study contains an artificial intelligence/machine learning (AI/ML) advanced algorithm to aid the endoscopists in detection of colonic mucosal lesions and the detected polyps will be highlighted to the endoscopists during the real-time colonoscopy procedures. This study plans to enroll subjects aged ≥ 40 years and < 80 years, who are scheduled for screening or diagnostic colonoscopy for colorectal cancer (CRC) or surveillance colonoscopy for post-polypectomy follow-up. After being evaluated with the inclusion and exclusion criteria, eligible subjects will be randomized in a 1:1 ratio to receive either the computer-aided colonoscopy (CC) or the standard colonoscopy(SC). Randomization will be stratified by gender, age, and colonoscopy indication (screening, diagnostic, or surveillance) of subjects. The resected polyps will be submitted for histologic examination by one expert pathologist at each site. If any uncertainty or doubt exists, an expert in gastrointestinal pathology will serve as the adjudicator to perform a second review and make the final decision. All of the pathologists (including the final adjudicator) who will perform the histopathologic examinations and produce the pathology assessment will be blinded to the assigned study arm of the specimens. The pathology reports of the subjects will be kept securely at each site as the source data.

The primary endpoint is the ADR of the CC as compared with that of the SC. The ADR is defined as the percentage of subjects undergoing a complete colonoscopy, who have at least one histologically confirmed adenoma detected and removed. In addition, the following secondary endpoints will also be evaluated, including: Polyp detection rate (PDR), Adenomas per colonoscopy (APC), Polyps per colonoscopy (PPC), Non-neoplastic polypectomy rate (NNPR), Non-neoplastic polypectomy (NNP), Sessile serrated lesions per colonoscopy (SPC), Advanced adenomas per colonoscopy (AAPC), and withdrawal time.

Signed written informed consent forms will be obtained from all participating subjects before enrollment.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1500
• Est. completion date: December 31, 2025
• Est. primary completion date: December 31, 2025
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 40 Years to 80 Years

Eligibility

Inclusion Criteria:

• Subjects who have given signed informed consent form

• Informed consensus has been obtained that endoscopic resection should be performed if a lesion is found

• Subjects who are scheduled for screening or diagnostic colonoscopy for colorectal cancer (CRC) or surveillance colonoscopy for post-polypectomy follow-up

Exclusion Criteria:

• Subjects with any of the following prior history or current conditions:

1. Contraindications to colonoscopy

2. Inflammatory bowel disease (IBD)

3. Colorectal cancer (CRC)

4. Familial adenomatous polyposis (FAP)

5. Colonic stenosis

6. Severe organ failure (cirrhosis of Child C, heart failure of ACC / AHA stage D)

7. Active gastrointestinal (GI) Bleeding

8. Pregnancy

9. Prior colorectal surgery, including colonic or rectal resection (except for appendectomy, surgery on the anus, and polypectomy)

10. Undergo colonoscopy within 3 years

• Subjects with any of the following conditions per the investigator's judgement:

1. High suspicion of IBD, CRC, and FAP.

2. High risk of bleeding after endoscopic treatment, and difficult management of anticoagulation or antiplatelet medication.

Related Conditions & MeSH terms

• Adenoma
• Colon Adenoma
• Colorectal Cancer
• Colorectal Neoplasms

Intervention

Device:
• "aetherAI" Computer-aided Polyp Detection (CADe) Systems for Colonoscopy
The investigational medical device is intended to automatically detect potential polyps via colonoscopy in real-time during colonoscopy examinations. The subject device contains an artificial intelligence/machine learning (AI/ML) advanced algorithm to aid the endoscopists in detection of colonic mucosal lesions and the detected polyps will be highlighted to the endoscopists during the real-time colonoscopy procedures.

Procedure:
• Standard colonoscopy
Standard colonoscopy procedure.

Locations

Country	Name	City	State
Taiwan	National Taiwan University Hospital	Taipei city

Sponsors (5)

Lead Sponsor	Collaborator
National Taiwan University Hospital	aetherAI Co., Ltd, Changhua Christian Hospital, Fu Jen Catholic University Hospital, Shin Kong Hospital

Country where clinical trial is conducted

Taiwan, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Adenoma detection rate	The percentage of subjects undergoing a complete colonoscopy, who have at least one histologically confirmed adenoma detected and removed.	1 week (after the colonoscopy procedure, when pathology report is released)
Secondary	Polyp detection rate (PDR)	Percentage of subjects undergoing a complete colonoscopy who have at least one polyp detected.	1 day(right after the colonoscopy procedure)
Secondary	Adenomas per colonoscopy (APC)	Number of adenomas per colonoscopy, calculated by dividing the total number of adenomas detected by the total number of colonoscopies.	1 week (after the colonoscopy procedure, when pathology report is released)
Secondary	Polyps per colonoscopy (PPC)	Number of polyps of any kind (i.e., adenoma, sessile serrated polyp, hyperplastic polyp, or non-neoplastic polyp) per colonoscopy, calculated by dividing the total number of polyps detected by the total number of colonoscopies.	1 day(right after the colonoscopy procedure)
Secondary	Non-neoplastic polypectomy rate (NNPR)	Percentage of subjects with at least one non-neoplastic polypectomy at the time of colonoscopy.	1 week (after the colonoscopy procedure, when pathology report is released)
Secondary	Sessile serrated lesions per colonoscopy (SPC)	Number of sessile serrated lesions (SSLs) per colonoscopy, calculated by dividing the total number of sessile serrated lesions detected by the total number of colonoscopies.	1 week (after the colonoscopy procedure, when pathology report is released)
Secondary	Advanced adenomas per colonoscopy (AAPC)	Number of advanced adenomas per colonoscopy, calculated by dividing the total number of advanced adenomas detected by the total number of colonoscopies.	1 week (after the colonoscopy procedure, when pathology report is released)
Secondary	Withdrawal time	The time spent in inspecting the colonic mucosa as the endoscope is withdrawn during a colonoscopy, excluding procedure time	1 day(right after the colonoscopy procedure)