Adenoma Detection Rate Using AI System in China | NCT03840590

Studies
Adenoma Detection Rate Using AI System in China

NCT03840590

Sponsor

Changhai Hospital

Status

Completed

Last Update Posted

Sep 25, 2020Actual

Enrollment

743Actual

Phase

Not Applicable

Conditions

Colorectal Neoplasms
Colonic Polyp
Adenoma

Interventions

CSK AI system
Standard Colonoscopy

Countries

China

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Sep 2020

Overall Recruitment Status or Expanded Access Status

Completed

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Jul 10, 2019Actual

Primary Completion Date

Dec 5, 2019Actual

Completion Date

Dec 5, 2019Actual

First Submitted Date

Feb 12, 2019

First Submission Date that Met QC Criteria

Feb 12, 2019

First Posted Date

Feb 15, 2019Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Sep 24, 2020

Last Update Posted Date

Sep 25, 2020Actual

Sponsor/Collaborators Module

Responsible Party, by Official Title

En-Da Yu, Director of Department of Colorectal Surgery and Vice Director of GI Endoscopy, Changhai HospitalPrincipal Investigator

Lead Sponsor

Changhai HospitalOTHER

Collaborators

Name	Class
Sixth Affiliated Hospital, Sun Yat-sen University	OTHER
Shanghai Zhongshan Hospital	OTHER
Tianjin People's Hospital	OTHER
Tianjin Nankai Hospital

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

The primary aim of this study is

- to explore the usefulness of Artificial Intelligence system in colonoscopy on adenoma detection rate (ADR). Other aims include to explore the data below when Artificial Intelligence is used.

Mean adenomas detected per procedure, MAP Proximal Adenoma detection rate, pADR Polyp detection rate, PDR Proximal polyp detection rate, pPDR Mean polyps detected per procedure, MPP Withdrawal time, WT Cecal intubation rate, CIR Cecal intubation time, CIT

Detailed Description

Colorectal cancer is common in China. Most colorectal cancers happen when an adenoma becomes cancerous. Doctors use colonoscopy to look inside the colon and rectum and find adenomas and remove them. Removing adenomas is known to reduce the chances of a person developing colorectal cancers. The ability of colonoscopists finding adenomas varies, and there is a lot of researches into how to improve "adenoma detection rates".

A new AI system, called the CSK endoscopic diagnosis and treatment system has been designed to improve the rate of polyp detection at colonoscopy. Previous tests have shown that there is a significant improvement in detection of adenomas when the system is used. This study will randomize patients coming for colonoscopy to have their procedure performed as usual or as an AI-assisted colonoscopy. The investigators will record polyp and adenoma detection rates, duration of procedure, participant comfort levels, and complications. All patients referred for colonoscopy will be invited in 4 centers, recruiting a total of 800 participants.

Design Module

Study Type

Interventional

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Not provided

Target Follow-Up Duration

Not provided

Phases

Not Applicable

Interventional Study Design

Allocation

Biospecimen

No data available

No data is available for this block.

Enrollment

743Actual

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
AI-assisted Colonoscopy	Experimental	Participants in this arm undergo AI-assisted colonoscopy using CSK AI system.	Device: CSK AI system
Standard Colonoscopy	Active Comparator	Participants in this arm undergo standard colonoscopy.	Device: Standard Colonoscopy

Interventions

Name	Type	Description	Arm Group Labels	Other Names
CSK AI system	Device	CSK system is equipped with the endoscopic mainframe and alarms the examiners when suspect lesions appear.	AI-assisted Colonoscopy

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Adenoma detection rate, ADR	ADR refer to the rate of adenoma detection, calculated as the proportion of subjects with at least one adenoma.	At the end of the procedure, up to 1 hour.

Secondary Outcomes

Measure	Description	Time Frame
Polyp detection rate, PDR	PDR refer to the rate of polyp detection, calculated as the proportion of subjects with at least one polyp.	At the end of the procedure, up to 1 hour.

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

All patients referred for screening, surveillance, or diagnostic colonoscopy
All patients must be able to give informed consent

Exclusion Criteria:

Patients with any absolute contraindications to colonoscopy
Patients with established or suspicion of large bowel obstruction or pseudo-obstruction
Patients with known colon cancer or polyposis syndromes
Patients with known colonic strictures
Patients with known severe diverticular segments (that is likely to impede colonoscope passage)
Patients with active colitis (ulcerative colitis, Crohn's colitis, diverticulitis, infective colitis)
Patients lacking capacity to give informed consent
Pregnancy
Patients who are on clopidogrel, warfarin, or other new generation anticoagulants who have not stopped this for the procedure.
Patients who are attending for a therapeutic procedure or assessment of a known lesion

Accepts Healthy Volunteers

Yes

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

45 Years

Maximum Age

80 Years

Standard Ages

AdultOlder Adult

Study Population

Not provided

Sampling Method

Not provided

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Name	Affiliation	Role
En-Da YU, MD	Changhai Hospital	Principal Investigator

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Sixth affiliated Hospital, Sun Yat-Sen University		Guangzhou	Guangdong	510655	China
Shanghai Zhongshan Hospital

IPD Sharing Statement Module

Plan to Share IPD

Description

Not provided

Types

Not provided

Time Frame

Not provided

Access Criteria

Not provided

URL

Not provided

Condition Browse Module

MeSH Terms

ID	Term
D015179	Colorectal Neoplasms
D003111	Colonic Polyps
D000236	Adenoma

Ancestor Terms

ID	Term
D007414	Intestinal Neoplasms
D005770	Gastrointestinal Neoplasms
D004067	Digestive System Neoplasms
D009371	Neoplasms by Site

Browse Leaves

Not provided

Browse Branches

Not provided

Intervention Model Description

CSK endoscopic diagnosis and treatment system a new system of artificial intelligence. It is manufactured by Tianjin Yujin Limited in China. It is equipped with the endoscopic mainframe and has the access to the endoscopic video and image. When lesion-like objects appear in the real-time video, the system will alarm the examiners by sound.