Clinical Trials Logo

Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT06063720
Other study ID # AIeffectiveV3
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date November 1, 2023
Est. completion date December 30, 2024

Study information

Verified date April 2024
Source The University of Hong Kong
Contact Ka Luen Thomas Lui
Phone +852 97360997
Email tkllui@hku.hk
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The goal of this observational study is to assess the correlation between the artificial intelligence (AI) derived effective withdrawal time (EWT) during colonoscopy and endoscopists' baseline adenoma detection rate (ADR). The association between the AI derived EWT with ADR during the prospective colonoscopy series would also be determined. The colonoscopy video of participants will be monitored by the AI and the result of EWT will be blinded to the endoscopists


Description:

This is a prospective colonoscopy trial using artificial intelligence (AI) real time effective mucosal examination monitor system (EndoScreener QC, Wision A.I. Shanghai & Chengdu). Low residue diet will be taken by all patients two days before the scheduled colonoscopy. Oral polyethylene glycol lavage solution is used for bowel preparation as in usual hospital practice. All examination will be performed with high-definition endoscopes (EVIS-EXERA 290 video system, Olympus Optical, Tokyo, Japan) under white light by experienced endoscopists. In all colonoscopy examination, colonoscope will be first advanced to the cecum as confirmed by identification of the appendiceal orifice and ileocecal valve or by intubation of the ileum. After cecal intubation is performed, the colonoscopy is slowly withdrawn. All detected polyps will be removed during the withdrawal only. The size (measured with biopsy forceps), location and morphology of each polyp will be recorded by an independent observer. The withdrawal time (minus the polypectomy site) will be measured by a stopwatch and with a minimum of 6 minutes. The bowel preparation quality will be graded according to the Boston Bowel Preparation Scale. The AI derived (AI) real time effective mucosal examination monitor system (EndoScreen QC) will be initiated during scope withdrawal, starting from cecum to anus. The polypectomy or biopsy time will be removed as determination of standard withdrawal time. All endoscopists will be blinded to the results of AI real time monitoring of EWT. All polyp specimens removed will be clearly labelled and send for histological examination. All resected and biopsy specimens are fixed in 10% buffered formalin solution, and examined histologically by hematoxylin and eosin staining. The histopathological diagnosis is determined by experienced pathologists, who are blinded to the assigned endoscopic system, according to the World Health Organization (WHO) criteria. Advanced adenomas are defined as adenoma ≥10 mm in diameter or with villous histology in 25% or high-grade dysplasia (HGD), or carcinoma.The primary outcome of this study is to correlate the adenoma detection rates of the endoscopists with EWT.


Recruitment information / eligibility

Status Recruiting
Enrollment 198
Est. completion date December 30, 2024
Est. primary completion date July 31, 2024
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 40 Years and older
Eligibility Inclusion Criteria: All adult patients, aged 40 or above, undergoing outpatient colonoscopy will be recruited Exclusion Criteria: - history of inflammatory bowel disease - history of colorectal cancer - previous bowel resection (apart from appendectomy) - Peutz-Jeghers syndrome, familial adenomatous polyposis or other polyposis syndromes - bleeding tendency or severe comorbid illnesses for which polypectomy is considered unsafe. - Cecum could not be intubated for various reasons - Poor bowel preparation with Boston Bowel Preparation Scale (BBPS) < 6

Study Design


Intervention

Device:
Endoscreen QC
Artificial intelligence monitoring of effective withdrawal time

Locations

Country Name City State
Hong Kong Queen Mary Hospital, the University of Hong Kong Hong Kong

Sponsors (1)

Lead Sponsor Collaborator
The University of Hong Kong

Country where clinical trial is conducted

Hong Kong, 

Outcome

Type Measure Description Time frame Safety issue
Primary Adenoma detection rates of the endoscopists Adenoma detection rates of the endoscopists Historical record of the endoscopists up to 7 years
Secondary Adenoma detection rate Adenoma detection rates of the colonoscopy During that colonoscopy
Secondary Polyp detection rate Polyp detection rates of the colonoscopy During that colonoscopy
See also
  Status Clinical Trial Phase
Completed NCT04589078 - Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
Completed NCT03857438 - Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
Completed NCT04735055 - Artificial Intelligence Prediction for the Severity of Acute Pancreatitis
Not yet recruiting NCT05452993 - Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography N/A
Not yet recruiting NCT04337229 - Evaluation of Comfort Behavior Levels of Newborns With Artificial Intelligence Techniques N/A
Completed NCT05687318 - A Clinical Trial of the Effectiveness and Safety of Software Assisting Diagnose the Intestinal Polyp Digestive Endoscopy by Analysis of Colonoscopy Medical Images From Electronic Digestive Endoscopy Equipment N/A
Recruiting NCT06051682 - Optimization of the Diagnosis of Bone Fractures in Patients Treated in the Emergency Department by Using Artificial Intelligence for Reading Radiological Images in Comparison With Traditional Reading by the Emergency Doctor. N/A
Not yet recruiting NCT06039917 - Effect of the Automatic Surveillance System on Surveillance Rate of Patients With Gastric Premalignant Lesions N/A
Not yet recruiting NCT06362629 - AI App for Management of Atopic Dermatitis N/A
Recruiting NCT06059378 - Real-life Implementation of an AI-based Optical Diagnosis N/A
Recruiting NCT06164002 - A I in the Prediction of Clinical Performance, Marginal Fit and Fracture Resistance of Vertical Versus Horizontal Margin Designs Fabricated With 2 Ceramic Materials N/A
Completed NCT05517889 - Repeatability and Stability of Healthy Skin Features on OCT
Completed NCT04816981 - AI-EBUS-Elastography for LN Staging N/A
Completed NCT05006092 - Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE) N/A
Recruiting NCT04535466 - Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
Enrolling by invitation NCT04719117 - Retrograde Cholangiopancreatography AI Assisted System Validation on Effectiveness and Safety
Completed NCT04399590 - Comparing the Number of False Activations Between Two Artificial Intelligence CADe Systems: the NOISE Study
Recruiting NCT04126265 - Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps N/A
Recruiting NCT06255808 - Development of Assist Tool for Breast Examination Using the Principle of Ultrasonic Sensor
Recruiting NCT04131530 - Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence