Artificial Intelligence Clinical Trial
Official title:
A Prospective Evaluation of the Correlation Between Real Time Artificial Intelligence-derived Effective Withdrawal Time and Adenoma Detection Rate
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
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 After cecal intubation is performed, the colonoscopy is slowly withdrawn.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. ;
| 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 |
NCT05006092 -
Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE)
|
N/A | |
| Completed |
NCT04816981 -
AI-EBUS-Elastography for LN Staging
|
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
|