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Prospective study on clinical practice using ultra magnifying endoscope and artificial intelligence -regarding diagnostic accuracy and image acquisition rate of colorectal tumor and cancer

Not Applicable
Conditions
colorectal tumor and cancer
Registration Number
JPRN-UMIN000027360
Lead Sponsor
Showa University Northern Yokohama Hospital
Brief Summary

Not available

Detailed Description

Not available

Recruitment & Eligibility

Status
Complete: follow-up continuing
Sex
All
Target Recruitment
600
Inclusion Criteria

Not provided

Exclusion Criteria

1.In cases where histological evaluation is impossible (biopsy, pathological evaluation of excised specimens not yet performed). 2.Cases in which pretreatment such as anticancer drug therapy, radiotherapy etc is done. 3.The patient made an offer to refuse to use data with opt-out. 4.A case with inflammatory bowel disease. 5.In addition, cases in which clinical researcher or clinical research sharing doctor judged inappropriate as subject of this examination. .

Study & Design

Study Type
Observational
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
This trial will be triple primary endpoint clinical trial. 1.When EC-CAD was used under methylene blue staining for polyps of 5 mm or less in diameter in the sigmoid colon from the rectum, it was verified that the result diagnosed with high confidence (probability 90% or more) was NPV 90% or more. 2.When observing a polyp of 5 mm or less in diameter with magnifying narrow band imaging (NBI) and NBI combined endocytoscopy (EC-NBI), verify that the ratio at which trainee can acquire a focused endoscope video for 3 seconds or more at EC-NBI. 3.When EC-CAD is used under methylene blue staining for colon lesions of 20 mm or more in diameter, we verify that the diagnostic ability for invasive cancer is over 90% PPV.
Secondary Outcome Measures
NameTimeMethod
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