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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT04607083
Other study ID # 599/2020
Secondary ID
Status Completed
Phase
First received
Last updated
Start date October 22, 2020
Est. completion date March 30, 2021

Study information

Verified date June 2021
Source Valduce Hospital
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Recently, a CNN-based artificial intelligence (AI) system for polyp characterization has been developed by Fujifilm Co., Tokyo, Japan. It works in conjunction with BLI system. In the present study we prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in characterization (i.e. as adenomas or non-adenomas) of diminutive rectosigmoid polyps having histopathology as reference standard. Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected are included. During endoscopic procedures all polyps identified by the endoscopist are documented for size, location and morphology. All diminutive polyps are characterized by a three sequential steps process: I) endoscopist prediction: the endoscopist evaluates the polyp by using BLI through the BASIC classification; the confidence level (high vs. low) in histology prediction is recorded; II) AI prediction: the AI system is switched on and the output of the automatic evaluation is recorded; this outcome is rated as stable or unstable, depending of the consistency over time of the outcome; III) combined prediction: a final classification is provided by endoscopist in light of the results of the first and of the second step; the confidence level is recorded. All polyps are resected and retrieved in separate jars and sent for pathology assessment. Only polyps characterized with high confidence will be included in the per-polyp analysis; the high-confidence characterization rate will be also calculated; the rate of polyps characterized with a CAD stable outcome will be calculated. Operative characteristics (sensitivity, specificity, positive and negative predictive value and accuracy) in distinguishing adenomatous from non-adenomatous polyps, evaluated with high confidence, will be calculated for each diminutive polyp and for each diminutive rectosigmoid polyp, having histopathology report as reference standard. The post-polypectomy surveillance intervals will be calculated on the basis of polyp histology (reference standard) in all patients according to both USMSTF and ESGE guidelines.


Recruitment information / eligibility

Status Completed
Enrollment 1134
Est. completion date March 30, 2021
Est. primary completion date February 27, 2021
Accepts healthy volunteers
Gender All
Age group 18 Years to 85 Years
Eligibility Inclusion Criteria: - Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected. Exclusion Criteria: - patients with CRC history or hereditary polyposis syndromes or hereditary non-polyposis colorectal cancer - patients with inadequate bowel preparation - patients scheduled for partial examinations - polyps could not be resected due to ongoing anticoagulation preventing resection and pathologic assessment - patients undergoing urgent colonoscopy

Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
Polyp carachterization by combing endoscopist evaluation and Ai output
A polyp characterization (adenoma vs. non adenoma) is provided by endoscopist in light of the results of this own evaluation and of the Ai system output. The confidence level (high vs. low) in polyp characterization is recorded. The combined evaluation is compared with histopathology results.

Locations

Country Name City State
Italy Gastroenterology Unit, Valduce Hospital Como

Sponsors (1)

Lead Sponsor Collaborator
Valduce Hospital

Country where clinical trial is conducted

Italy, 

Outcome

Type Measure Description Time frame Safety issue
Primary Agreement of combined prediction with PIVI I statement To prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in characterization (i.e. as adenomas or non-adenomas) of diminutive rectosigmoid polyps (i.e. PIVI I threshold) having histopathology as reference standard. 6 months
Secondary Endoscopist prediction to calculate the performance measures (sensitivity, specificity, positive and negative predictive value) of the endoscopist alone in characterizing diminutive rectosigmoid polyps 6 months
Secondary Ai prediction - to calculate the performance measures (sensitivity, specificity, positive and negative predictive value) of the AI system alone in characterizing diminutive rectosigmoid polyps 6 months
Secondary Agreement of combined prediction with PIVI II statement - to evaluate if the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in the assignment of post-polypectomy surveillance intervals, according to US and EU guidelines, when combined with the histopathology assessment of polyps >5 mm in size 6 months