Artificial Intelligence to Implement Cost-saving Strategies for Colonoscopy Screening Based on in Vivo Prediction of Polyp Histology (SAVE)
Saving by Artificial Intelligence for Virtual Endoscopy Biopsy Artificial Intelligence to Implement Cost-saving Strategies for Colonoscopy Screening Based on in Vivo Prediction of Polyp Histology
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Cesare Hassan
- Phone Number: 02-82247385
- Email: cesare.hassan@hunimed.eu
Study Locations
-
-
Milano
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Rozzano, Milano, Italy, 20089
- Recruiting
- Istituto Clinico Humanitas
-
Principal Investigator:
- Cesare Hassan
-
Contact:
- Cesare Hassan, Prof/MD
- Phone Number: 0039-02-82247385
- Email: cesare.hassan@hunimed.eu
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- All >40 years-old patients undergoing colonoscopy for selected indications
Exclusion Criteria:
- patients with personal history of CRC, or IBD
- patients affected with Lynch syndrome or Familiar Adenomatous Polyposis.
- patients with inadequate bowel preparation (defined as Boston Bowel Preparation Scale <2 in any colonic segment).
- patients with previous colonic resection.
- patients on antithrombotic therapy, precluding polyp resection.
- patients who were not able or refused to give informed written consent.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Prevention
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Active Comparator: Standard Arm CADe
Standard, high-definition colonoscopy with the use of CADe assistance (GI-GENIUS, Medtronic; CAD-EYE, Fujifilm; WISE VISION ,NEC).
All detected polyps regardless of size and optical diagnosis will be resected and sent to pathology.
|
All detected polyps regardless of size and optical diagnosis will be resected and sent to pathology.
|
|
Active Comparator: Standard Arm CADe/CADx
Standard, high-definition colonoscopy with the use of CADe/CADx assistance (GI-GENIUS, Medtronic; CAD-EYE, Fujifilm; WISE VISION ,NEC).
All detected polyps regardless of size and optical diagnosis will be resected and sent to pathology.
|
Device: Standard, high-definition colonoscopy with the use of CADe/CADx assistance, no leave-in-situ
All detected polyps regardless of size and optical diagnosis will be resected and sent to pathology.
|
|
Experimental: Leave-In-Situ Arm
Standard, high-definition colonoscopy with the use of CADe/CADx assistance (GI-GENIUS, Medtronic; CAD-EYE, Fujifilm; WISE VISION, NEC). Polyps will be left in situ if diminutive (≤5 mm) in size, located in the rectum or sigma and optically diagnosed by the endoscopist using the system to be hyperplastic with high confidence, otherwise resected and sent to pathology. |
Polyps will be left in situ if diminutive (≤5 mm) in size, located in the rectum or sigma and optically diagnosed by the endoscopist using the system to be hyperplastic with high confidence, otherwise resected and sent to pathology.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Non-inferiority in Adenoma Detection Rate
Time Frame: 4 years
|
Non-inferiority in the Adenoma Detection Rate, defined as the proportion of participants with at least one adenoma (per-patient analysis) in the three arms, when adopting a cost-saving leave-in-situ strategy for non-neoplastic rectosigmoid diminutive polyps.
|
4 years
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Negative Predictive Value for colorectal neoplasia
Time Frame: 4 years
|
Negative Predictive Value for colorectal neoplasia when adopting a leave-in-situ strategy for rectosigmoid diminutive polyps based on the use of Artificial Intelligence.
|
4 years
|
|
Concordance between post-polypectomy surveillance and when adopting a leave-in-situ strategy
Time Frame: 4 years
|
Concordance between post-polypectomy surveillance based on strategies based on optical diagnosis with Artificial Intelligence and those based on histology, and when adopting a leave-in-situ strategy for colorectal diminutive polyps based on the use of Artificial Intelligence
|
4 years
|
|
Change in the cost of polypectomy and histology in screening programs
Time Frame: 4 years
|
Change in the cost of polypectomy and histology in screening programs, when implementing strategies based on Artificial Intelligence-based optical biopsy, without changes in benefit related with detection of colorectal neoplasia
|
4 years
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 3483 - SAVE
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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