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| Name | Class |
|---|---|
| Meditrial Europe Ltd. | INDUSTRY |
| Meditrial USA Inc. | INDUSTRY |
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This is a prospective, multicenter, randomized study to evaluate the clinical performance of a novel CADe device, WISE VISION® Endoscopy System, in patients undergoing high-definition white light (HDWL) colonoscopy for screening or surveillance of colorectal Cancer (CRC).
Eligible subjects who meet the study inclusion/exclusion criteria will be randomized in a 1:1 ratio to undergo colonoscopy :
This study aims to evaluate whether NEC WISE VISION® Endoscopy enhances the ability to detect mucosal lesions when compared with the current standard-of-care procedure (high-definition white light [HDWL] colonoscopy). The CADe device, Wise VISION® Endoscopy, contains an artificial intelligence/machine learning (AI/ML) advanced algorithm to aid the endoscopists in detection of colonic lesions.
This study plans to enrol 830 subjects aged ≥ 45 years and < 75 years, who are scheduled for screening or surveillance colonoscopy.
After review of the inclusion and exclusion criteria, eligible subjects will be randomized in a 1:1 ratio to receive either computer-aided colonoscopy (CADe Group) or standard colonoscopy without CADe (Standard Colonoscopy Group).
All adenomas, that are identified during the colonoscopies, will be removed and biopsied as per standard clinical practice to assess adenoma miss rate, polyp miss rate, adenomas per colonoscopy and other endpoints.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| CADe Colonoscopy | Experimental | CADe Colonoscopy: Patient undergoes WISE VISION® Endoscopy CADe colonoscopy |
|
| HDWL Colonoscopy | Active Comparator | HDWL Colonoscopy: Patient undergoes HDWL colonoscopy without CADe |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Computer Aided Detection (CADe) | Diagnostic Test | Computer-aided detection (CADe) devices are used in conjunction with colonoscopy to aid in the detection of lesions in the gastrointestinal tract. |
| Measure | Description | Time Frame |
|---|---|---|
| Adenomas per Colonoscopy (APC) | Total number of histologically confirmed adenomas resected divided by the total number of colonoscopies. | during the procedure/surgery |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Hitoshi Ikeda | NEC Corporation | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Kansas City VA Hospital | Kansas City | Missouri | 64128 | United States | ||
| GastroZentrum Lippe |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31594962 | Background | Yamada M, Saito Y, Imaoka H, Saiko M, Yamada S, Kondo H, Takamaru H, Sakamoto T, Sese J, Kuchiba A, Shibata T, Hamamoto R. Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy. Sci Rep. 2019 Oct 8;9(1):14465. doi: 10.1038/s41598-019-50567-5. |
| Label | URL |
|---|---|
| Meditrial Clinical Research Organization | View source |
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| ID | Term |
|---|---|
| D015179 | Colorectal Neoplasms |
| D003111 | Colonic Polyps |
| ID | Term |
|---|---|
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
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Parallel trial design
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| Bad Salzuflen |
| Germany |
| Humanitas Mater Domini | Castellanza | Italy |
| Humanitas Research Hospital | Milan | 20089 | Italy |
| Portsmouth Hospitals University NHS Trust, Cosham | Portsmouth | PO6 3LY | United Kingdom |
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D012002 | Rectal Diseases |
| D007417 | Intestinal Polyps |
| D011127 | Polyps |
| D020763 | Pathological Conditions, Anatomical |
| D013568 | Pathological Conditions, Signs and Symptoms |