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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT03279783
Other study ID # 341/2017
Secondary ID
Status Recruiting
Phase N/A
First received August 24, 2017
Last updated September 10, 2017
Start date July 1, 2017
Est. completion date December 30, 2017

Study information

Verified date September 2017
Source Valduce Hospital
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

Although colonoscopy with polypectomy can prevent up to 80% of colorectal cancers, a significant adenoma miss rate still exists, particularly in the right colon. Optimizing the detection of adenomas and sessile serrated lesions in the right colon is crucial to increase the effectiveness of colonoscopy in colorectal cancer prevention.

Last generation Fuji videocolonscopes incorporates the Linked Color Imaging (LCI), a recently developed technology that differentiates the red colour spectrum more effectively than White Light imaging thanks to its optimal pre-process composition of light spectrum and advanced signal processing. The increased colour contrast results in more accurate delineation of abnormal inflammatory or neoplastic findings of colonic mucosa. Preliminary data suggest that LCI may be improve the detection of neoplastic lesion of colon.

The investigators performe a tandem prospective study to compare the right colon adenoma miss rates of LCI colonoscopy with those of conventional white light colonoscopy.

Therefore participants scheduled for colonoscopy for the assessment of symptoms or for colorectal cancer screening/surveillance receive the examination of the right colon twice, in a back to back fashion, with standard white light (WL) and with LCI. Patients are randomly assigned (1:1), via computer-generated randomisation with block size of 20, to which procedure is done first. The endoscopist are masked to group allocation until immediately before the cecum is reached. Examinations are performed with Fuji videocolonscopes series 700 (EC-760R, EC-760ZP).


Recruitment information / eligibility

Status Recruiting
Enrollment 752
Est. completion date December 30, 2017
Est. primary completion date December 1, 2017
Accepts healthy volunteers No
Gender All
Age group 18 Years to 80 Years
Eligibility Inclusion Criteria:

- all outpatients referred for colonoscopy

Exclusion Criteria:

- inadequatete bowel preparation (Boston Bowel Preparation Scale (BBPS) < 2 in one colonic segment)

- previous colonic resection

- inflammatory bowel disease

- ereditary polyposic syndromes

- patients on antithrombotics precluding polyp recetion

- absence of informed consent

- inpatients or patients undergoing urgent colonscopy

Study Design


Related Conditions & MeSH terms


Intervention

Device:
LCI (Linked color imaging)
Colonoscope withdrawal was performed in the right colon evaluating the mucosa using LCI (Linked color imaging)

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 Right colon adenoma miss rate Number of adenomas identified during the second right coloninspection/ overall number of adenomas identified during the first and the second right colon inspection One year
Secondary Right colon advanced adenomas (size>1 cm and/or high grade displasia and/or villous component) miss rate Number of advanced adenomas identified during the second right coloninspection/ overall number of advanced adenomas identified during the first and the second right colon inspection One year
Secondary Right colon sessile serrated lesions miss rate Number of sessile serrated lesions identified during the second right coloninspection/ overall number of sessile serrated lesions identified during the first and the second right colon inspection One year
See also
  Status Clinical Trial Phase
Not yet recruiting NCT06406062 - Artificial Intelligence-assisted System in Colonoscopy
Completed NCT03775811 - In Vivo Computer-aided Prediction of Polyp Histology on White Light Colonoscopy