Clinical trial NCT03359343: Computer-assisted Diagnosis System Based on Linked Colour Imaging
Official title: Computer-aided Classification of Colorectal Polyp by Using Linked Colour Imaging
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Colorectal Polyp
Linked Color Imaging
Computer-aided Diagnosis
Lead sponsor: Affiliated Hospital to Academy of Military Medical Sciences
Sponsor class: OTHER
First posted: 2017-12-02
Enrollment: 250
Sex: ALL
Minimum age (years): 16
Maximum age (years): 80
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: consecutive patients undergoing colonoscopy

Brief summary: Linked color imaging (LCI)，a new endoscopy modality, creates clear and bright images by using short wavelength narrow band laser light. LCI can make red area appear redder and white areas appear whiter. Thus, it may be possible to distinguish adenoma and non-adenoma polyps based on color evaluation of LCI images. This study aimed to assess the correlation between histology results and LCI images. Moreover, the investigators conducted a pilot study to explore the clinical potential of LCI to distinguish adenoma and non-adenoma polyps and the accuracy of an automatic computer-aided diagnosis system using LCI imagine to predict histology polyps when compared to human experts physicians.

Detailed description: This study consists of a retrospective analysis and a pilot study. In the retrospective study, the investigators tried to find out an correlation between LCI images and histology results for polyp lesions. And a computer-aided analysis of the images was conducted to demonstrate the correlation objectively. Thereafter,a pilot study was performed to explore whether the previous correlation could be easily learned to distinguish adenoma and non-adenoma polyps by comparing the results of experts diagnosis of LCI image and non-experts. Also, in the pilot study, the investigators assessed the accuracy of an automate histology diagnosis method for polyp LCI images using the computer-aided system when compared to human experts physicians. Throughout the entire research, histology results are regarded as gold standard.

Eligibility criteria: Inclusion Criteria:

- at least one polyp found during colonoscopy examination.

Exclusion Criteria:

- poor quality of bowel preparation which impedes histology evaluation; previous resection of colon; inflammatory bowel disease; familiar adenomatous polyposis; Peutz-Jeghers syndrome or other polyposis syndrome.

Primary outcomes:
measure: LCI accuracy
timeFrame: June 1, 2018
Secondary outcomes:
measure: the short learning curve
timeFrame: June 1, 2018
measure: the correlation
timeFrame: June 1, 2018
Other outcomes:
Locations:
city: Beijing
country: China
facility: Affiliated Hospital to Academy of Military Medical Sciences
state: Beijing
city: Beijing
country: China
facility: Department of Gastroenterology, Affilited Hospital to Academy of Military Medical Sciences
Study officials:
affiliation: Department of gastroenterology, Affiliated Hospital to Academy of Military Medical Sciences.
name: Yan Liu
role: STUDY_DIRECTOR
References:
citation: Fukuda H, Miura Y, Hayashi Y, Takezawa T, Ino Y, Okada M, Osawa H, Lefor AK, Yamamoto H. Linked color imaging technology facilitates early detection of flat gastric cancers. Clin J Gastroenterol. 2015 Dec;8(6):385-9. doi: 10.1007/s12328-015-0612-9. Epub 2015 Nov 11.
citation: Sun X, Dong T, Bi Y, Min M, Shen W, Xu Y, Liu Y. Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study. Sci Rep. 2016 Sep 19;6:33473. doi: 10.1038/srep33473.
citation: Dohi O, Yagi N, Onozawa Y, Kimura-Tsuchiya R, Majima A, Kitaichi T, Horii Y, Suzuki K, Tomie A, Okayama T, Yoshida N, Kamada K, Katada K, Uchiyama K, Ishikawa T, Takagi T, Handa O, Konishi H, Naito Y, Itoh Y. Linked color imaging improves endoscopic diagnosis of active Helicobacter pylori infection. Endosc Int Open. 2016 Jul;4(7):E800-5. doi: 10.1055/s-0042-109049.