Computer-assisted Diagnosis System Based on Linked Colour Imaging

Colorectal Polyp Clinical Trial

Official title:

Computer-aided Classification of Colorectal Polyp by Using Linked Colour Imaging

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT03359343
• Other study ID #: 307-LCI-CAD
• Status: Recruiting
• Phase: N/A
• First received: November 27, 2017
• Last updated: January 11, 2018
• Start date: October 1, 2017
• Est. completion date: February 1, 2018

Study information

• Verified date: January 2018
• Source: Affiliated Hospital to Academy of Military Medical Sciences
• Contact: Min Min, M.D.
• Phone: +86-010-66947473
• Email: minmin823[@]sina.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 250
• Est. completion date: February 1, 2018
• Est. primary completion date: February 1, 2018
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 16 Years to 80 Years

Eligibility

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.

Related Conditions & MeSH terms

• Colorectal Polyp
• Computer-aided Diagnosis
• Linked Color Imaging
• Polyps

Locations

Country	Name	City	State
China	Affiliated Hospital to Academy of Military Medical Sciences	Beijing	Beijing
China	Department of Gastroenterology, Affilited Hospital to Academy of Military Medical Sciences	Beijing

Sponsors (1)

Lead Sponsor	Collaborator
Affiliated Hospital to Academy of Military Medical Sciences

Country where clinical trial is conducted

China, 

References & Publications (3)

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. — View 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. — View 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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	LCI accuracy	the accuracy between a novel developed computer-aided diagnosis system and human experts physicians o distinguish adenoma polyps and non-adenoma polyps based on LCI image.	June 1, 2018
Secondary	the short learning curve	the accuracy between experts and non-experts to distinguish adenoma polyps and non-adenoma polyps based on LCI image was compared to explore whether LCI method is of an shorter learning curve.	June 1, 2018
Secondary	the correlation	the correlation between LCI image and histology results were retrospectively explored	June 1, 2018