Literature DB >> 30342029

Automated polyp detection in the colorectum: a prospective study (with videos).

Peter Klare1, Christoph Sander1, Martin Prinzen2, Bernhard Haller3, Sebastian Nowack2, Mohamed Abdelhafez1, Alexander Poszler1, Hayley Brown1, Dirk Wilhelm4, Roland M Schmid1, Stefan von Delius5, Thomas Wittenberg2.   

Abstract

BACKGROUND AND AIMS: Adenoma detection is a highly personalized task that differs markedly among endoscopists. Technical advances are therefore desirable for the improvement of the adenoma detection rate (ADR). An automated computer-driven technology would offer the chance to objectively assess the presence of colorectal polyps during colonoscopy. We present here the application of a real-time automated polyp detection software (APDS) under routine colonoscopy conditions.
METHODS: This was a prospective study at a university hospital in Germany. A prototype of a novel APDS ("KoloPol," Fraunhofer IIS, Erlangen, Germany) was used for automated image-based polyp detection. The software functions by highlighting structures of possible polyp lesions in a color-coded manner during real-time colonoscopy procedures. Testing the feasibility of APDS deployment under real-time conditions was the primary goal of the study. APDS polyp detection rates (PDRs) were defined as secondary endpoints provided that endoscopists' detection served as criterion standard.
RESULTS: The APDS was applied in 55 routine colonoscopies without the occurrence of any clinically relevant adverse events. Endoscopists' PDRs and ADRs were 56.4% and 30.9%, respectively. The PDRs and ADRs of the APDS were 50.9% and 29.1%, respectively. The APDS detected 55 of 73 polyps (75.3%). Smaller polyp size and flat polyp morphology were correlated with insufficient polyp detection by the APDS.
CONCLUSION: Computer-assisted automated low-delay polyp detection is feasible during real-time colonoscopy. Efforts should be undertaken to improve the APDS with respect to smaller and flat shaped polyps. (Clinical trial registration number: NCT02838888.).
Copyright © 2019 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2018        PMID: 30342029     DOI: 10.1016/j.gie.2018.09.042

Source DB:  PubMed          Journal:  Gastrointest Endosc        ISSN: 0016-5107            Impact factor:   9.427


  22 in total

Review 1.  State of the Art: The Impact of Artificial Intelligence in Endoscopy 2020.

Authors:  Jiyoung Lee; Michael B Wallace
Journal:  Curr Gastroenterol Rep       Date:  2021-04-14

Review 2.  Optimizing Screening Colonoscopy: Strategies and Alternatives.

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Journal:  Visc Med       Date:  2019-07-09

Review 3.  Artificial Intelligence and Polyp Detection.

Authors:  Nicholas Hoerter; Seth A Gross; Peter S Liang
Journal:  Curr Treat Options Gastroenterol       Date:  2020-01-21

4.  [Digitalization in surgery : What surgeons currently think and know about it-results of an online survey].

Authors:  D Wilhelm; M Kranzfelder; D Ostler; A Stier; H J Meyer; H Feussner
Journal:  Chirurg       Date:  2020-01       Impact factor: 0.955

Review 5.  Artificial Intelligence-Based Polyp Detection in Colonoscopy: Where Have We Been, Where Do We Stand, and Where Are We Headed?

Authors:  Thomas Wittenberg; Martin Raithel
Journal:  Visc Med       Date:  2020-11-12

6.  Automated Classification of Colorectal Neoplasms in White-Light Colonoscopy Images via Deep Learning.

Authors:  Young Joo Yang; Bum-Joo Cho; Myung-Je Lee; Ju Han Kim; Hyun Lim; Chang Seok Bang; Hae Min Jeong; Ji Taek Hong; Gwang Ho Baik
Journal:  J Clin Med       Date:  2020-05-24       Impact factor: 4.241

Review 7.  Artificial Intelligence in Endoscopy.

Authors:  Yutaka Okagawa; Seiichiro Abe; Masayoshi Yamada; Ichiro Oda; Yutaka Saito
Journal:  Dig Dis Sci       Date:  2021-06-21       Impact factor: 3.199

Review 8.  Application of Artificial Intelligence in the Detection and Characterization of Colorectal Neoplasm.

Authors:  Kyeong Ok Kim; Eun Young Kim
Journal:  Gut Liver       Date:  2021-05-15       Impact factor: 4.519

Review 9.  Potential applications of artificial intelligence in colorectal polyps and cancer: Recent advances and prospects.

Authors:  Ke-Wei Wang; Ming Dong
Journal:  World J Gastroenterol       Date:  2020-09-14       Impact factor: 5.742

10.  Artificial inelegance in endoscopy: An updated auricle of Delphi!

Authors:  Majid A Almadi; Khek Yu Ho
Journal:  Saudi J Gastroenterol       Date:  2020 Jan-Feb       Impact factor: 2.485

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