Basic Study
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Mar 14, 2019; 25(10): 1197-1209
Published online Mar 14, 2019. doi: 10.3748/wjg.v25.i10.1197
Quest for the best endoscopic imaging modality for computer-assisted colonic polyp staging
Georg Wimmer, Michael Gadermayr, Gernot Wolkersdörfer, Roland Kwitt, Toru Tamaki, Jens Tischendorf, Michael Häfner, Shigeto Yoshida, Shinji Tanaka, Dorit Merhof, Andreas Uhl
Georg Wimmer, Roland Kwitt, Andreas Uhl, Department of Computer Sciences, University of Salzburg, Salzburg 5020, Austria
Michael Gadermayr, Dorit Merhof, Interdisciplinary Imaging and Vision Institute Aachen, RWTH Aachen, Aachen 52074, Germany
Gernot Wolkersdörfer, Department of Internal Medicine I, Paracelsus Medical University/Salzburger Landeskliniken (SALK), Salzburg 5020, Austria
Toru Tamaki, Department of Information Engineering, Graduate School of Engineering, Hiroshima University, Hiroshima 7398527, Japan
Jens Tischendorf, Internal Medicine and Gastroenterology, University Hospital Aachen, Würselen 52146, Germany
Michael Häfner, Department of Gastroenterologie and Hepatologie, Krankenhaus St. Elisabeth, Wien 1080, Austria
Shigeto Yoshida, Department of Endoscopy and Medicine, Graduate School of Biomedical and Health Science, Hiroshima University, Hiroshima 7348551, Japan
Shinji Tanaka, Department of Endoscopy, Hiroshima University Hospital, Hiroshima 7348551, Japan
Author contributions: Wimmer G and Gadermayr M performed the experiments; Wimmer G, Gadermayr M, Merhof D and Uhl A coordinated the research; Tamaki T, Tischendorf J, Häfner M, Yoshida S and Tanaka S provided the endoscopic image databases; Wimmer G, Gadermayr M, Wolkersdörfer G and Uhl A wrote the paper.
Supported by the Austrian Science Fund (FWF), KLI project 429, No. TRP206.
Conflict-of-interest statement: There are no conflicts of interest.
Data sharing statement: No additional data are available.
ARRIVE guidelines statement: The authors have read the ARRIVE guidelines, and the manuscript was prepared and revised according to the ARRIVE guidelines.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Corresponding author: Georg Wimmer, PhD, Postdoc, Department of Computer Sciences, University of Salzburg, Jakob Haringer Strasse 2, Salzburg 5020, Austria.
Telephone: +43-662-80446035
Received: December 14, 2018
Peer-review started: December 14, 2018
First decision: January 18, 2019
Revised: February 13, 2019
Accepted: February 15, 2019
Article in press: February 16, 2019
Published online: March 14, 2019
Research background

Colorectal cancer is the second most common cause of cancer death worldwide. Computer-aided decision support systems (CADSSs) aim at helping physicians to detect and classify colonic polyps more accurately. Since about two decades, there is a rising interest in CADSSs and a rising number on publications on CADSSs for colonic polyp staging.

Research motivation

Clinical studies showed that high definition endoscopy, high magnification endoscopy and image enhancement technologies, such as chromoendoscopy and digital chromoendoscopy [narrow-band imaging (NBI), i-Scan] facilitate the detection and classification of colonic polyps during endoscopic sessions. However, there are no comprehensive studies so far that analyze which endoscopic imaging modalities facilitate CADSSs for colonic polyp staging.

Research objectives

In this work, we assess which endoscopic imaging modalities are best suited for the computer-assisted classification of colonic polyps.

Research methods

In our experiments, we apply twelve automated polyp staging systems to five endoscopic image databases of colonic lesions. The image databases were obtained using different endoscopic imaging modalities. By comparing the classification results of the different image databases, we aim to find out which imaging modalities are most suited for the automated classification of colonic polyps.

Research results

The high-definition (HD) image databases obtained with chromoendoscopy achieved overall classification rates of up to 79.2% whereas the HD image databases without chromoendoscopy achieved results up to 88.9%. The classification rates of the image database obtained by high-magnification (HM) chromoendoscopy were up to 81.4%. For the two image databases obtained by HM endoscopy in combination with NBI, one database achieved classification rates up to 97.4%, whereas the other one only achieved classification rates up to 84%.

Research conclusions

The results strongly indicate that chromoendoscopy has a negative impact on the automated diagnosis. The results also indicate that HD and HM endoscopy perform equally well, although the results are not strictly conclusive. Given the higher costs of HM systems and the difficulty in acquiring high quality imagery due to the HM (which definitely requires a well-trained endoscopist), HD systems should be the better option in clinical computer-assisted staging practice. In case of the comparison of chromoendoscopy vs NBI, there are strong indications that NBI is favorable. However, it turned out that the image recording conditions partly contribute to a stronger effect on the staging results than the used imaging modality.

Research perspectives

We showed that CADSSs for colonic polyp staging should not be applied to endoscopic image data obtained by chromoendoscopy, whereas image data obtained by NBI is suited for automated diagnosis systems. Important factors for the success of CADSSs are the image quality of the endoscopic image data and the uniformity of the image recording conditions.