Prospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastrointest Endosc. Mar 8, 2024; 5(1): 90574
Published online Mar 8, 2024. doi: 10.37126/aige.v5.i1.90574
Artificial intelligence for characterization of diminutive colorectal polyps: A feasibility study comparing two computer-aided diagnosis systems
Quirine Eunice Wennie van der Zander, Ramon M Schreuder, Ayla Thijssen, Carolus H J Kusters, Nikoo Dehghani, Thom Scheeve, Bjorn Winkens, Mirjam C M van der Ende - van Loon, Peter H N de With, Fons van der Sommen, Ad A M Masclee, Erik J Schoon
Quirine Eunice Wennie van der Zander, Ayla Thijssen, Ad A M Masclee, Department of Gastroenterology and Hepatology, Maastricht University Medical Center, Maastricht 6202 AZ, Netherlands
Quirine Eunice Wennie van der Zander, Ayla Thijssen, Erik J Schoon, GROW, School for Oncology and Reproduction, Maastricht University, Maastricht 6200 MD, Netherlands
Ramon M Schreuder, Mirjam C M van der Ende - van Loon, Erik J Schoon, Division of Gastroenterology and Hepatology, Catharina Hospital Eindhoven, Eindhoven 5602 ZA, Netherlands
Carolus H J Kusters, Nikoo Dehghani, Thom Scheeve, Peter H N de With, Fons van der Sommen, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5600 MB, Netherlands
Bjorn Winkens, Department of Methodology and Statistics, Maastricht University, Postbus 616, 6200 MD Maastricht, Netherlands
Bjorn Winkens, School for Public Health and Primary Care, Maastricht University, Maastricht 6200 MD, Netherlands
Author contributions: van der Zander QEW, Schreuder RM, Masclee AAM, and Schoon EJ substantially contributed to the study design; van der Zander QEW developed the study protocol under supervision of Masclee AAM and Schoon EJ, Kusters CHJ, Dehghani N, Scheeve T, de With PHN, and van der Sommen F developed the in-house CADx-system AI4CRP; van der Zander QEW, Schreuder RM, Thijssen A, and van der Ende - van Loon MCM did the data acquisition and processed the data; van der Zander QEW did the data analyses; Winkens B oversaw the data analyses and provided critical review of the data analyses; van der Zander QEW did the data interpretation and drafted the manuscript; Schreuder RM, Thijssen A, Kusters CHJ, Dehghani N, Scheeve T, Winkens B, van der Ende - van Loon MCM, de With PHN, van der Sommen F, Masclee AAM, and Schoon EJ provided a constructive review of the manuscript for important intellectual content. All authors approved the final version of the manuscript before submission. All authors had full access to all the data in the study and accept responsibility for all aspects of the work regarding accuracy, integrity, and publication.
Supported by Dutch Cancer Society, No. 12639.
Institutional review board statement: The Medical Research Ethics Committees United (W20.239, July 2021) approved the study.
Clinical trial registration statement: This study is registered at (NCT05349110).
Informed consent statement: All patients provided written informed consent.
Conflict-of-interest statement: Author QvdZ was supported by Fujifilm Inc. to attend scientific meetings, outside the submitted work. Author FvdS received research support from Olympus, outside the submitted work. Author AM was supported by a health care efficiency grant from ZonMw, an unrestricted research grant from Will Pharma S.A., a restricted educational grant from Ferring B.V., a research grant from Pentax Europa, research funding from Allegan and Grünenthal, and gave scientific advice to Bayer, Kyowa Kirin, and Takeda, outside the submitted work. Author ES received research support and speakers’ fees from Fujifilm Inc., outside the submitted work. Authors PdW, FvdS, AM, and ES report a joined research grant from the Dutch Cancer Society for the submitted work (project number 12639). Fujifilm Inc. provided the CAD EYE equipment on loan to the Catharina Hospital Eindhoven. Authors RMS, AT, CK, ND, TS, BW, and MvE declare no conflicts of interests.
Data sharing statement: The data supporting the findings of this study are available from the corresponding author upon reasonable request. This data includes deidentified participant data. Additional documents that will be made available are the study protocol, the statistical analysis plan, and the informed consent forms. Data will be available following publication with no end date. Requests should be methodologically sound proposals with the purpose to achieve aims in the approved proposal. Data requestors will need to sign a data access agreement after approval of a proposal.
CONSORT 2010 statement: The authors have read the CONSORT 2010 statement, and the manuscript was prepared and revised according to the CONSORT 2010 statement.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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: Quirine Eunice Wennie van der Zander, MD, MSc, Researcher, Department of Gastroenterology and Hepatology, Maastricht University Medical Center, Postbus 5800, Maastricht 6202 AZ, Netherlands.
Received: December 7, 2023
Peer-review started: December 7, 2023
First decision: December 29, 2023
Revised: January 11, 2024
Accepted: February 2, 2024
Article in press: February 2, 2024
Published online: March 8, 2024

Artificial intelligence (AI) has potential in the optical diagnosis of colorectal polyps.


To evaluate the feasibility of the real-time use of the computer-aided diagnosis system (CADx) AI for ColoRectal Polyps (AI4CRP) for the optical diagnosis of diminutive colorectal polyps and to compare the performance with CAD EYETM (Fujifilm, Tokyo, Japan). CADx influence on the optical diagnosis of an expert endoscopist was also investigated.


AI4CRP was developed in-house and CAD EYE was proprietary software provided by Fujifilm. Both CADx-systems exploit convolutional neural networks. Colorectal polyps were characterized as benign or premalignant and histopathology was used as gold standard. AI4CRP provided an objective assessment of its characterization by presenting a calibrated confidence characterization value (range 0.0-1.0). A predefined cut-off value of 0.6 was set with values < 0.6 indicating benign and values ≥ 0.6 indicating premalignant colorectal polyps. Low confidence characterizations were defined as values 40% around the cut-off value of 0.6 (< 0.36 and > 0.76). Self-critical AI4CRP’s diagnostic performances excluded low confidence characterizations.


AI4CRP use was feasible and performed on 30 patients with 51 colorectal polyps. Self-critical AI4CRP, excluding 14 low confidence characterizations [27.5% (14/51)], had a diagnostic accuracy of 89.2%, sensitivity of 89.7%, and specificity of 87.5%, which was higher compared to AI4CRP. CAD EYE had a 83.7% diagnostic accuracy, 74.2% sensitivity, and 100.0% specificity. Diagnostic performances of the endoscopist alone (before AI) increased non-significantly after reviewing the CADx characterizations of both AI4CRP and CAD EYE (AI-assisted endoscopist). Diagnostic performances of the AI-assisted endoscopist were higher compared to both CADx-systems, except for specificity for which CAD EYE performed best.


Real-time use of AI4CRP was feasible. Objective confidence values provided by a CADx is novel and self-critical AI4CRP showed higher diagnostic performances compared to AI4CRP.

Keywords: Artificial intelligence, Colorectal polyp characterization, Computer aided diagnosis, Diminutive colorectal polyps, Optical diagnosis, Self-critical artificial intelligence

Core Tip: In this study, two computer-aided diagnosis systems (CADx) [Artificial intelligence for ColoRectal polyps (AI4CRP) and CAD EYE] were compared head-to-head and showed that real-time use was feasible in clinical practice, but does not yet meet quality standards for optical diagnosis. AI4CRP provided characterizations accompanied by confidence values, enabling self-critical AI4CRP in which low confidence characterizations were excluded. Self-critical AI4CRP resulted in considerably higher diagnostic performances compared to AI4CRP. The AI-assisted endoscopists, optically diagnosing colorectal polyps after reviewing both CADx characterizations, had non-significantly higher diagnostic performances compared to the endoscopist alone (before CADx).