Identifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology

Article

Ahmad, O., Mazomenos, E., Chadebecq, F., Kader, R., Hussein, M., Haidry, R., Puyal, J., Brandao, P., Toth, D. and Mountney, P. 2023. Identifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology. Journal of Gastroenterology and Hepatology. 38 (5), pp. 768-774. https://doi.org/10.1111/jgh.16127
TypeArticle
TitleIdentifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology
AuthorsAhmad, O., Mazomenos, E., Chadebecq, F., Kader, R., Hussein, M., Haidry, R., Puyal, J., Brandao, P., Toth, D. and Mountney, P.
Abstract

Background and Aim
Lack of visual recognition of colorectal polyps may lead to interval cancers. The mechanisms contributing to perceptual variation, particularly for subtle and advanced colorectal neoplasia, have scarcely been investigated. We aimed to evaluate visual recognition errors and provide novel mechanistic insights.

Methods
Eleven participants (seven trainees and four medical students) evaluated images from the UCL polyp perception dataset, containing 25 polyps, using eye-tracking equipment. Gaze errors were defined as those where the lesion was not observed according to eye-tracking technology. Cognitive errors occurred when lesions were observed but not recognized as polyps by participants. A video study was also performed including 39 subtle polyps, where polyp recognition performance was compared with a convolutional neural network.

Results
Cognitive errors occurred more frequently than gaze errors overall (65.6%), with a significantly higher proportion in trainees (P = 0.0264). In the video validation, the convolutional neural network detected significantly more polyps than trainees and medical students, with per-polyp sensitivities of 79.5%, 30.0%, and 15.4%, respectively.

Conclusions
Cognitive errors were the most common reason for visual recognition errors. The impact of interventions such as artificial intelligence, particularly on different types of perceptual errors, needs further investigation including potential effects on learning curves. To facilitate future research, a publicly accessible visual perception colonoscopy polyp database was created.

Keywordsartificial intelligence; colonic polyps; colonoscopy; colorectal cancer
Sustainable Development Goals3 Good health and well-being
Middlesex University ThemeHealth & Wellbeing
PublisherWiley
JournalJournal of Gastroenterology and Hepatology
ISSN0815-9319
Electronic1440-1746
Publication dates
Online18 Jan 2023
PrintMay 2023
Publication process dates
Accepted14 Jan 2023
Deposited12 Feb 2024
Output statusPublished
Publisher's version
License
File Access Level
Open
Digital Object Identifier (DOI)https://doi.org/10.1111/jgh.16127
Web of Science identifierWOS:000920025000001
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