Maastricht University Medical Center
Maastricht, Limburg, 6202AZ, Netherlands
NCT Number: NCT04349787
Primary, this study aims to develop and validate a computer-aided diagnosis (CADx) system for the characterization of colorectal polyps.
Second, this study evaluates the effect of using a clinical classification model Blue Light Imaging Adenoma Serrated International (BASIC) on the diagnostic accuracy of the optical diagnosis of colorectal polyps compared to intuitive optical diagnosis for both expert endoscopists and novices.
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Notify Me18 year and older
All sexes
Observational
Maastricht, Limburg, 6202AZ, Netherlands
Optical diagnosis of colorectal polyps, the in-vivo characterization of the histology by endoscopists, is of increasing interest for clinical endoscopy practice. Recent studies have shown that thresholds for optical diagnosis are met in highly selected groups of expert endoscopists, but the same is not true in community endoscopy practices. In order to improve optical diagnosis, imaging enhancement techniques and the use of artificial intelligence are proposed.
This observational study developes a computer-aided diagnosis (CADx) system to differentiate between benign and (pre-)malignant CRPs, using state-of-the-art machine learning methods and deep learning architectures. For the development, HDWL and BLI images are used. The CADx is trained using histology as gold standard. The CADx is externally validated using on a set of 60 colorectal polyps. This study will evaluate if the optical diagnosis of colorectal polyps can be improved with the aid of CADx.
In addition, both expert endoscopists and novices optically diagnose the colorectal polyps. In the first, pre-training phase, endoscopists optically diagnose colorectal polyps based on intuition. Afterwards, in the post-training phase, the same set of colorectal polyps is optically diagnosed based on a clinical classification system; BLI Adenoma Serrated International Classification (BASIC). This study will evaluate if the optical diagnosis of colorectal polyps can be improved with the aid of BASIC in both expert and non-expert hands.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Optical diagnosis of colorectal polyps made with computer-aided diagnosis (CADx) using state-of-the-art machine learning methods and deep learning architectures.
Optical diagnosis of colorectal polyps made with BLI Adenoma Serrated International Classification (BASIC), both by exert endoscopists and novices.
Time frame: 6 months
The diagnostic accuracy of characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx in comparison to the diagnostic accuracy of both expert endoscopists and novices. In which histology is the gold standard.
Time frame: 6 months
The diagnostic accuracy of both expert endoscopists and novices in characterizing colorectal polyps (into hyperplastic polyp, adenoma, sessile serrated adenoma, or adenocarcinoma) based on the clinical classification model BASIC, in comparison to the diagnostic accuracy based on intuition. In which histology is the gold standard.
Time frame: 6 months
The sensitivity, specificity, negative and positive predictive value of characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx.
Time frame: 6 months
Area Under ROC Curve (AUC) of CADx for characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx.
Time frame: 6 months
The sensitivity, specificity, negative and positive predictive value of characterizing colorectal polyps (into hyperplastic polyp, adenoma, sessile serrated adenoma, or adenocarcinoma) of both expert endoscopists and novices.
Time frame: 6 months
The diagnostic accuracy, sensitivity, specificity, negative and positive predictive value of both expert endoscopists and novices for optical diagnosis made with high (>90%) confidence.
Time frame: 6 months
The interobserver agreement of experts, novices and CADx for characterizing colorectal polyps.
Time frame: 6 months
The computation time per image of CADx for characterizing colorectal polyps.
Maastricht University Medical Center
Other
Improving Optical Diagnosis of Colorectal Polyps Using Computer-aided Diagnosis (CADx) and the BLI Adenoma Serrated International Classification (BASIC).
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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