Discussion
polyp, polyps, non-neoplastic diminutive, diminutive polyps, colorectal polyps
REGRESSION, COLORECTAL POLYPS

To improve the accuracy and reliability of endoscopists’ optical diagnosis of diminutive (1–5 mm) colorectal polyps, numerous CADx systems based on machine learning techniques have been developed

During real-time endoscopy, the POLAR system achieved an accuracy of 79 % for differentiating neoplastic from non-neoplastic diminutive polyps, an accuracy that was comparable to that of 20 screening endoscopists from eight hospitals. Neither the system nor the endoscopists were able to achieve the SODA-1, SODA-2, or PIVI-2 competence standards required for safe implementation of the optical diagnosis strategy for diminutive polyps

Apart from the strict validation approach, another explanation for the suboptimal specificity and NPV may be the fact that our study is one of the few to also include the optical diagnosis of SSLs in the CADx system
We believe we have reached the point at which big improvements in the performance of our model (and potentially also other systems) are nearly impossible with the data that we currently have. The performance of the models could be improved by increasing the quantity of data, but more importantly by improving the variety and quality of the data. Even though the dataset that was used to train and test the system in this study was broad and diverse, we noticed that some polyps were more difficult to collect in daily practice because they are relatively rare or not removed in clinical practice (e. g. diminutive HPPs in the rectosigmoid). These rare or not removed polyps might be even more relevant for the development of a CADx system. Although we have done our utmost to collect high quality training data in a standardized manner, we do believe that even more rigorous data collection should be done. This hypothesis was supported by our multivariate regression analysis, which demonstrated that POLAR performed better when endoscopists with the highest accuracy for optical diagnosis were taking the images. This suggests that there are differences between the quality of the images collected by the best and least performing endoscopists. We strongly believe that if these differences can be identified, they would yield extremely useful insights as to how we can improve the quality of image collection and build better performing CADx systems.
Potential limitations of this study should also be mentioned. First, our CADx system was specifically trained and validated only on NBI. As white-light endoscopy is the most basic and available endoscopy diagnostic modality, application of CADx to white-light endoscopy would be beneficial
To conclude, we report the development and validation of a CADx system, suitable for performing optical diagnosis of diminutive colorectal polyps during endoscopy, using a maximum of three NBI images. In a multicenter setting, the system achieved an accuracy for neoplastic diminutive polyp diagnosis that was comparable to that of a group of screening endoscopists. The methodology of this study provides a reliable diagnostic accuracy of the POLAR system in daily practice. To increase the diagnostic accuracy of this and other CADx systems, efforts should be made to improve the variety, but most importantly the quality, of data.