Optical diagnosis of colorectal polyps using high-definition i-scan: An educational experience

AIM: To examine performances regarding prediction of polyp histology high-definition (HD) i-scan in a group of endoscopists with varying experience. METHODS: We used a digital library of HD i-scan still comprising twin pictures (surface enhancement and tone enhancement), our university hospital. We defined endoscopic features of adenomatous non-adenomatous polyps, according to the following parameters: color, pattern and vascular pattern. We familiarized the participating optical diagnosis of colorectal polyps using a 20-min didactic training All endoscopists were asked to evaluate an image set of 50 colorectal regard to polyp histology. We classified the diagnoses into high (i.e., cases in which the endoscopist could assign a diagnosis with and low confidence diagnoses (i.e., cases in which the endoscopist send the polyp for formal histology). Mean sensitivity, specificity and per endoscopist/image were computed and differences between groups independent-samples t tests. High vs low confidence diagnoses were the paired-samples t test. RESULTS: Eleven endoscopists without previous experience on optical diagnosis evaluated a total of 550 images (396 154 non-adenomatous). Mean sensitivity, specificity and accuracy for adenomas were 79.3%, 85.7% and 81.1%, respectively. No significant were found between gastroenterologists and trainees regarding optical diagnosis (mean accuracy 78.0% vs 82.9%, P = 0.098). Diminutive were predicted with a lower mean accuracy as compared to non-diminutive (74.2% vs 93.1%, P = 0.008). A total of 446 (81.1%) diagnoses were made confidence. High confidence diagnoses corresponded to a significantly accuracy than low confidence diagnoses (84.0% vs 64.3%, P = 0.008). A 319 (58.0%) images were evaluated as having excellent quality. excellent quality images in conjunction with high confidence diagnosis, accuracy increased to 92.8%. CONCLUSION: After a single training endoscopists with varying levels of experience can already provide diagnosis with an accuracy of 84.0%.