A comparison of endoscopy versus pathology sizing of colorectal adenomas and potential implications for surveillance colonoscopy

Background and AimsTo compare endoscopy and pathology sizing in a large population-based series of colorectal adenomas and to evaluate the implications for patient stratification into surveillance colonoscopy.MethodsEndoscopy and pathology sizes available from intact adenomas removed at colonoscopies performed as part of the Northern Ireland Bowel Cancer Screening Programme, from 2010 to 2015, were included in this study. Chi-squared tests were applied to compare size categories in relation to clinicopathological parameters and colonoscopy surveillance strata according to current American Gastroenterology Association and British Society of Gastroenterology guidelines.ResultsA total of 2521 adenomas from 1467 individuals were included. There was a trend toward larger endoscopy than pathology sizing in 4 of the 5 study centers, but overall sizing concordance was good. Significantly greater clustering with sizing to the nearest 5 mm was evident in endoscopy versus pathology sizing (30% vs 19%, p<0.001), which may result in lower accuracy. Applying a 10-mm cut-off relevant to guidelines on risk stratification, 7.3% of all adenomas and 28.3% of those 8 to 12 mm in size had discordant endoscopy and pathology size categorization. Depending upon which guidelines are applied, 4.8% to 9.1% of individuals had differing risk stratification for surveillance recommendations, with the use of pathology sizing resulting in marginally fewer recommended surveillance colonoscopies.ConclusionsChoice of pathology or endoscopy approaches to determine adenoma size will potentially influence surveillance colonoscopy follow-up in 4.8% to 9.1% of individuals. Pathology sizing appears more accurate than endoscopy sizing, and preferential use of pathology size would result in a small, but clinically important, decreased burden on surveillance colonoscopy demand. Careful endoscopy sizing is required for adenomas removed piecemeal.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.