ObjectiveTo investigate the success rate of cold snare polypectomy (CSP) for complete resection of 4–9 mm colorectal adenomatous polyps compared with that of hot snare polypectomy (HSP).DesignA prospective, multicentre, randomised controlled, parallel, non-inferiority trial conducted in 12 Japanese endoscopy units. Endoscopically diagnosed sessile adenomatous polyps, 4–9 mm in size, were randomly assigned to the CSP or HSP group. After complete removal of the polyp using the allocated technique, biopsy specimens from the resection margin after polypectomy were obtained. The primary endpoint was the complete resection rate, defined as no evidence of adenomatous tissue in the biopsied specimens, among all pathologically confirmed adenomatous polyps.ResultsA total of 796 eligible polyps were detected in 538 of 912 patients screened for eligibility between September 2015 and August 2016. The complete resection rate for CSP was 98.2% compared with 97.4% for HSP. The non-inferiority of CSP for complete resection compared with HSP was confirmed by the +0.8% (90% CI −1.0 to 2.7) complete resection rate (non-inferiority p<0.0001). Postoperative bleeding requiring endoscopic haemostasis occurred only in the HSP group (0.5%, 2 of 402 polyps).ConclusionsThe complete resection rate for CSP is not inferior to that for HSP. CSP can be one of the standard techniques for 4–9 mm colorectal polyps. (Study registration: UMIN000018328)

Background and Aim: Computer-aided diagnosis (CAD) is becoming a next-generation tool for the diagnosis of human disease. CAD for colon polyps has been suggested as a particularly useful tool for trainee colonoscopists, as the use of a CAD system avoids the complications associated with endoscopic resections. In addition to conventional CAD, a convolutional neural network (CNN) system utilizing artificial intelligence (AI) has been developing rapidly over the past 5 years. We attempted to generate a unique CNN-CAD system with an AI function that studied endoscopic images extracted from movies obtained with colonoscopes used in routine examinations. Here, we report our preliminary results of this novel CNN-CAD system for the diagnosis of colon polyps. Methods: A total of 1,200 images from cases of colonoscopy performed between January 2010 and December 2016 at Kindai University Hospital were used. These images were extracted from the video of actual endoscopic examinations. Additional video images from 10 cases of unlearned processes were retrospectively assessed in a pilot study. They were simply diagnosed as either an adenomatous or nonadenomatous polyp. Results: The number of images used by AI to learn to distinguish adenomatous from nonadenomatous was 1,200:600. These images were extracted from the videos of actual endoscopic examinations. The size of each image was adjusted to 256 × 256 pixels. A 10-hold cross-validation was carried out. The accuracy of the 10-hold cross-validation is 0.751, where the accuracy is the ratio of the number of correct answers over the number of all the answers produced by the CNN. The decisions by the CNN were correct in 7 of 10 cases. Conclusion: A CNN-CAD system using routine colonoscopy might be useful for the rapid diagnosis of colorectal polyp classification. Further prospective studies in an in vivo setting are required to confirm the effectiveness of a CNN-CAD system in routine colonoscopy.

In previous studies, we found that human IgG4-related autoimmune pancreatitis (AIP) and murine AIP are driven by activation of plasmacytoid dendritic cells (pDCs) producing IFN-α. In the present studies we examined additional roles of pDC-related mechanisms in AIP pathogenesis, particularly those responsible for induction of fibrosis. We found that in murine AIP (MRL/Mp mice treated with polyinosinic-polycytidylic acid) not only the pancreatic infiltration of immune cells but also the development of fibrosis were markedly reduced by the depletion of pDCs or blockade of type I IFN signaling; moreover, such treatment was accompanied by a marked reduction of pancreatic expression of IL-33. Conversely, polyinosinic-polycytidylic acid-induced inflamed pancreatic tissue in murine AIP exhibited increased expression of type I IFNs and IL-33 (and downstream IL-33 cytokines such as IL-13 and TGF-β1). pDCs stimulated by type I IFN were the source of the IL-33 because purified populations of these cells isolated from the inflamed pancreas produced a large amount of IL-33 upon activation by TLR9 ligands, and such production was abrogated by the neutralization of type I IFN. The role of IL-33 in murine AIP pathogenesis was surprisingly important because blockade of IL-33 signaling by anti-ST2 Ab attenuated both pancreatic inflammation and accompanying fibrosis. Finally, whereas patients with both conventional pancreatitis and IgG4-related AIP exhibited increased numbers of acinar cells expressing IL-33, only the latter also exhibited pDCs producing this cytokine. These data thus suggest that pDCs producing IFN-α and IL-33 play a pivotal role in the chronic fibro-inflammatory responses underlying murine AIP and human IgG4-related AIP.

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were compared with the final pathological diagnoses to determine the JNET classification's accuracy. The interobserver agreement was calculated, and the intraobserver agreement was assessed after 6 months. Results: The final pathological diagnoses identified 14 HPs/SSPs, 127 LGDs, 22 HGDs, 19 SM-s carcinomas, and 17 SM-d carcinomas. The respective sensitivities, specificities, positive predictive value, negative predictive value, and accuracies were as follows: Type 1, 85.7, 99.5, 92.3, 98.9, and 98.5%; Type 2A, 96.0, 81.9, 90.3, 92.1, and 90.9%; Type 2B, 75.6%, 90.5, 67.3, 93.4, and 87.4%; and Type 3, 29.4%, 100, 100, 93.8, and 94.0%. The interobserver agreement and the intraobserver agreement were moderate (κ value: 0.52) and excellent (κ value: 0.88), respectively. Lesions presenting as Type 2B during NBI comprised a range of colorectal tumors, including HGDs, SM-s, and SM-d. Conclusions: The JNET classification was useful for the diagnosis of HPs/SSPs, LGDs, and SM-d, but not SM-s lesions. For low-confidence cases, magnified chromoendoscopy is recommended to ensure correct diagnoses. In this classification system, types 1, 2A, 2B, and 3 correspond to hyperplastic polyps (HPs) including sessile serrated polyps (SSPs), low-grade dysplasia (LGD), high-grade dysplasia (HGD) to shallow submucosal invasive (SM-s) carcinomas, and deep submucosal invasive (SM-d) carcinomas, respectively. Methods: To validate this system, we performed a retrospective image evaluation study, in which 199 colorectal tumors previously assessed by NBI magnifying endoscopy were classified by 3 blinded experienced colonoscopists using the JNET system. The results