Titlebook: Endoscopic Management of Colorectal T1(SM) Carcinoma; Shinji Tanaka,Yusuke Saitoh Book 2020 Springer Nature Singapore Pte Ltd. 2020 Endosc

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Endoscopic Mucosal Resection (EMR)agnosis, appropriate strategy of treatment, handling of the resected specimen, and finally pathological diagnosis. Before performing EMR, the lesion should be evaluated carefully with magnified observation, and the resection should be carried out systematically without cutting into the area which is

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Precutting EMRter mucosal incision around the lesion. The indication of this resection method is the tumors up to 30–40 mm in size, which is difficult to resect by en bloc with snare EMR. In clinical situation, the choice of precutting EMR is dependent on the condition of the lesion. The safety and efficacy of pr

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Pathological Diagnosis of Submucosal Invasive Colorectal Carcinoma (pT1 Colorectal Cancer): Overviewoscopic resection of SICRC is critical. Here we describe histopathological and biological risk factors for lymph node metastasis (LNM) in patients with SICRC. Histopathological predictors of LNM of SICRC traditionally include submucosal invasion depth (>1000 μm), unfavorable histology (poorly differ

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Treatment Strategy After Endoscopic Resection for Colorectal T1(SM) Cancer: Present Status and Futurss of its size. In this chapter, we assessed the present status and future perspective of management for Tis/T1 colorectal cancer. Recently, according to the accumulation of many cases and detailed evaluation, after complete endoscopic en bloc resection for T1 colorectal cancer, if below all conditi

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Backdoor Sets for DLL Subsolvers,ome more important for determining whether detected T1 carcinoma can be cured by endoscopy alone (lesions with <1000 μm submucosal invasion) or should be treated by surgery (lesions with ≥1000 μm submucosal invasion). Useful conventional colonoscopic findings suggestive of polypoid-type T1b carcinom

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Sitzung 7: Aufmerksamkeit Teil 2 which makes it possible to perform high-level diagnosis that approximates pathological diagnosis. In pit pattern classification (Kudo’s classification), the proper rate of discrimination was reported to be approximately 96–98% between tumors and non-tumors and 70–90% between adenoma and cancer. In

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https://doi.org/10.1007/978-1-4612-2942-1d light observations. This mode enables us to observe the detailed surface pattern and vessel pattern for diagnosing JNET classifications for colorectal lesions. Although it is originally performed with NBI, the JNET classification can be used with BLI in similar to NBI; we previously demonstrated t