臨牀消化器内科 Vol.32 No.13(9)


特集名 消化器癌の拡大内視鏡診断
題名 大腸の腫瘍・非腫瘍の拡大観察診断
発刊年月 2017年 12月
著者 新村 健介 国立がん研究センター東病院消化管内視鏡科
著者 伊藤 錬磨 国立がん研究センター東病院消化管内視鏡科
著者 池松 弘朗 国立がん研究センター東病院消化管内視鏡科
【 要旨 】 大腸病変を治療するうえで,まず腫瘍性病変か非腫瘍性病変なのかを鑑別しなければならない.鑑別するうえで有用とされているのがNBIやBLIに代表される画像強調内視鏡である.多種類存在するNBI分類の有用性については数多く報告されていたが,2014年に大腸拡大NBI統一分類であるJNET分類が提唱された.JNET分類は病変の血管構造や表面構造から非腫瘍・腫瘍・癌を診断していくがやはり診断には限界があるため,pit pattern診断を組み合わせて診断を向上していく必要がある.
Theme Magnifying Endoscopic Diagnosis of Gastro‒intestinal Carcinomas
Title Diagnosis of Colorectal Lesions
Author Kensuke Shinmura Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East
Author Renma Ito Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East
Author Hiroaki Ikematsu Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East
[ Summary ] During colonoscopy, colorectal lesions must be distinguished as either neoplastic or non‒neoplastic. Image‒enhanced endoscopy techniques such as NBI (Narrow Band Imaging) and BLI (Blue LASER Imaging) are useful for differential diagnoses. We previously reported an improved confidence in the diagnosis of diminutive neoplastic colorectal polyps with magnifying NBI. Moreover, magnifying NBI has been reported to provide high accuracy for distinguishing between adenoma and cancer. Many reports have also shown the usefulness of NBI with the Sano, Showa, Jikei, and Hiroshima classifications. Although these classifications are now widely used in daily practice, some confusion arises among endoscopists because of the different terminologies related to endoscopic findings. To standardize these diagnostic strategies, the Japan NBI Expert Team (JNET) classification, which is a unified classification of NBI with magnification colonoscopy, was proposed in 2014. The JNET classification distinguishes among non-neoplastic lesions, neoplastic lesions, and cancer according to both the vessel and surface patterns of the lesions. However, as there is a limit to the diagnosis, it is necessary to improve the diagnosis by combining this classification with pit pattern diagnosis.
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