Validity of the usefulness of microvascular architecture and microsurface structure using magnifying endoscopy with narrow-band imaging in the colorectal neoplasm
Autor: | Hisabe, Takashi, Yao, Kenshi, Beppu, Takahiro, Ninomiya, Kazeo, Nagahama, Takashi, Takaki, Yasuhiro, Hirai, Fumihito, Matsui, Toshiyuki, Tanabe, Hiroshi, Iwashita, Akinori |
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Jazyk: | angličtina |
Rok vydání: | 2013 |
Předmět: | |
Zdroj: | Annals of Gastroenterology : Quarterly Publication of the Hellenic Society of Gastroenterology |
ISSN: | 1792-7463 1108-7471 |
Popis: | Background Magnifying endoscopy (ME) with narrow-band imaging (NBI) has been described as useful in diagnosing colorectal neoplasms. However, there is no standardized simple classification system, and its usefulness in comparison with pit pattern diagnosis by magnifying chromoendoscopy (MC) is unclear. The aim of this study was to investigate the usefulness of evaluations of microvascular architecture (MV) and microsurface structure (MS) by ME with NBI in the diagnosis of colorectal neoplasms. Methods A total of 360 colorectal neoplasms were analyzed by retrospective analysis of prospectively collected data. The vessel plus surface (VS) classification system was applied for ME with NBI diagnosis. The main outcome measurement was comparison of the diagnostic performance of ME with NBI and MC. Results The sensitivity of ME with NBI and MC for the diagnosis of adenomas was 91.9% and 95.7%, respectively, and their specificity was 79.2% and 79.9%, respectively. The sensitivity of ME with NBI and MC for the diagnosis of cancer was 70.5% and 79.9%, respectively, and the specificity was 95.3% and 95.7%, respectively. The sensitivity of ME with NBI and MC for the diagnosis of cancer with deep submucosal invasion was 50.0% and 88.0%, respectively (P < 0.0001), and their specificity was 100% and 82.8%, respectively (P < 0.0001). Conclusions The specificity of evaluation of MV and MS by ME with NBI for the diagnosis of cancer with deep submucosal invasion was much higher than that of pit pattern analysis by MC. |
Databáze: | OpenAIRE |
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