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1 "Risaburo Akasaka"
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Original Article
Colorectal neoplasia
Microvascular density under magnifying narrow-band imaging endoscopy in colorectal epithelial neoplasms
Takahiro Gonai, Keisuke Kawasaki, Shotaro Nakamura, Shunichi Yanai, Risaburo Akasaka, Kunihiko Sato, Yousuke Toya, Kensuke Asakura, Jun Urushikubo, Yasuko Fujita, Makoto Eizuka, Noriyuki Uesugi, Tamotsu Sugai, Takayuki Matsumoto
Intest Res 2020;18(1):107-114.   Published online November 4, 2019
DOI: https://doi.org/10.5217/ir.2019.00061
AbstractAbstract PDFPubReaderePub
Background/Aims
Magnifying endoscopic classification systems, such as the Japan narrow-band imaging (NBI) Expert Team (JNET) classification, have been widely used for predicting the histologic diagnosis and invasion depth of colorectal epithelial tumors. However, disagreement exists among observers regarding magnifying endoscopic diagnosis, because these classification systems are subjective. We herein investigated the utility of endoscopic microvascular density (eMVD) calculated from magnifying NBI endoscopic images in colorectal tumors.
Methods
We reviewed magnifying NBI endoscopic images from 169 colorectal epithelial tumors (97 adenomas, 72 carcinomas/high-grade dysplasias) resected endoscopically or surgically. The eMVD on magnifying NBI endoscopic images was evaluated using image-editing software, and relationships between eMVD and clinical, endoscopic, and pathological findings were retrospectively analyzed.
Results
The eMVD in carcinomas (0.152 ± 0.079) was significantly higher than that in adenomas (0.119 ± 0.059, P< 0.05). The best cutoff value for distinguishing carcinoma from adenoma was 0.133. Sensitivity, specificity, and accuracy were 56.9%, 67.0%, and 62.7%, respectively. In addition, JNET type 2B tumors showed significantly higher eMVD (0.162 ± 0.079) compared to type 2A tumors (0.111 ± 0.050, P< 0.05).
Conclusions
The eMVD as determined by magnifying NBI endoscopy is considered to be a possible objective indicator for differentiating colorectal carcinomas from adenomas.

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