Endocytoscopy Is Useful for the Diagnosis of Superficial Nonampullary Duodenal Epithelial Tumors

Takashi Hirose, Naomi Kakushima, Kazuhiro Furukawa, Satoshi Furune, Eri Ishikawa, Tsunaki Sawada, Keiko Maeda, Takeshi Yamamura, Takuya Ishikawa, Eizaburo Ohno, Masanao Nakamura, Kazuki Nishida, Takio Yokoi, Hiroki Kawashima, Mitsuhiro Fujishiro

研究成果: ジャーナルへの寄稿学術論文査読

10 被引用数 (Scopus)


Introduction: Endoscopic criteria for the diagnosis of superficial nonampullary duodenal epithelial tumors (SNADETs) are lacking. The aim of this study was to explore the usefulness of endocytoscopy (ECS) in the duodenum. Methods: A total of 77 ECS images stained by methylene blue and 58 images with double staining of methylene blue and crystal violet were obtained from 20 patients. Images were classified into 3 grades based on nuclear and villi atypia: EC A, B, and C. Diagnostic performance of ECS classification to predict histology and interobserver agreement was evaluated. The performance was compared between staining methods and ×520 or ×936 zoom. Results: With methylene blue staining, high rates of accuracy, sensitivity, specificity, and positive predictive value (PPV) over 90% were achieved for tumor and nontumor diagnosis as assessed by EC A versus EC B. High rates of accuracy, sensitivity, PPV, and negative predictive value over 90% were achieved for the differentiation between the diagnosis of the Vienna category 3 and 4/5 as assessed by EC B versus C. The accuracy rate of interpreting ECS images with ×936 zoom among 10 endoscopists was 82%, and the interobserver agreement rate was 0.803 (Kendall's coefficient of concordance). In the ×936 zoom group, methylene blue staining was significantly associated with higher accuracy rate (odds ratio 1.76 [1.06-2.92], p value 0.0297). No benefit was observed by double staining. Conclusions: ECS diagnosis with methylene blue provides a high accuracy rate and good interobserver agreement to predict histology of SNADETs.

出版ステータス出版済み - 01-11-2021

All Science Journal Classification (ASJC) codes

  • 消化器病学


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