Dynamic computed tomography is useful for prediction of pathological grade in pancreatic neuroendocrine neoplasm. Issue 4 (April 2017)

• Record Type: Journal Article
• Authors: Horiguchi, Shigeru; Kato, Hironari; Shiraha, Hidenori; Tsutsumi, Koichiro; Yamamoto, Naoki; Matsumoto, Kazuyuki; Tomoda, Takeshi; Uchida, Daisuke; Akimoto, Yutaka; Mizukawa, Syou; Tanaka, Takehiro; Ichimura, Koichi; Takaki, Akinobu; Yagi, Takahito; Okada, Hiroyuki
• Is Part Of: Journal of gastroenterology and hepatology. Volume 32:Issue 4(2017)
• Page Start: 925
• Page End: 931
• Publication Date: 2017-04
• Subjects: dynamic CT -- microvessel density -- pancreatic neuroendocrine neoplasm -- pathological grade -- WHO2010; Gastroenterology -- Periodicals; Digestive organs -- Diseases -- Periodicals; Liver -- Diseases -- Periodicals; Gastroenterology -- Periodicals; Liver Diseases -- Periodicals; 616.33
• DOI: 10.1111/jgh.13594
• Languages: English
• ISSNs: 0815-9319

Abstract

Abstract: Background and Aim: Pathological grading is important in defining the therapeutic strategy in pancreatic neuroendocrine neoplasm (PNEN) but is difficult for unresectable cases. Endoscopic ultrasound (EUS)‐guided fine needle aspiration (FNA) is useful in the diagnosis of PNEN, but its usefulness for pathological grading is not well established. No studies have examined the diagnostic ability of dynamic computed tomography (CT) for pathological grading of PNEN. We investigated the usefulness of EUS–FNA and dynamic CT in the diagnosis and pathological grading of PNEN. Methods: In this retrospective study, 39 PNEN patients finally diagnosed via EUS–FNA and/or surgical resection underwent dynamic CT. Pathological samples were diagnosed based on WHO2010; staging was based on the European Neuroendocrine Tumor Society classification. The proportion of the quantification value in the tumor to the pancreatic parenchyma in arterial phase was defined as the CT ratio. Immunohistochemical staining with CD31 was performed to evaluate microvessel density (MVD). We evaluated the relationship between pathological grade, CT ratio, and MVD. Results: By using EUS–FNA, 35 of 39 (90%) cases were diagnosed as PNEN. As for pathological grade, 15 of 35 (43%) cases could be identified correctly. CT ratio could predict pathological Grade 3 disease. The sensitivity, specificity, and diagnostic accuracy were 100%, 94%, and 95%. MVD was significantly correlated with CT ratio ( r = 0.83, P < 0.0001) and pathological grade ( P = 0.0074). Conclusions: Computed tomography ratio has a relationship with pathological grade in PNEN, which would help decide therapeutic strategy in unresectable cases and cases in which pathological grading is difficult.