中国普外基础与临床杂志

中国普外基础与临床杂志

CT 特征鉴别非富血供胰腺神经内分泌肿瘤与胰腺导管腺癌的初步研究

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目的 探索能用于鉴别非富血供胰腺神经内分泌肿瘤(pNEN)与胰腺导管腺癌(PDAC)的 CT 特征。 方法 回顾性纳入四川大学华西医院 2010 年 5 月至 2017 年 5 月期间经过病理确诊为非富血供 pNEN 和 PDAC 的患者,分析二者的 CT 特征,通过多元逻辑回归筛选 CT 特征并计算其诊断效能。 结果 40 例非富血供 pNEN(无功能性 33 例,功能性 7 例)及 80 例 PDAC 患者纳入本研究。非富血供 pNEN 与 PDAC 间差异有统计学意义的特征包括肿瘤位置、肿瘤长径、肿瘤边界、肿瘤实质均匀、肿瘤内钙化及肿瘤内血管影(P<0.05)。将各项有统计学意义的特征经过多元逻辑回归分析后提示肿瘤边界 [OR 为 14.63,95% CI 为(2.82,75.99)]、肿瘤内钙化[OR 为 4.00,95% CI 为(1.03,15.59)] 及肿瘤位置 [OR为3.09,95% CI为(1.19,7.99)] 能够独立鉴别出非富血供 pNEN。再根据有统计学意义的特征最终得出非富血供 pNEN 与 PDAC 鉴别诊断的多元逻辑回归模型,其诊断敏感度为 70.00%,95%CI 为(53.5,83.4);特异度为 83.54%,95%CI 为(73.5,90.9);受试者工作特征曲线下面积为 0.824,95% CI 为(0.743,0.887)。 结论 CT 特征多元逻辑回归模型可应用于非富血供 pNEN 与 PDAC 鉴别诊断,其中肿瘤边界及肿瘤内钙化特征在非富血供 pNEN 与 PDAC 鉴别诊断中有一定的应用价值。

Objective To explore CT features that can be used to identify nonhypervascular pancreatic neuroendocrine neoplasm (pNEN) and pancreatic ductal adenocarcinoma (PDAC). Methods The patients with pathologically confirmed the pNEN and PDAC were retrospectively included from May 2010 to May 2017. The CT features were analyzed. The CT features were extracted by the multivariate logistic regression, and their diagnostic performances were calculated. Results Forty patients with the nonhypervascular pNEN (33 unfunctional, 7 functional) and 80 patients with the PDAC were included in this study. The features of significant differences between the nonhypervascular pNEN and the PDAC included: the location, long diameter, margin, uniform lesions, calcification, and vascular shadows of the lesion (P<0.05). The margin [OR=14.63, 95% CI (2.82, 75.99)], calcification [OR=4.00, 95% CI (1.03, 15.59)], and location [OR=3.09, 95% CI(1.19, 7.99)] of the lesion could independently identify the nonhypervascular pNEN. The multivariate logistic regression model of the differential diagnosis of the nonhypervascular pNEN and PDAC was obtained through the CT features of significant differences. The diagnostic sensitivity was 70.00%, 95% CI (53.5,83.4); specificity was 83.54%, 95% CI (73.5, 90.9); and area under the receiver operating curve was 0.824, 95% CI (0.743, 0.887). Conclusions Multivariate logistic regression model of CT features is helpful for differential diagnosis of nonhypervascular pNEN and PDAC. Features of margin and calcification of lesion are more valuable in differential diagnosis of nonhypervascular pNEN and PDAC.

关键词: 胰腺神经内分泌肿瘤; 胰腺导管腺癌; CT

Key words: pancreatic neuroendocrine neoplasm; pancreatic ductal adenocarcinoma; computed tomography

引用本文: 黄子星, 于浩鹏, 李谋, 汪翊, 宋彬. CT 特征鉴别非富血供胰腺神经内分泌肿瘤与胰腺导管腺癌的初步研究. 中国普外基础与临床杂志, 2018, 25(11): 1375-1379. doi: 10.7507/1007-9424.201809016 复制

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1. Hallet J, Law CH, Cukier M, et al. Exploring the rising incidence of neuroendocrine tumors: a population-based analysis of epidemiology, metastatic presentation, and outcomes. Cancer, 2015, 121(4): 589-597.
2. 中国临床肿瘤学会神经内分泌肿瘤专家委员会. 中国胃肠胰神经内分泌肿瘤专家共识 (2016 年版). 临床肿瘤学杂志, 2016, 21(10): 927-946.
3. 张雨晴, 马莉, 贺宇彤, 等. 2001~2010 年中国胰腺神经内分泌肿瘤的临床流行病学特征分析. 中国肿瘤, 2016, 25(5): 329-333.
4. 张雨晴, 范金虎, 乔友林, 等. 中国胃肠胰腺神经内分泌肿瘤的十年回顾性临床流行病学研究. 公共卫生, 2016.
5. 王齐艳, 黄子星, 吴明蓬, 等. 胰腺神经内分泌肿瘤的多层螺旋 CT 表现与其病理分级的关系. 中国普外基础与临床杂志, 2016, 23(2): 243-247.
6. 张笑, 王齐艳, 黄子星, 等. 基于文献计量学的胰腺神经内分泌肿瘤的影像学研究热点分析. 中国普外基础与临床杂志, 2015, 22(8): 1007-1013.
7. 刘曦娇, 王威亚, 黄子星, 等. 胰腺神经内分泌癌的影像学表现. 中国普外基础与临床杂志, 2012, 19(10): 1126-1129.
8. Jeon SK, Lee JM, Joo I, et al. Nonhypervascular pancreatic neuroendocrine tumors: differential diagnosis from pancreatic ductal adenocarcinomas at MR imaging-retrospective cross-sectional study. Radiology, 2017, 284(1): 77-87.
9. Ichikawa T, Peterson MS, Federle MP, et al. Islet cell tumor of the pancreas: biphasic CT versus MR imaging in tumor detection. Radiology, 2000, 216(1): 163-171.
10. Stafford-Johnson DB, Francis IR, Eckhauser FE, et al. Dual-phase helical CT of nonfunctioning islet cell tumors. J Comput Assist Tomogr, 1998, 22(2): 335-339.
11. De Robertis R, Tinazzi Martini P, Cingarlini S, et al. Digital subtraction of magnetic resonance images improves detection and characterization of pancreatic neuroendocrine neoplasms. J Comput Assist Tomogr, 2017, 41(4): 614-618.
12. Park HS, Kim SY, Hong SM, et al. Hypervascular solid-appearing serous cystic neoplasms of the pancreas: Differential diagnosis with neuroendocrine tumours. Eur Radiol, 2016, 26(5): 1348-1358.
13. Al-Hawary MM, Francis IR, Chari ST, et al. Pancreatic ductal adenocarcinoma radiology reporting template: consensus statement of the Society of Abdominal Radiology and the American Pancreatic Association. Radiology, 2014, 270(1): 248-260.
14. 冯婷婷, 凌孙彬, 刘碧霞, 等. 非功能型胰腺神经内分泌肿瘤手术预后分析— 一项基于 SEER 数据库的回顾性研究. 中国肿瘤, 2017, 26(11): 910-914.
15. Ito T, Hijioka S, Masui T, et al. Advances in the diagnosis and treatment of pancreatic neuroendocrine neoplasms in Japan. J Gastroenterol, 2017, 52(1): 9-18.
16. Karakaxas D, Gazouli M, Liakakos T, et al. Pancreatic neuroendocrine tumors: current opinions on a rare, but potentially curable neoplasm. Eur J Gastroenterol Hepatol, 2014, 26(8): 826-835.
17. Masciocchi M. Pancreatic imaging. Endocrinol Metab Clin North Am, 2017, 46(3): 761-781.
18. Baur AD, Pavel M, Prasad V, et al. Diagnostic imaging of pancreatic neuroendocrine neoplasms (pNEN): tumor detection, staging, prognosis, and response to treatment. Acta Radiol, 2016, 57(3): 260-270.
19. Ohmoto A, Rokutan H, Yachida S. Pancreatic neuroendocrine neoplasms: basic biology, current treatment strategies and prospects for the future. Int J Mol Sci, 2017, 18(1): pii: E143.
20. Jin K, Xu J, Chen J, et al. Surgical management for non-functional pancreatic neuroendocrine neoplasms with synchronous liver metastasis: A consensus from the Chinese Study Group for Neuroendocrine Tumors (CSNET). Int J Oncol, 2016, 49(5): 1991-2000.
21. Tamburrino D, Partelli S, Renzi C, et al. Systematic review and meta-analysis on laparoscopic pancreatic resections for neuroendocrine neoplasms (PNENs). Expert Rev Gastroenterol Hepatol, 2017, 11(1): 65-73.
22. Partelli S, Cirocchi R, Crippa S, et al. Systematic review of active surveillance versus surgical management of asymptomatic small non-functioning pancreatic neuroendocrine neoplasms. Br J Surg, 2017, 104(1): 34-41.
23. 张永嫦, 于浩鹏, 李谋, 等. CT 图像纹理分析鉴别乏血供胰腺神经内分泌肿瘤与胰腺导管腺癌. 中国普外基础与临床杂志, 2018, 25(6): 748-753.
24. Berenguer R, Pastor-Juan MDR, Canales-Vázquez J, et al. Radiomics of CT features may be nonreproducible and redundant: influence of CT acquisition parameters. Radiology, 2018, 288(2): 407-415.
25. 罗国培, 金凯舟, 程合, 等. 改良胰腺神经内分泌肿瘤分期的临床解读. 中国癌症杂志, 2017, 27(5): 321-325.
26. Lesniak RJ, Hohenwalter MD, Taylor AJ. Spectrum of causes of pancreatic calcifications. AJR Am J Roentgenol, 2002, 178(1): 79-86.
27. Verde F, Fishman EK. Calcified pancreatic and peripancreatic neoplasms: spectrum of pathologies. Abdom Radiol (NY), 2017, 42(11): 2686-2697.
28. Kuo JH, Lee JA, Chabot JA. Nonfunctional pancreatic neuroendocrine tumors. Surg Clin North Am, 2014, 94(3): 689-708.
29. Manuel-Vazquez A, Ramia JM, Latorre-Fragua R, et al. Pancreatic neuroendocrine tumors and intraductal papillary mucinous neoplasm of the pancreas: a systematic review. Pancreas, 2018, 47(5): 551-555.