Fujii-Lau Larissa L, Abu Dayyeh Barham K, Bruno Marco J, Chang Kenneth J, DeWitt John M, Fockens Paul, Forcione David, Napoleon Bertrand, Palazzo Laurent, Topazian Mark D, Wiersema Maurits J, Chak Amitabh, Clain Jonathan E, Faigel Douglas O, Gleeson Ferga C, Hawes Robert, Iyer Prasad G, Rajan Elizabeth, Stevens Tyler, Wallace Michael B, Wang Kenneth K, Levy Michael J
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA.
Department of Gastroenterology and Hepatology, Erasmus Medical Center, University Medical Center, Rotterdam, The Netherlands.
Gastrointest Endosc. 2015 May;81(5):1188-96.e1-7. doi: 10.1016/j.gie.2014.10.035. Epub 2015 Feb 7.
Detection of hepatic metastases during EUS is an important component of tumor staging.
To describe our experience with EUS-guided FNA (EUS-FNA) of solid hepatic masses and derive and validate criteria to help distinguish between benign and malignant hepatic masses.
Retrospective study, survey.
Single, tertiary-care referral center.
Medical records were reviewed for all patients undergoing EUS-FNA of solid hepatic masses over a 12-year period.
EUS-FNA of solid hepatic masses.
Masses were deemed benign or malignant according to predetermined criteria. EUS images from 200 patients were used to create derivation and validation cohorts of 100 cases each, matched by cytopathologic diagnosis. Ten expert endosonographers blindly rated 15 initial endosonographic features of each of the 100 images in the derivation cohort. These data were used to derive an EUS scoring system that was then validated by using the validation cohort by the expert endosonographer with the highest diagnostic accuracy.
A total of 332 patients underwent EUS-FNA of a hepatic mass. Interobserver agreement regarding the initial endosonographic features among the expert endosonographers was fair to moderate, with a mean diagnostic accuracy of 73% (standard deviation 5.6). A scoring system incorporating 7 EUS features was developed to distinguish benign from malignant hepatic masses by using the derivation cohort with an area under the receiver operating curve (AUC) of 0.92; when applied to the validation cohort, performance was similar (AUC 0.86). The combined positive predictive value of both cohorts was 88%.
Single center, retrospective, only one expert endosonographer deriving and validating the EUS criteria.
An EUS scoring system was developed that helps distinguish benign from malignant hepatic masses. Further study is required to determine the impact of these EUS criteria among endosonographers of all experience.
超声内镜检查（EUS）时检测肝转移是肿瘤分期的重要组成部分。
描述我们对实性肝肿块进行EUS引导下细针穿刺抽吸活检（EUS-FNA）的经验，并推导和验证有助于区分良性和恶性肝肿块的标准。
回顾性研究、调查。
单一的三级医疗转诊中心。
回顾了12年间所有接受实性肝肿块EUS-FNA的患者的病历。
对实性肝肿块进行EUS-FNA。
根据预定标准将肿块判定为良性或恶性。来自200例患者的EUS图像用于创建各有100例病例的推导队列和验证队列，并根据细胞病理学诊断进行匹配。10名专家超声内镜医师对推导队列中100张图像各自的15项初始超声内镜特征进行盲法评分。这些数据用于推导一个EUS评分系统，然后由诊断准确性最高的专家超声内镜医师使用验证队列对其进行验证。
共有332例患者接受了肝肿块的EUS-FNA。专家超声内镜医师之间关于初始超声内镜特征的观察者间一致性为中等，平均诊断准确性为73%（标准差5.6）。通过使用推导队列，开发了一个包含7项EUS特征的评分系统来区分良性和恶性肝肿块，其受试者工作特征曲线（ROC）下面积为0.92；应用于验证队列时，表现相似（ROC下面积0.86）。两个队列的联合阳性预测值为88%。
单中心、回顾性研究，仅由一名专家超声内镜医师推导和验证EUS标准。
开发了一种EUS评分系统，有助于区分良性和恶性肝肿块。需要进一步研究以确定这些EUS标准对所有经验水平的超声内镜医师的影响。
