定量对比增强谐波超声内镜在鉴别诊断胰腺局灶性肿块中的应用（附有视频）。

Quantitative contrast-enhanced harmonic EUS in differential diagnosis of focal pancreatic masses (with videos).

机构信息

Research Center of Gastroenterology and Hepatology of Craiova, University of Medicine and Pharmacy, Craiova, Romania; Endoscopy Department, Copenhagen University Hospital, Herlev, Denmark.

Endoscopy Department, Copenhagen University Hospital, Herlev, Denmark.

出版信息

Gastrointest Endosc. 2015 Jul;82(1):59-69. doi: 10.1016/j.gie.2014.11.040. Epub 2015 Mar 16.

DOI:10.1016/j.gie.2014.11.040

PMID:25792386

Abstract

BACKGROUND

The role of EUS with contrast agents can be expanded through the use of time-intensity curve (TIC) analysis and computer-aided interpretation.

OBJECTIVE

To validate the use of parameters derived from TIC analysis in an artificial neural network (ANN) classification model designed to diagnose pancreatic carcinoma (PC) and chronic pancreatitis (CP).

SETTING

Prospective, multicenter, observational trial-endoscopy units from Romania, Denmark, Germany, and Spain.

PATIENTS

A total of 167 consecutive patients with PC or CP.

INTERVENTIONS

Contrast-enhanced harmonic EUS (CEH-EUS) and EUS-guided FNA (EUS-FNA), TIC analysis, and ANN processing.

MAIN OUTCOME MEASUREMENTS

Sensitivity, specificity, positive and negative predictive values (PPV, NPV) for EUS-FNA, CEH-EUS, and the ANN.

RESULTS

After excluding all of the recordings that did not meet the technical and procedural criteria, 112 cases of PC and 55 cases of CP were included. EUS-FNA was performed in 129 patients, and the diagnosis was confirmed by surgery (n = 15) or follow-up (n = 23) in the remaining cases. Its sensitivity and specificity were 84.82% and 100%, respectively, whereas the PPV and NPV were 100% and 76.63%, respectively. The sensitivity of real-time quantitative assessment of CEH-EUS was 87.5%, specificity 92.72%, PPV 96.07%, and NPV 78.46%. Peak enhancement, wash-in area under the curve, wash-in rate, and the wash-in perfusion index were significantly different between the groups. No significant differences were found between rise time, mean transit time, and time to peak. For the ANN, sensitivity was 94.64%, specificity 94.44%, PPV 97.24%, and NPV 89.47%.

LIMITATIONS

Only PC and CP lesions were included.

CONCLUSION

Parameters obtained through TIC analysis can differentiate between PC and CP cases and can be used in an automated computer-aided diagnostic system with good diagnostic results. (

CLINICAL TRIAL REGISTRATION NUMBER

NCT01315548.).

摘要

背景

通过使用时间-强度曲线（TIC）分析和计算机辅助解释，EUS 可以扩展其作用。

目的

验证在设计用于诊断胰腺癌（PC）和慢性胰腺炎（CP）的人工神经网络（ANN）分类模型中使用源自 TIC 分析的参数的有效性。

设置

前瞻性、多中心、观察性试验——来自罗马尼亚、丹麦、德国和西班牙的内镜单位。

患者

共纳入 167 例连续的 PC 或 CP 患者。

干预

对比增强谐波 EUS（CEH-EUS）和 EUS 引导下细针抽吸活检（EUS-FNA）、TIC 分析和 ANN 处理。

主要观察测量指标

EUS-FNA、CEH-EUS 和 ANN 的敏感性、特异性、阳性和阴性预测值（PPV、NPV）。

结果

排除所有不符合技术和程序标准的记录后，纳入 112 例 PC 和 55 例 CP。对 129 例患者进行了 EUS-FNA 检查，在其余病例中，通过手术（n=15）或随访（n=23）确定诊断。EUS-FNA 的敏感性和特异性分别为 84.82%和 100%，PPV 和 NPV 分别为 100%和 76.63%。实时定量 CEH-EUS 评估的敏感性为 87.5%，特异性为 92.72%，PPV 为 96.07%，NPV 为 78.46%。两组之间增强峰值、曲线下的早期强化面积、早期强化率和早期强化灌注指数差异有统计学意义。上升时间、平均通过时间和达峰时间无显著差异。对于 ANN，敏感性为 94.64%，特异性为 94.44%，PPV 为 97.24%，NPV 为 89.47%。