Alici Ibrahim Onur, Yılmaz Demirci Nilgün, Yılmaz Aydın, Karakaya Jale, Özaydın Esra
Lung Transplantation Center, Turkiye Yuksek Ihtisas Education and Research Hospital, Ankara, Turkey.
Department of Pulmonary Diseases, Gazi University, Ankara, Turkey.
Clin Respir J. 2016 Sep;10(5):606-13. doi: 10.1111/crj.12267. Epub 2015 Mar 3.
There are several papers on the sonographic features of mediastinal lymph nodes affected by several diseases, but none gives the importance and clinical utility of the features.
In order to find out which lymph node should be sampled in a particular nodal station during endobronchial ultrasound, we investigated the diagnostic performances of certain sonographic features and proposed an algorithmic approach.
We retrospectively analyzed 1051 lymph nodes and randomly assigned them into a preliminary experimental and a secondary study group. The diagnostic performances of the sonographic features (gray scale, echogeneity, shape, size, margin, presence of necrosis, presence of calcification and absence of central hilar structure) were calculated, and an algorithm for lymph node sampling was obtained with decision tree analysis in the experimental group. Later, a modified algorithm was applied to the patients in the study group to give the accuracy.
The demographic characteristics of the patients were not statistically significant between the primary and the secondary groups. All of the features were discriminative between malignant and benign diseases. The modified algorithm sensitivity, specificity, and positive and negative predictive values and diagnostic accuracy for detecting metastatic lymph nodes were 100%, 51.2%, 50.6%, 100% and 67.5%, respectively.
In this retrospective analysis, the standardized sonographic classification system and the proposed algorithm performed well in choosing the node that should be sampled in a particular station during endobronchial ultrasound.
有几篇关于多种疾病所致纵隔淋巴结超声特征的论文，但均未提及这些特征的重要性及临床应用价值。
为了明确在支气管内超声检查时特定淋巴结区域应穿刺取样的淋巴结，我们研究了某些超声特征的诊断效能并提出了一种算法方法。
我们回顾性分析了1051个淋巴结，并将它们随机分为初步试验组和二次研究组。计算超声特征（灰度、回声性、形状、大小、边界、有无坏死、有无钙化及有无中央肺门结构）的诊断效能，并在试验组中通过决策树分析获得淋巴结取样算法。随后，将改良算法应用于研究组患者以得出准确性。
主要组和次要组患者的人口统计学特征无统计学差异。所有特征在恶性和良性疾病之间均具有鉴别性。改良算法检测转移性淋巴结的敏感性、特异性、阳性和阴性预测值及诊断准确性分别为100%、51.2%、50.6%、100%和67.5%。
在这项回顾性分析中，标准化超声分类系统及所提出的算法在支气管内超声检查时选择特定区域应穿刺取样的淋巴结方面表现良好。
