Diagnostic value of endobronchial ultrasound elastography for the differentiation of benign and malignant intrathoracic lymph nodes

Respirology ◽  
2017 ◽  
Vol 22 (5) ◽  
pp. 972-977 ◽  
Author(s):  
Potjanee Korrungruang ◽  
Viboon Boonsarngsuk
2020 ◽  
pp. 155335062097802
Author(s):  
Surong Fang ◽  
Ligong Chang ◽  
Feifei Chen ◽  
Xiaoming Mao ◽  
Wei Gu

Objective. This study was to combine endobronchial ultrasound elastography (UE) with computed tomography (CT) to identify benign and malignant thoracic lymph nodes (LNs) more objectively and accurately. Methods. A total of 42 patients with intrathoracic lymphadenopathy required for endobronchial ultrasound with real-time guided transbronchial needle aspiration (EBUS-TBNA) examination were enrolled. All patients were examined by enhanced chest CT, B-mode ultrasound, and endobronchial ultrasound (EBUS)-guided elastography before EBUS-TBNA. Each lymph node was assessed by describing the characteristics of CT image (short diameter, texture, shape, boundary, and mean CT value), B-mode ultrasound (short diameter, echo characteristic, shape, and boundary), and elastography (image type, grading score, strain rate, and blue area ratio). The pathological results were used as the gold standard. The characteristics were compared alone and in combination between benign and malignant LNs. Results. The blue area ratio of elastography combined with CT had better diagnostic value in differentiating benign and malignant LNs than elastography alone, with the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) being 92%, 96%, 80%, 94%, and 86% vs 81%, 77%, 93%, 97%, and 56%, respectively. Elastography combined with B-mode ultrasound and CT characteristics showed the highest diagnostic value. Accuracy, sensitivity, specificity, PPV, and NPV were all 100%. Conclusions. Endobronchial UE combined with CT and B-mode ultrasound imaging shows a greater diagnostic value in differentiating benign and malignant intrathoracic LNs than either imaging alone.


Respiration ◽  
2021 ◽  
pp. 1-11
Author(s):  
Xinxin Zhi ◽  
Junxiang Chen ◽  
Lei Wang ◽  
Fangfang Xie ◽  
Xiaoxuan Zheng ◽  
...  

<b><i>Background:</i></b> Endobronchial ultrasound (EBUS) imaging is valuable in diagnosing intrathoracic lymph nodes (LNs), but there has been little analysis of multimodal imaging. This study aimed to comprehensively compare the diagnostic performance of single and multimodal combinations of EBUS imaging in differentiating benign and malignant intrathoracic LNs. <b><i>Methods:</i></b> Subjects from July 2018 to June 2019 were consecutively enrolled in the model group and July 2019 to August 2019 in the validation group. Sonographic features of three EBUS modes were analysed in the model group for the identification of malignant LNs from benign LNs. The validation group was used to verify the diagnostic efficiency of single and multimodal diagnostic methods built in the model group. <b><i>Results:</i></b> 373 LNs (215 malignant and 158 benign) from 335 subjects and 138 LNs (79 malignant and 59 benign) from 116 subjects were analysed in the model and validation groups, respectively. For single mode, elastography had the best diagnostic value, followed by grayscale and Doppler. The corresponding accuracies in the validation group were 83.3%, 76.8%, and 71.0%, respectively. Grayscale with elastography had the best diagnostic efficiency of multimodal methods. When at least two of the three features (absence of central hilar structure, heterogeneity, and qualitative elastography score 4–5) were positive, the sensitivity, specificity, and accuracy in the validation group were 88.6%, 78.0%, and 84.1%, respectively. <b><i>Conclusions:</i></b> In both model and validation groups, elastography performed the best in single EBUS modes, as well as grayscale combined with elastography in multimodal imaging. Elastography alone or combined with grayscale are feasible to help predict intrathoracic benign and malignant LNs.


2014 ◽  
Vol 44 (10) ◽  
pp. 956-962 ◽  
Author(s):  
Takehiro Izumo ◽  
Shinji Sasada ◽  
Christine Chavez ◽  
Yuji Matsumoto ◽  
Takaaki Tsuchida

2020 ◽  
Vol 154 (2) ◽  
pp. 45-51
Author(s):  
María Hernández Roca ◽  
Javier Pérez Pallarés ◽  
María del Mar Valdivia Salas ◽  
José García Solano ◽  
David Prieto Merino ◽  
...  

Author(s):  
Takehiro Izumo ◽  
Yuji Matsumoto ◽  
Yoshihisa Hiraishi ◽  
Manabu Hayama ◽  
Christine Chavez ◽  
...  

2018 ◽  
Vol 106 (4) ◽  
pp. 1251-1257 ◽  
Author(s):  
Ye-Feng Chen ◽  
Xiao-Wei Mao ◽  
Yu-Jun Zhang ◽  
Chun-Yi Zhang ◽  
Yue-Fang Yu ◽  
...  

2019 ◽  
Vol 118 (1) ◽  
pp. 436-443 ◽  
Author(s):  
Ching-Kai Lin ◽  
Kai-Lun Yu ◽  
Lih-Yu Chang ◽  
Hung-Jen Fan ◽  
Yueh-Feng Wen ◽  
...  

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