Chest · 2016
Spectrum Analysis of Endobronchial Ultrasound Radiofrequency of Lymph Nodes in Patients With Lung Cancer.
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Nakajima Takahiro, Shingyoji Masato, Anayama Takashi, Kimura Hideki, Yasufuku Kazuhiro, Yoshino Ichiro
Аннотация
OBJECTIVE: The aim of this study was to analyze the spectral features of the radiofrequency of lymph nodes during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and to determine its diagnostic value for detecting metastatic nodes in patients with lung cancer.
METHODS: Ultrasound spectrums of lymph nodes during EBUS-TBNA were retrospectively analyzed. A linear regression of frequency spectrum and the ultrasonic spectral parameters midband-fit, slope, and intercept were calculated. Mean values for these parameters within lymph nodes were computed. The cutoff values for each parameter for distinguishing metastatic vs benign lymph nodes were first determined within the training set; these cutoff values were then applied to the testing set for validation.
RESULTS: Overall, 362 lymph nodes (112 metastatic, 250 benign) were analyzed as the training set, and 284 lymph nodes (74 metastatic, 210 benign) were evaluated as the testing set. In the training set, all of the parameters showed a significant difference between metastatic and benign lymph nodes (P < .001). The metastatic nodes tended to show low midband-fit, high slope, and low intercept. When midband-fit and intercept were combined, the diagnostic accuracy was maximized in the training set. In the testing set, the combination of intercept and slope produced the highest diagnostic accuracy, with the following outcomes: sensitivity, 79.7%; specificity, 84.3%; diagnostic accuracy, 83.1%; positive predictive value, 64.1%; and negative predictive value, 92.2%.
CONCLUSIONS: Metastatic lymph nodes possess unique ultrasonic spectrum features, and spectrum analysis can be used as a novel diagnostic tool for differentiating between benign and malignant nodes in patients with lung cancer.
METHODS: Ultrasound spectrums of lymph nodes during EBUS-TBNA were retrospectively analyzed. A linear regression of frequency spectrum and the ultrasonic spectral parameters midband-fit, slope, and intercept were calculated. Mean values for these parameters within lymph nodes were computed. The cutoff values for each parameter for distinguishing metastatic vs benign lymph nodes were first determined within the training set; these cutoff values were then applied to the testing set for validation.
RESULTS: Overall, 362 lymph nodes (112 metastatic, 250 benign) were analyzed as the training set, and 284 lymph nodes (74 metastatic, 210 benign) were evaluated as the testing set. In the training set, all of the parameters showed a significant difference between metastatic and benign lymph nodes (P < .001). The metastatic nodes tended to show low midband-fit, high slope, and low intercept. When midband-fit and intercept were combined, the diagnostic accuracy was maximized in the training set. In the testing set, the combination of intercept and slope produced the highest diagnostic accuracy, with the following outcomes: sensitivity, 79.7%; specificity, 84.3%; diagnostic accuracy, 83.1%; positive predictive value, 64.1%; and negative predictive value, 92.2%.
CONCLUSIONS: Metastatic lymph nodes possess unique ultrasonic spectrum features, and spectrum analysis can be used as a novel diagnostic tool for differentiating between benign and malignant nodes in patients with lung cancer.