BACKGROUND: Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive procedure with a high yield for lymph node staging of lung cancer. The aim of this study was to assess the utility of sonographic features of lymph nodes during EBUS-TBNA for the prediction of metastasis in patients with lung cancer and to establish a standard endobronchial ultrasound (EBUS) image classification system. METHODS: Digital images of lymph nodes obtained during EBUS-TBNA in patients with lung cancer were categorized according to the following characteristics: (1) size (short axis) less or more than 1 cm, (2) shape (oval or round), (3) margin (indistinct or distinct), (4) echogenicity (homogeneous or heterogeneous), (5) presence or absence of central hilar structure, and (6) presence or absence of coagulation necrosis sign. The sonographic findings were compared with the final pathologic results. RESULTS: A total of 1,061 lymph nodes were retrospectively evaluated in 487 patients. The accuracy of predicting metastatic property for each category was as high as 63.8% to 86.0%. A multivariate analysis revealed that round shape, distinct margin, heterogeneous echogenicity, and presence of coagulation necrosis sign were independent predictive factors for metastasis. Two hundred eighty-five of the 664 lymph nodes (42.9%) having at least one metastatic feature of the four categories were pathologically proven metastatic, and 96.0% of lymph nodes (381/397) were proven not metastatic when all four categories were determined as benign. CONCLUSIONS: Sonographic features of lymph nodes based on the new EBUS imaging classification may be helpful in the prediction of metastatic lymph nodes during EBUS-TBNA.
BACKGROUND: Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive procedure with a high yield for lymph node staging of lung cancer. The aim of this study was to assess the utility of sonographic features of lymph nodes during EBUS-TBNA for the prediction of metastasis in patients with lung cancer and to establish a standard endobronchial ultrasound (EBUS) image classification system. METHODS: Digital images of lymph nodes obtained during EBUS-TBNA in patients with lung cancer were categorized according to the following characteristics: (1) size (short axis) less or more than 1 cm, (2) shape (oval or round), (3) margin (indistinct or distinct), (4) echogenicity (homogeneous or heterogeneous), (5) presence or absence of central hilar structure, and (6) presence or absence of coagulation necrosis sign. The sonographic findings were compared with the final pathologic results. RESULTS: A total of 1,061 lymph nodes were retrospectively evaluated in 487 patients. The accuracy of predicting metastatic property for each category was as high as 63.8% to 86.0%. A multivariate analysis revealed that round shape, distinct margin, heterogeneous echogenicity, and presence of coagulation necrosis sign were independent predictive factors for metastasis. Two hundred eighty-five of the 664 lymph nodes (42.9%) having at least one metastatic feature of the four categories were pathologically proven metastatic, and 96.0% of lymph nodes (381/397) were proven not metastatic when all four categories were determined as benign. CONCLUSIONS: Sonographic features of lymph nodes based on the new EBUS imaging classification may be helpful in the prediction of metastatic lymph nodes during EBUS-TBNA.
Authors: Jessica S Wang Memoli; Ezzat El-Bayoumi; Nicholas J Pastis; Nichole T Tanner; Mario Gomez; J Terrill Huggins; Georgiana Onicescu; Elizabeth Garrett-Mayer; Kent Armeson; Katherine K Taylor; Gerard A Silvestri Journal: Chest Date: 2011-06-02 Impact factor: 9.410
Authors: Christian Jenssen; Jouke Tabe Annema; Paul Clementsen; Xin-Wu Cui; Mathias Maximilian Borst; Christoph Frank Dietrich Journal: J Thorac Dis Date: 2015-10 Impact factor: 2.895