To attempt to develop a simple scoring system based on images of endobronchial ultrasound (EBUS) to discriminate between benign and malignant pulmonary nodules.

data of patients who undergone bronchoscopy in the Bronchoscopy Room of North Jiangsu People′s Hospital during May 1, 2018 and March 1, 2020 were retrospectively included. all of the patients′chest CT scan showed pulmonary nodules ≤3 cm, while routine bronchoscopy showed no obvious abnormalities. Ultrasound probe guided biopsy and brush examination were used to assist in the diagnosis of the disease. Patients with no definite diagnosis were further subjected to invasive surgeries or observations after the treatment for at least 3 months to obtain the final diagnosis. Eight different EBUS image characteristics including lesion shape, margin, border, internal echo strength, homogeneous, or heterogeneous internal echoe, air bronchogram, irregular anechoic area, concentric circles were observed, and the relationship between these image characteristics and the nature of pulmonary nodules were analyzed, a simple scoring system was established, datas were analyzed using SPSS software.

Among 114 patients with pulmonary nodules, 65 were benign and 49 were malignant. Three image features in EBUS images, including round or round shape of lesions, discontinuous margin, and heterogeneous echogenicity, with statistically significant (P<0.05). According to the simple scoring system established, ROC curve was drawn. When the score was set at 7, the sensitivity (65.3%) and specificity (78.5%) were the highest, and this was the best point for diagnosis. When the score is≥7, the diagnosis of pulmonary malignant lesions was more accurate. Kappa consistency was calculated with a coefficient of 0.441 (95%CI 0.274-0.607, P<0.01), showing moderate strength consistency.

EBUS can provide image characteristic information to differentiate the nature of pulmonary nodules, and the scoring system based on the images has a good application value in differentiating benign from malignant pulmonary nodules.