Abstract：Objective To analyze image feature of multislice spiral CT of intrapulmonary lymph nodes. Methods The image features and clinical data of 15 cases with intrapulmonary lymph nodes were analyzed retrospectively between January 2014 and June 2017. All cases diagnosed by surgery and pathology. Among 15 cases, there were 6 males and 9 females, aged 38-69 years, with an average of 55.6 years. Low dose CT scan and high resolution CT scan were performed in all cases. Three cases received enhanced CT scan at the same time. The location, number, size, image features and accompanying lesions of pulmonary lymph nodes were observed. Results In total, 19 intrapulmonary lymph nodes were discovered in 15 cases by multi-slice spiral CT, with a maximum diameter of 4-10 (5.53±1.50)mm. There were 14 intrapulmonary lymph nodes situated at the right lung, 1 in the right upper lobe, 5 in the middle and 8 in the lower lobe. Other 5 intrapulmonary lymph nodes were all located at the inferior lobe of left lung. There were 15 lymph nodes occurred at the outside of sub-pleural area or near the interlobular pleura. The vertical distance between lesions and adjacent pleura were from 3-16 mm, with an average of 9 mm. Other 4 lymph nodes were closely attached to the sub-pleura. The boundary of 17 lymph nodes was clear and sharp, and other 2 were rough. The density of 17 lymph nodes was uniform and other 2 were uneven, without calcification or cystoid variation. In axial images, 11 pulmonary lymph nodes were round like, 2 triangular and 6 irregular. In 12 lymph nodes, one or more uniform and compact linear shadows were linked to the lesions on the axis image or reconstructed image of coronal and sagittal plane. Three intrapulmonary lymph nodes were found in 3 cases by enhanced CT scan. Two lymph nodes showed no obvious enhancement and 1 showed progressive delayed enhancement. There were 4 cases accompanied with primary lung cancer at the same time. Conclusions The image features of intrapulmonary lymph nodes represent some common characteristics. Learning about these futures will contribute to clear diagnosis before surgery.
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2018, Vol. 23 
