Qualitative (and Quantitative) Values of the Lung-RADS and Computed Tomography in Diagnosing Solitary Pulmonary Nodules

• Published in: Diagnostics (Basel) Vol. 12; no. 11; p. 2699
• Main Authors: Duan, Lizhen, Shan, Wenli, Bo, Genji, Lu, Guangming, Guo, Lili
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.11.2022; MDPI
• Subjects: Analysis; Calcification; Care and treatment; CT imaging; CT signs; Diagnosis; Diagnosis, Differential; Hyperplasia; Lung cancer; Lung diseases; Lung-RADS; Methods; Pulmonary function tests; ROC curve; Semantics; Software; solitary pulmonary nodules; Tomography; Tumors; Taiwan; Lung-RADS; ROC curve; CT signs; solitary pulmonary nodules
• ISSN: 2075-4418; 2075-4418
• DOI: 10.3390/diagnostics12112699

Background: Lung-RADS classification and CT signs can both help in the differential diagnosis of SPNs. The purpose of this study was to investigate the diagnostic value of these two methods and the combination of the two methods for solitary pulmonary nodules (SPNs). Methods: A total of 296 cases of SPNs were retrospectively analyzed. All the SPNs were classified according to the Lung-RADS grading version 1.1. The scores of each lesion were calculated according to their CT signs. Imaging features, such as the size and margin of the lesions, pleural traction, spiculation, lobulation, bronchial cutoff, air bronchogram, vacuoles, tumor vasculature, and cavity signs, were analyzed. The imaging results were compared with the pathology examination findings. Receiver operating characteristic (ROC) curves were applied to compare the values of the different methods in differentially diagnosing benign and malignant SPNs. Results: The sensitivity, specificity, and accuracy of Lung-RADS grading for diagnosing SPNs were 34.0%, 94.4%, and 47.6%, respectively. The area under the ROC curve (AUC) was 0.600 (p < 0.001). The sensitivity, specificity, and accuracy of the CT sign scores were 56.3%, 70.0%, and 60.5%, respectively, and the AUC was 0.657 (p < 0.001). The sensitivity, specificity, and accuracy of the combination of the two methods for diagnosing SPNs were 93.2%, 61.1%, and 83.5%, and the AUC was 0.777 (p < 0.001). Conclusion: The combination of Lung-RADS classification and CT signs significantly improved the differential diagnosis of SPNs.