Impact of lung-RADS classification system on the accurate diagnosis of pulmonary nodular lesions in oncology patients

• Published in: Egyptian journal of radiology and nuclear medicine 2021-07, Vol.52 (1), p.173-8
• Main Authors: Ahmed, Hoda Abdel Kareem, FarghalyAmin, Mohamed
• Format: Article
• Language: English
• Subjects: Classification; Etiology; Histopathology; Lung cancer; Lung-RADS; Males; Medical research; Medicine, Experimental; Metastasis; Oncology; Patients; Prostate; Pulmonary nodules; Thyroid gland; Tomography
• ISSN: 0378-603X; 2090-4762
• DOI: 10.1186/s43055-021-00551-9

Background Lung assessment is highly recommended in the management of oncology patients as it is the commonest affected site in metastatic dissemination. The low-dose CT with nodule reporting system based on Lung Reporting and Data System (lung-RADS) is a promising non-invasive tool for the characterization of incidentally detected pulmonary nodules. The authors aimed to assess the accuracy of the "lung-RADS" classification system as a non-invasive tool for the characterization of any newly developed pulmonary nodules among oncology patients. Ethics committee approval and informed written consent were obtained from the studied patients. A non-contrast LDCT study was performed on all patients with a nodule reporting system based on the lung-RADS classification system applied for evaluation of each detected pulmonary nodule. Diagnoses were established using the help of either histopathology or follow-up clinical results as a gold standard. Results In this prospective study, we enrolled 187 known malignancy patients with 200 suspicious newly developed pulmonary nodules. Their mean patient age was 48.4 ± 9.7 years. The studied 200 pulmonary nodular lesions were categorized using a nodule reporting system based on the lung-RADS into 6 sub-groups with 122 lesions found to be malignant and 78 lesions were of benign etiology, which showed a high sensitivity of 92.08%, specificity of 78.79%, and accuracy of 85.50% with 81.58% positive predictive value and 90.70% negative predictive value in the diagnosis of pulmonary nodules in cancer patients. Conclusion Low-density CT with a nodule reporting system based on the lung-RADS classification system was found to be an accurate non-invasive tool to characterize and to risk stratify pulmonary nodules in oncology patients.