Abstract

Background: A pulmonary nodule is defined as a rounded or irregular opacity, well or poorly defined, measuring up to 3 cm in diameter. Early detection the malignancy of nodules has a significant role in decreasing the mortality, increasing the survival time and consider as early diagnosis lung cancer. Method: Selection criteria for sample: Nodules in the lung parenchyma measuring ≤ 30mm in patients >18 years old, high risk of malignancy, underwent chest low dose CT and histological examination. Results: The risk threshold for lung cancer prediction according to Lung-RADS 2019 in 83 study samples is 29.39% (Se 80%, Sp 54.6%, AUC 0.652, p<0.05). In which, Lung-RADS 2019 categories has Se 98%, Sp 21.2%, PPV 65.3%, NPV 87.5%, accuracy 67.5%, p<0.05); Lung-RADS 2019 predicts the risk of nodule malignancy through Lung Nodule software has Se 96%, Sp 27.3%, PPV 66.7%, NPV 81.8%, accuracy 68.7%, p<0.05. Conclusion: LungRADS 2019: Classification of American College of Radiology, LungRADS, is a new application but showed many advantages in comparison with others classification such as increasing positive predictive value (PPV), no result of false negative and cost effectiveness. “Lung nodule” was applied as a smart phone application in order to have a quick evaluation, especially the malignancy and management face on a pulmonary nodule.