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Diagnostic Performance of Lung-RADS Categories in Patients With Histopathologically Evaluated Pulmonary Lesions: A
M Ertugrul1, U Bozlar2, D Guvenir3
1Department of Radiology, Ürgüp State Hospital, Nevşehir, Turkey.
Background And Aim:
This study aimed to evaluate the diagnostic performance of Lung Imaging Reporting and Data System (Lung-RADS) categories for predicting malignancy in a selected cohort of patients with pulmonary lesions who underwent histopathological evaluation.
Methods:
This retrospective diagnostic accuracy study included patients with pulmonary lesions detected on computed tomography (CT) who underwent histopathological evaluation between January 2011 and February 2018, and their CT images were retrospectively classified according to Lung-RADS version 1.0. Patients were grouped by age and sex. Histopathologic examination was accepted as the gold standard test. Negative and positive results according to the Lung RADS guidelines and histopathological results were compared. Sensitivity, specificity, positive predictive, and negative predictive values were calculated as a result of this comparison.
Results:
A total of 161 patients were included, of whom 122 (75.8%) had malignant and 39 (24.2%) had benign histopathological findings. According to Lung-RADS, 151 patients (93.8%) were classified as positive and 10 (6.2%) as negative. Lung-RADS categories were significantly associated with histopathological outcomes ( P < 0.001), with malignancy rates increasing across categories. Sensitivity, specificity, PPV, and NPV were 99.2%, 23.1%, 80.1%, and 90.0%, respectively. Diagnostic performance was more favorable in older patients, particularly in the 55-80 age group (κ =0.407, P < 0.001), with similar findings observed in the 55-74 subgroup (κ =0.404, P < 0.001).
Conclusions:
In this selected cohort of patients undergoing histopathological evaluation, Lung-RADS demonstrated high sensitivity but limited specificity for predicting malignant pulmonary lesions. We believe that prospective studies conducted using multicenter, standardized protocols involving larger patient groups will yield more accurate data.
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