Efficacy of Low Dose Computed Tomography Using Adaptive Statistical Iterative Reconstruction in Lung Cancer Screening
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- Category: Vol. 89, June 2021
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Efficacy of Low Dose Computed Tomography Using Adaptive Statistical Iterative Reconstruction in Lung Cancer Screening, SABRY ALAM EL-DIN M. EL-MOGY, MOHAMMAD Kh. EL-BADRAWY, NEHAL E. EL-EMAM and NEHAL THARWAT
Abstract
Background: Lung cancer is the most common malignant tumor and the leading cause of cancer-related deaths all over the world. Early detection and treatment are important to increase survival rate. Therefore, screening of lung cancer should target those individuals at high risk. Aim of Study: To detect the efficacy of low dose computed tomography (LDCT) of the chest with adaptive statistical iterative reconstruction (ASIR) algorithmas a screening method in diagnosing early stages of lung cancer and thus decrease the disease related morbidity and mortality as itminimizes exposure to ionizing radiation while maintaining sufficient image quality. Material and Methods: Ninety-six high risk cases (current smokers or ex-smokers), 94 males and 2 females, withage range from 50-78 yearswere included in this study. All cases underwent CT of the chest using low dose protocol with-ASIR algorithm with different blending levels of reconstruction (40%, 60%) for lung cancer screening. All images were interpreted using the International Early Lung Cancer Action Program (I-ELCAP) diagnostic protocol for lung nodule diagnosis and management. Results: From 96 cases included in the study, 82 cases had normal chest CT and 14 cases showed abnormal findings in chest CT (4 of them showed nodular lung lesions and the other 10 cases showed other findings related to smoking as bullae, bronchial wall thickening, emphysema, honey combing and bronchiectasis). Among the 6 nodules detected in the 4 cases, one nodule was >!15mm, and 5 nodules were <15mm. According to I-ELCAP diagnostic protocol, one nodule was considered positive and 5 nodules were considered semi-positive. LDCT chest using ASIR algorithm for lung cancer screening revealed high sensitivity and specificity for detecting lesions at cut off point size 6 mm (84.9% and 100% respec-tively). The area under receiver operating characteristic (ROC) curve for prediction of nodule with cutoff point size 6mm was 0.938 with 95% confidence interval (0.887-0.990). Conclusion: LDCT of the chest using ASIR algorithm is a promising and efficient tool for lung cancer screening with significant minimization of ionizing radiation exposure as well as preserved optimum image quality.