Assessment of Calcium Score Cutoff Point for Clinically Significant Aortic Stenosis on Lung Cancer Screening Program Low-Dose Computed Tomography—A Cross-Sectional Analysis - Kaja Klein-Awerjanow; Witold Rzyman; Robert Dziedzic; Jadwiga Fijalkowska; Piotr Spychalski; Edyta Szurowska; Marcin Fijalkowski (Diagnostics, 2023)
Low-dose computed tomography (LDCT) is predominantly applied in lung cancer screening programs. Tobacco smoking is the main risk factor for developing lung cancer but is also common for cardiovascular diseases, including aortic stenosis (AS). Consequently, an increased prevalence of cardiovascular diseases is expected in lung cancer screenees. Therefore, initial aortic valve calcification evaluation should be additionally performed on LDCT. The aim of this study was to estimate a calcium score (CS) cutoff point for clinically significant AS diagnosis based on LDCT, confirmed by echocardiographic examination. The study included 6631 heavy smokers who participated in a lung cancer screening program (MOLTEST BIS). LDCTs were performed on all individuals and were additionally assessed for aortic valve calcification with the use of CS according to the Agatston method. Patients with CS ≥ 900 were referred for echocardiography to confirm the diagnosis of AS and to evaluate its severity. Of 6631 individuals, 54 met the inclusion criteria and underwent echocardiography for confirmation and assessment of AS. Based on that data, receiver operating characteristic (ROC) curves of CS were plotted, and cutoff points for clinically significant AS diagnosis were established: A CS of 1758 for at least moderate AS had 85.71% (CI 65.36–95.02%) sensitivity and 75.76% (CI 58.98–87.17%) specificity; a CS of 2665 for severe AS had 87.5% (CI 73.89–94.54%) sensitivity and 76.92% (CI 49.74–91.82%) specificity. This is the first study to assess possible CS cutoff points for diagnosing clinically significant AS detected by LDCT in lung cancer screening participants. LDCT with CS assessment could enable early detection of patients with clinically significant AS and therefore identify patients who require appropriate treatment.