Abstract
ObjectiveTo determine the agreement and reliability of fully automated coronary artery calcium (CAC) scoring in a lung cancer screening population.Materials and Methods1793 low-dose chest CT scans were analyzed (non-contrast-enhanced, non-gated). To establish the reference standard for CAC, first automated calcium scoring was performed using a preliminary version of a method employing coronary calcium atlas and machine learning approach. Thereafter, each scan was inspected by one of four trained raters. When needed, the raters corrected initially automaticity-identified results. In addition, an independent observer subsequently inspected manually corrected results and discarded scans with gross segmentation errors. Subsequently, fully automatic coronary calcium scoring was performed. Agatston score, CAC volume and number of calcifications were computed. Agreement was determined by calculating proportion of agreement and examining Bland-Altman plots. Reliability was determined by calculating linearly weighted kappa (κ) for Agatston strata and intraclass correlation coefficient (ICC) for continuous values.Results44 (2.5%) scans were excluded due to metal artifacts or gross segmentation errors. In the remaining 1749 scans, median Agatston score was 39.6 (P25–P75∶0–345.9), median volume score was 60.4 mm3 (P25–P75∶0–361.4) and median number of calcifications was 2 (P25–P75∶0–4) for the automated scores. The κ demonstrated very good reliability (0.85) for Agatston risk categories between the automated and reference scores. The Bland-Altman plots showed underestimation of calcium score values by automated quantification. Median difference was 2.5 (p25–p75∶0.0–53.2) for Agatston score, 7.6 (p25–p75∶0.0–94.4) for CAC volume and 1 (p25–p75∶0–5) for number of calcifications. The ICC was very good for Agatston score (0.90), very good for calcium volume (0.88) and good for number of calcifications (0.64).DiscussionFully automated coronary calcium scoring in a lung cancer screening setting is feasible with acceptable reliability and agreement despite an underestimation of the amount of calcium when compared to reference scores.
Highlights
Smoking is an important factor in the etiology of cardiovascular disease (CVD) [1,2]
Fully automated coronary calcium scoring in a lung cancer screening setting is feasible with acceptable reliability and agreement despite an underestimation of the amount of calcium when compared to reference scores
Intraclass correlation coefficient (ICC) between absolute Agatston scores on two low-dose ungated computed tomography (CT) scans within four months was very good (0.94) [16]. These findings indicate that CAC scores obtained in lung cancer screening setting can be used for identification of subjects at risk of CVD events
Summary
Smoking is an important factor in the etiology of cardiovascular disease (CVD) [1,2]. Intraclass correlation coefficient (ICC) between absolute Agatston scores on two low-dose ungated CT scans within four months was very good (0.94) [16]. These findings indicate that CAC scores obtained in lung cancer screening setting can be used for identification of subjects at risk of CVD events. Manual scoring of CAC on low-dose non-gated CT is time-consuming as a result of the increased number of slices and the high prevalence of coronary calcification, difficult due to cardiac motion and cumbersome and expensive in a screening setting. Automated quantification of CAC could overcome these limitations and previous studies demonstrated preliminary feasibility using non-gated CT [17]
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