Frequency of coronary artery calcification on low-dose computed tomography screening for lung cancer

PURPOSE: The purpose of this study was to determine the frequency of coronary artery calcification (CAC) in high-risk people undergoing computed tomography (CT) screening for lung cancer. METHODS: Between 1999 and 2004, we performed CT screening for lung cancer on 4250 participants, all without documented prior cardiovascular disease, using multidetector-row (MD) CT. Of the patients, 1102 underwent imaging with a four-detector-row CT at 120 kVp and 40 mA, with pitch 1.5 and collimation of 2.5 mm in a single breath hold of 15-20 seconds, and 3148 did with an eight-detector-row CT at the same kVp, mA, and pitch settings but with collimation of 1.25 mm. Visualized CACs in each coronary artery (main, left anterior descending, circumflex, and right) were scored separately as 0 (absent), 1 (mild), 2 (moderate), or 3 (severe), yielding a possible score of 0-12 for each person. Frequency distributions by gender, age, and pack-years of smoking were determined. Odds ratios (ORs) were calculated using logistic regression analysis of the prevalence of CAC as a joint function of gender, age, pack-years of smoking, and presence of diabetes. RESULTS: Among the subjects younger than 50 years, positive CAC scores were three times more frequent for men than for women (22% vs. 7%); among those older than 50 years, the frequency increased for both men and women but the increase for women was greater than that for men. The frequency of positive CAC scores increased with increasing pack-years of smoking; it was always higher for men than for women. The ORs were 2.6 for male gender (P<.0001), 3.7 and 9.6 for ages 60-69 years and 70 years or older, respectively, for increasing age (P<.0001 for both), 1.6 and 2.3 for 30-59 pack-years and 60 pack-years or longer, respectively, for increasing pack-years of smoking (P<.0001 for both), and 1.6 for having diabetes (P=.016). CONCLUSION: The CAC score can be derived from ungated low-dose MDCT images. This information can contribute to risk stratification and management of coronary artery disease.