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1 Section of Cardiovascular Imaging, Division of Radiology/ Hb6, The Cleveland
Clinic Foundation, 9500 Euclid Ave., Cleveland, OH 44195.
2 Department of Biostatistics and Epidemiology, The Cleveland Clinic Foundation,
Cleveland, OH 44195.
OBJECTIVE. The potential clinical impact of variability in the measurement of coronary artery calcification with sequential MDCT was evaluated using Agatston, volume, and mass scoring algorithms.
SUBJECTS AND METHODS. Fifty-six patients were imaged twice using an identical prospectively ECG-triggered sequential scanning protocol. The Agatston, volume, and mass scores were computed by two observers independently. In addition, a patient's total Agatston score was referenced to an age- and sex-stratified database to determine a percentile ranking. Interscan, interobserver, and intraobserver variability and the resultant impact on patients' risk stratifications were assessed.
RESULTS. Significant interscan differences were found for all mean coronary calcium scores (Wilcoxson's signed rank test, p < 0.0001). Although the median percentage of interscan variability was low for all scoring methods, the interquartile range was wide, indicating significant variability in the data. Median scores (lower quartile–upper quartile) for observers 1 and 2, respectively, were as follows: Agatston, 5% (0–79%) and 6% (0–83%); volume, 12% (0–51%) and 12% (0–57%); and mass, 14% (0–57%) and 14% (0–58%). Interobserver and intraobserver differences between mean calcium scores were not significant, and consequently, lower interobserver and intraobserver variabilities (narrow interquartile ranges of 0–5%) were observed for all scores. Despite significant interscan differences in calcium scores, the percentile ranking assigned to the two scans differed in only 13% of patients. Interobserver differences resulted in a change in the percentile ranking in 7–9% of patients, whereas intraobserver differences caused a change in only 5% of patients.
CONCLUSION. The accuracy of sequential MDCT for coronary calcium quantification is sufficient in most cases for stratification of patient risk.
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