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OBJECTIVE: The objective of our study was to develop a model for determining the smallest statistically significant change in the coronary artery calcium score (CAC) between serial measurements in a given subject. MATERIALS AND METHODS: We assembled a convenience sample of 2,217 pairs of repeated electron beam CT coronary calcium scans acquired in quick succession. Each scan consisted of forty 100-msec, 3-mm sections obtained at 60% of the ECG R-R interval. A single observer quantified calcium in each scan independent of knowledge of calcium quantity in the repeated scan. We then modeled a relationship between the variation of the differences between repeated measurements of calcium and the magnitude of the calcium score and formulated 95% repeatability coefficient equations for the Agatston and volumetric CAC score. The equations allow determining the smallest statistically significant interval change in the calcium score between two serial measurements in a given subject. RESULTS: In a subject with measurable CAC at baseline, the smallest statistically significant interval change is +/- (4.930 x square root of baseline Agatston CAC score) or +/- (3.445 x square root of baseline volumetric CAC score). In a subject with no measurable CAC at baseline, a follow-up CAC score exceeding 11.6 Agatston units or 9.5 mm3 qualifies for statistically significant progression. The results were similar in men and women. CONCLUSION: By examining repeatability of quantitative electron beam CT measurements of coronary calcium as a function of the magnitude of the calcium score, we developed a model to determine the smallest statistically significant change between serial measurements in a given subject.
Sevrukov et al. (Tue,) studied this question.