Interplatform Reproducibility of CT Coronary Calcium Scoring Software

Published Online:

Our comparative analysis shows high correlation and statistical comparability of multidetector CT-derived coronary artery calcium scores calculated with different commercially available software systems.


To investigate whether coronary artery calcium (CAC) scoring performed on three different workstations generates comparable and thus vendor-independent results.

Materials and Methods

Institutional review board and Federal Office for Radiation Protection approval were received, as was each patient’s written informed consent. Fifty-nine patients (37 men, 22 women; mean age, 57 years ± 3 [standard deviation]) underwent CAC scoring with use of 64-section multidetector computed tomography (CT) with retrospective electrocardiographic gating (one examination per patient). Data sets were created at 10% increments of the R-R interval from 40%–80%. Two experienced observers in consensus calculated Agatston and volume scores for all data sets by using the calcium scoring software of three different workstations. Comparative analysis of CAC scores between the workstations was performed by using regression analysis, Spearman rank correlation (rs), and the Kruskal-Wallis test.


Each workstation produced different absolute numeric results for Agatston and volume scores. However, statistical analysis revealed excellent correlation between the workstations, with highest correlation at 60% of the R-R interval (minimal rs = 0.998; maximal rs = 0.999) for both scoring methods. No significant differences were detected for Agatston and volume score results between the software platforms. At analysis of individual reconstruction intervals, each workstation demonstrated the same score variability, with the consequence that 12 of 59 patients were assigned to divergent cardiac risk groups by using at least one of the workstations.


While mere numeric values might be different, commercially available software platforms produce comparable CAC scoring results, which suggests a vendor-independence of the method; however, none of the analyzed software platforms appears to provide a distinct advantage for risk stratification, as the variability of CAC scores depending on the reconstruction interval persists across platforms.

© RSNA, 2012

Supplemental material:


  • 1 Quercioli A, Montecucco F, Bertolotto M, et al.. Coronary artery calcification and cardiovascular risk: the role of RANKL/OPG signalling. Eur J Clin Invest 2010;40(7):645–654.
  • 2 Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 1990;15(4):827–832.
  • 3 Greenland P, Bonow RO, Brundage BH, et al.. ACCF/AHA 2007 clinical expert consensus document on coronary artery calcium scoring by computed tomography in global cardiovascular risk assessment and in evaluation of patients with chest pain: a report of the American College of Cardiology Foundation Clinical Expert Consensus Task Force (ACCF/AHA Writing Committee to Update the 2000 Expert Consensus Document on Electron Beam Computed Tomography). Circulation 2007;115(3):402–426.
  • 4 Knollmann FD, Helmig K, Kapell S, et al.. Coronary artery calcium scoring: diagnostic accuracy of different software implementations. Invest Radiol 2003;38(12):761–768.
  • 5 Haberl R, Becker A, Leber A, et al.. Correlation of coronary calcification and angiographically documented stenoses in patients with suspected coronary artery disease: results of 1,764 patients. J Am Coll Cardiol 2001;37(2):451–457.
  • 6 Schlosser T, Hunold P, Voigtländer T, Schmermund A, Barkhausen J. Coronary artery calcium scoring: influence of reconstruction interval and reconstruction increment using 64-MDCT. AJR Am J Roentgenol 2007;188(4):1063–1068.
  • 7 Elias-Smale SE, Proença RV, Koller MT, et al.. Coronary calcium score improves classification of coronary heart disease risk in the elderly: the Rotterdam study. J Am Coll Cardiol 2010;56(17):1407–1414.
  • 8 Vliegenthart R, Oudkerk M, Hofman A, et al.. Coronary calcification improves cardiovascular risk prediction in the elderly. Circulation 2005;112(4):572–577.
  • 9 Budoff MJ, Gul KM. Expert review on coronary calcium. Vasc Health Risk Manag 2008;4(2):315–324.
  • 10 Devries S, Wolfkiel C, Shah V, Chomka E, Rich S. Reproducibility of the measurement of coronary calcium with ultrafast computed tomography. Am J Cardiol 1995;75(14):973–975.
  • 11 Yamamoto H, Budoff MJ, Lu B, Takasu J, Oudiz RJ, Mao S. Reproducibility of three different scoring systems for measurement of coronary calcium. Int J Cardiovasc Imaging 2002;18(5):391–397.
  • 12 Detrano RC, Anderson M, Nelson J, et al.. Coronary calcium measurements: effect of CT scanner type and calcium measure on rescan reproducibility—MESA study. Radiology 2005;236(2):477–484.
  • 13 Hong C, Becker CR, Schoepf UJ, Ohnesorge B, Bruening R, Reiser MF. Coronary artery calcium: absolute quantification in nonenhanced and contrast-enhanced multi-detector row CT studies. Radiology 2002;223(2):474–480.
  • 14 Hong C, Bae KT, Pilgram TK. Coronary artery calcium: accuracy and reproducibility of measurements with multi-detector row CT—assessment of effects of different thresholds and quantification methods. Radiology 2003;227(3):795–801.
  • 15 Hoffmann U, Siebert U, Bull-Stewart A, et al.. Evidence for lower variability of coronary artery calcium mineral mass measurements by multi-detector computed tomography in a community-based cohort—consequences for progression studies. Eur J Radiol 2006; 57(3):396–402.
  • 16 Takahashi N, Bae KT. Quantification of coronary artery calcium with multi-detector row CT: assessing interscan variability with different tube currents pilot study. Radiology 2003;228(1):101–106.
  • 17 Hong C, Bae KT, Pilgram TK, Zhu F. Coronary artery calcium quantification at multi-detector row CT: influence of heart rate and measurement methods on interacquisition variability initial experience. Radiology 2003;228(1):95–100.
  • 18 van Ooijen PM, Vliegenthart R, Witteman JC, Oudkerk M. Influence of scoring parameter settings on Agatston and volume scores for coronary calcification. Eur Radiol 2005;15(1):102–110.
  • 19 Matsuura N, Horiguchi J, Yamamoto H, et al.. Optimal cardiac phase for coronary artery calcium scoring on single-source 64-MDCT scanner: least interscan variability and least motion artifacts. AJR Am J Roentgenol 2008;190(6):1561–1568.
  • 20 Horiguchi J, Fukuda H, Yamamoto H, et al.. The impact of motion artifacts on the reproducibility of repeated coronary artery calcium measurements. Eur Radiol 2007;17(1):81–86.
  • 21 Rutten A, Krul SP, Meijs MF, de Vos AM, Cramer MJ, Prokop M. Variability of coronary calcium scores throughout the cardiac cycle: implications for the appropriate use of electrocardiogram-dose modulation with retrospectively gated computed tomography. Invest Radiol 2008;43(3):187–194.
  • 22 Mahnken AH, Wildberger JE, Sinha AM, et al.. Variation of the coronary calcium score depending on image reconstruction interval and scoring algorithm. Invest Radiol 2002;37(9):496–502.
  • 23 Schlosser T, Hunold P, Schmermund A, et al.. Coronary artery calcium score: influence of reconstruction interval at 16-detector row CT with retrospective electrocardiographic gating. Radiology 2004;233(2):586–589.
  • 24 Adamzik M, Schmermund A, Reed JE, Adamzik S, Behrenbeck T, Sheedy PF. Comparison of two different software systems for electron-beam CT-derived quantification of coronary calcification. Invest Radiol 1999;34(12):767–773.
  • 25 Jakobs TF, Becker CR, Ohnesorge B, et al.. Multislice helical CT of the heart with retrospective ECG gating: reduction of radiation exposure by ECG-controlled tube current modulation. Eur Radiol 2002;12(5):1081–1086.
  • 26 Budoff MJ, Nasir K, McClelland RL, et al.. Coronary calcium predicts events better with absolute calcium scores than age-sex-race/ethnicity percentiles: MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol 2009;53(4):345–352.
  • 27 Rumberger JA. Using noncontrast cardiac CT and coronary artery calcification measurements for cardiovascular risk assessment and management in asymptomatic adults. Vasc Health Risk Manag 2010;6:579–591.
  • 28 Rumberger JA, Brundage BH, Rader DJ, Kondos G. Electron beam computed tomographic coronary calcium scanning: a review and guidelines for use in asymptomatic persons. Mayo Clin Proc 1999;74(3):243–252.
  • 29 Altman DG. Statistics and ethics in medical research. VII—Interpreting results. BMJ 1980;281(6255):1612–1614.
  • 30 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1(8476):307–310.
  • 31 Kruskal WH, Wallis WA. Use of ranks in one-criterion variance analysis. J Am Stat Assoc 1952;47(260):583–621.
  • 32 Ghadri JR, Goetti R, Fiechter M, et al.. Inter-scan variability of coronary artery calcium scoring assessed on 64-multidetector computed tomography vs. dual-source computed tomography: a head-to-head comparison. Eur Heart J 2011;32(15):1865–1874.
  • 33 Hoff JA, Chomka EV, Krainik AJ, Daviglus M, Rich S, Kondos GT. Age and gender distributions of coronary artery calcium detected by electron beam tomography in 35,246 adults. Am J Cardiol 2001;87(12):1335–1339.
  • 34 Yaghoubi S, Tang W, Wang S, et al.. Offline assessment of atherosclerotic coronary calcium from electron beam tomograms. Am J Card Imaging 1995;9(4):231–236.
  • 35 Efstathopoulos EP, Pantos I, Thalassinou S, et al.. Patient radiation doses in cardiac computed tomography: comparison of published results with prospective and retrospective acquisition. Radiat Prot Dosimetry 2012;148(1):83–91.

Article History

Received November 24, 2011; revision requested January 18, 2012; revision received February 28; accepted March 2; final version accepted March 22.
Published online: Oct 2012
Published in print: Oct 2012