Ullrich Ebersberger MD, Presenter: Nothing to Disclose

Dov Eilot PhD, Abstract Co-Author: Employee, Rcadia Medical Imaging, Ltd

U. Joseph Schoepf MD, Abstract Co-Author: Research Consultant, Bayer AG Research Grant, Bayer AG Research Consultant, Bracco Group Research Grant, Bracco Group Research Consultant, General Electric Company Research Grant, General Electric Company Research Consultant, Siemens AG Research Grant, Siemens AG

James Reid Spears BS, Abstract Co-Author: Nothing to Disclose

Garrett W. Rowe BS, Abstract Co-Author: Nothing to Disclose

Roman Goldenberg PhD, Abstract Co-Author: Employee, Rcadia Medical Imaging, Ltd

Alon Lev PhD, Abstract Co-Author: Employee, Rcadia Medical Imaging, Ltd

Coronary artery calcium scoring (CCS) is well established for risk stratification and early detection of coronary atherosclerosis and has been recognized as an independent predictor of cardiovascular events. It is often performed as a non contrast-enhanced CT scan prior to contrast-medium enhanced coronary CT angiography (cCTA) studies. The purpose of our investigation was to evaluate the accuracy of a fully automated system for computing CCS from contrast enhanced coronary cCTA data.

With IRB approval and in HIPAA compliance, we included 39 patients (age 62±10yrs, 22 male) who had undergone contrast-medium enhanced cCTA as well as non-contrast CCS studies using 2nd generation dual-source CT. Calcium scores were computed from cCTA using an automatic software application (COR Analyzer, Rcadia). For extracting calcium scores from contrast-enhanced cCTA data, this algorithm performs a segmentation process employing a model of intensity value distribution in a tubular structure, which is adaptive to the local vessel geometry as well as to the local contrast intensity and noise estimations. Calcium scores derived from processed cCTA studies were compared to CCS measures obtained by standard manual assessment (Aquarius Intuition, TeraRecon) of non-contrast CCS studies. Results were correlated according to age, gender, and race dependent Multi Ethnic Study of Atherosclerosis (MESA) percentiles as well as 5 CCS cardiac risk categories (0, 1-10, 11-100, 101-400, >400).

35/39 scans were successfully processed. Mean Agatston score measurements did not differ between non-contrast and contrast-enhanced CT studies (459.4 ± 585.3 versus 421.2 ± 574.2; p >0.05). MESA percentiles were also not significantly different (p>0.05) based on processed contrast enhanced cCTA studies (66.0 ± 36.7) when compared to non-contrast CCS studies (64.5 ± 38.7). CCS risk categories between the two groups showed very high correlation (Spearman rank correlation coefficient = 0.97, p<0.0001).

CCS values automatically computed from contrast-enhanced cCTA studies are highly correlated with measurements from standard non-contrast CCS scans. These results suggest a radiation dose- and room time-saving potential by deriving calcium scores from cCTA studies.

The method described here may obviate the need for dedicated CCS studies prior to performing cCTA and reduce radiation exposure to patients with suspected coronary artery disease.

Ebersberger, U, Eilot, D, Schoepf, U, Spears, J, Rowe, G, Goldenberg, R, Lev, A, Automatic Assessment of Calcium Scores from Contrast-Enhanced Dual-Source Coronary CT Angiography.  Radiological Society of North America 2012 Scientific Assembly and Annual Meeting, November 25 - November 30, 2012 ,Chicago IL. http://archive.rsna.org/2012/12034445.html