Christian Tesche1,2, Carlo N De Cecco1,3, Andrew Stubenrauch1, Brian E Jacobs1, Akos Varga-Szemes1, Sheldon E Litwin1,4, B Devon Ball1, Moritz Baquet5, David Jochheim5, Ullrich Ebersberger1,2, Richard R Bayer4, Ellen Hoffmann2, Daniel H Steinberg4, U Joseph Schoepf6,7. 1. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA. 2. Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Englschalkinger Strasse 77, 81925, Munich, Germany. 3. Department of Radiological Sciences, Oncology and Pathology, University of Rome "Sapienza", Piazzale Aldo Moro 5, 00185, Rome, Italy. 4. Division of Cardiology, Department of Medicine, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA. 5. Department of Cardiology, Hospital of the Ludwig-Maximilians-University, Marchioninistrasse 15, 81377, Munich, Germany. 6. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA. schoepf@musc.edu. 7. Division of Cardiology, Department of Medicine, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA. schoepf@musc.edu.
Abstract
OBJECTIVE: To evaluate the correlation between aortic root calcification (ARC) markers and coronary artery calcification (CAC) derived from coronary artery calcium scoring (CACS) and their ability to predict obstructive coronary artery disease (CAD). METHODS: We retrospectively analyzed 189 patients (47% male, age 60.3 ± 11.1 years) with an intermediate probability of CAD who underwent clinically indicated CACS and coronary CT angiography (CCTA). ARC markers [aortic root calcium score (ARCS) and volume (ARCV)] were calculated and compared to CAC markers: coronary artery calcium score (CACS), volume (CACV), and mass (CACM). CCTA datasets were visually evaluated for significant CAD (stenosis ≥ 50%) and the ability of ARC markers to predict obstructive CAD was assessed. RESULTS: ARCS (mean 67.7 ± 189.5) and ARCV (mean 67.3 ± 184.7) showed significant differences between patients with and without CAC (109.4 ± 238.6 vs 9.42 ± 31.4, p < 0.0001; 108.5 ± 232.4 vs 9.9 ± 30.5, p < 0.0001). A strong correlation was found for ARCS and ARCV with CACS, CACM, and CACV (all p < 0.0001). In a multivariate analysis, ARCS (OR 1.09, p = 0.033) and ARCV (OR 1.12, p = 0.046) were independent markers for CAC. Using a receiver-operating characteristics analysis, the AUC to detect severe CAC was 0.71 (p < 0.0001) and 0.71 (p < 0.0001) for ARCS and ARCV, respectively. ARCS (0.67, p < 0.0001) and ARCV (0.68, p < 0.0001) showed discriminatory power for predicting obstructive CAD, yielding sensitivities 61 and 78% and specificities of 62 and 80%, respectively. CONCLUSION: ARC markers are associated with and independently predict the presence of CAC and obstructive CAD. Further testing is required in patients with severe ARC and significant CAD in order to reliably obtain these markers from thoracic-CT or X-ray for proper risk classification.
OBJECTIVE: To evaluate the correlation between aortic root calcification (ARC) markers and coronary artery calcification (CAC) derived from coronary artery calcium scoring (CACS) and their ability to predict obstructive coronary artery disease (CAD). METHODS: We retrospectively analyzed 189 patients (47% male, age 60.3 ± 11.1 years) with an intermediate probability of CAD who underwent clinically indicated CACS and coronary CT angiography (CCTA). ARC markers [aortic root calcium score (ARCS) and volume (ARCV)] were calculated and compared to CAC markers: coronary artery calcium score (CACS), volume (CACV), and mass (CACM). CCTA datasets were visually evaluated for significant CAD (stenosis ≥ 50%) and the ability of ARC markers to predict obstructive CAD was assessed. RESULTS: ARCS (mean 67.7 ± 189.5) and ARCV (mean 67.3 ± 184.7) showed significant differences between patients with and without CAC (109.4 ± 238.6 vs 9.42 ± 31.4, p < 0.0001; 108.5 ± 232.4 vs 9.9 ± 30.5, p < 0.0001). A strong correlation was found for ARCS and ARCV with CACS, CACM, and CACV (all p < 0.0001). In a multivariate analysis, ARCS (OR 1.09, p = 0.033) and ARCV (OR 1.12, p = 0.046) were independent markers for CAC. Using a receiver-operating characteristics analysis, the AUC to detect severe CAC was 0.71 (p < 0.0001) and 0.71 (p < 0.0001) for ARCS and ARCV, respectively. ARCS (0.67, p < 0.0001) and ARCV (0.68, p < 0.0001) showed discriminatory power for predicting obstructive CAD, yielding sensitivities 61 and 78% and specificities of 62 and 80%, respectively. CONCLUSION: ARC markers are associated with and independently predict the presence of CAC and obstructive CAD. Further testing is required in patients with severe ARC and significant CAD in order to reliably obtain these markers from thoracic-CT or X-ray for proper risk classification.
Authors: B F Stewart; D Siscovick; B K Lind; J M Gardin; J S Gottdiener; V E Smith; D W Kitzman; C M Otto Journal: J Am Coll Cardiol Date: 1997-03-01 Impact factor: 24.094
Authors: D S Jeon; S Atar; A V Brasch; H Luo; J Mirocha; T Z Naqvi; R Kraus; D S Berman; R J Siegel Journal: J Am Coll Cardiol Date: 2001-12 Impact factor: 24.094
Authors: Matthew J Budoff; Khurram Nasir; Ronit Katz; Junichiro Takasu; J Jeffery Carr; Nathan D Wong; Matthew Allison; Joao A C Lima; Robert Detrano; Roger S Blumenthal; Richard Kronmal Journal: Atherosclerosis Date: 2010-11-26 Impact factor: 5.162
Authors: Khurram Nasir; Ronit Katz; Mouaz Al-Mallah; Junichiro Takasu; David M Shavelle; Jeffery J Carr; Richard Kronmal; Roger S Blumenthal; Kevin O'Brien; Matthew J Budoff Journal: J Cardiovasc Comput Tomogr Date: 2009-12-28
Authors: Shane Oberoi; U Joseph Schoepf; Mathias Meyer; Thomas Henzler; Garret W Rowe; Philip Costello; John W Nance Journal: AJR Am J Roentgenol Date: 2013-04 Impact factor: 3.959