Omar Dzaye1, Alexander C Razavi2, Zeina A Dardari3, Daniel S Berman4, Matthew J Budoff5, Michael D Miedema6, Olufunmilayo H Obisesan3, Ellen Boakye3, Khurram Nasir7, Alan Rozanski8, John A Rumberger9, Leslee J Shaw10, Martin Bødtker Mortensen11, Seamus P Whelton3, Michael J Blaha3. 1. Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. Electronic address: odzaye@jhmi.edu. 2. Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA. 3. Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 4. Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA. 5. Lundquist Institute, Harbor-UCLA Medical Center, Torrance, California, USA. 6. Minneapolis Heart Institute and Foundation, Minneapolis, Minnesota, USA. 7. Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas, USA. 8. Division of Cardiology, Mount Sinai, St. Luke's Hospital, New York, New York, USA. 9. Department of Cardiac Imaging, Princeton Longevity Center, Princeton, New Jersey, USA. 10. Department of Radiology, Weill Cornell Medicine, New York, New York, USA. 11. Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark.
Abstract
OBJECTIVES: This study sought to assess the relationship between mean vs peak calcified plaque density and their impact on calculating coronary artery calcium (CAC) scores and to compare the corresponding differential prediction of atherosclerotic cardiovascular disease (ASCVD) and coronary heart disease (CHD) mortality. BACKGROUND: The Agatston CAC score is quantified per lesion as the product of plaque area and a 4-level categorical peak calcium density factor. However, mean calcium density may more accurately measure the heterogenous mixture of lipid-rich, fibrous, and calcified plaque reflective of ASCVD risk. METHODS: We included 10,373 individuals from the CAC Consortium who had CAC >0 and per-vessel measurements of peak calcium density factor and mean calcium density. Area under the curve and continuous net reclassification improvement analyses were performed for CHD and ASCVD mortality to compare the predictive abilities of mean calcium density vs peak calcium density factor when calculating the Agatston CAC score. RESULTS: Participants were on average 53.4 years of age, 24.4% were women, and the median CAC score was 68 Agatston units. The average values for mean calcium density and peak calcium density factor were 210 ± 50 HU and 3.1 ± 0.5, respectively. Individuals younger than 50 years of age and/or those with a total plaque area <100 mm2 had the largest differences between the peak and mean density measures. Among persons with CAC 1-99, the use of mean calcium density resulted in a larger improvement in ASCVD mortality net reclassification improvement (NRI) (NRI = 0.49; P < 0.001 vs. NRI = 0.18; P = 0.08) and CHD mortality discrimination (Δ area under the curve (AUC) = +0.169 vs +0.036; P < 0.001) compared with peak calcium density factor. Neither peak nor mean calcium density improved mortality prediction at CAC scores >100. CONCLUSION: Mean and peak calcium density may differentially describe plaque composition early in the atherosclerotic process. Mean calcium density performs better than peak calcium density factor when combined with plaque area for ASCVD mortality prediction among persons with Agatston CAC 1-99.
OBJECTIVES: This study sought to assess the relationship between mean vs peak calcified plaque density and their impact on calculating coronary artery calcium (CAC) scores and to compare the corresponding differential prediction of atherosclerotic cardiovascular disease (ASCVD) and coronary heart disease (CHD) mortality. BACKGROUND: The Agatston CAC score is quantified per lesion as the product of plaque area and a 4-level categorical peak calcium density factor. However, mean calcium density may more accurately measure the heterogenous mixture of lipid-rich, fibrous, and calcified plaque reflective of ASCVD risk. METHODS: We included 10,373 individuals from the CAC Consortium who had CAC >0 and per-vessel measurements of peak calcium density factor and mean calcium density. Area under the curve and continuous net reclassification improvement analyses were performed for CHD and ASCVD mortality to compare the predictive abilities of mean calcium density vs peak calcium density factor when calculating the Agatston CAC score. RESULTS: Participants were on average 53.4 years of age, 24.4% were women, and the median CAC score was 68 Agatston units. The average values for mean calcium density and peak calcium density factor were 210 ± 50 HU and 3.1 ± 0.5, respectively. Individuals younger than 50 years of age and/or those with a total plaque area <100 mm2 had the largest differences between the peak and mean density measures. Among persons with CAC 1-99, the use of mean calcium density resulted in a larger improvement in ASCVD mortality net reclassification improvement (NRI) (NRI = 0.49; P < 0.001 vs. NRI = 0.18; P = 0.08) and CHD mortality discrimination (Δ area under the curve (AUC) = +0.169 vs +0.036; P < 0.001) compared with peak calcium density factor. Neither peak nor mean calcium density improved mortality prediction at CAC scores >100. CONCLUSION: Mean and peak calcium density may differentially describe plaque composition early in the atherosclerotic process. Mean calcium density performs better than peak calcium density factor when combined with plaque area for ASCVD mortality prediction among persons with Agatston CAC 1-99.
Authors: Michael J Blaha; Seamus P Whelton; Mahmoud Al Rifai; Zeina A Dardari; Leslee J Shaw; Mouaz H Al-Mallah; Kuni Matsushita; John A Rumberger; Daniel S Berman; Matthew J Budoff; Michael D Miedema; Khurram Nasir Journal: J Cardiovasc Comput Tomogr Date: 2016-11-11
Authors: Michael H Criqui; Jessica B Knox; Julie O Denenberg; Nketi I Forbang; Robyn L McClelland; Thomas E Novotny; Veit Sandfort; Jill Waalen; Michael J Blaha; Matthew A Allison Journal: JACC Cardiovasc Imaging Date: 2017-08
Authors: Song S Mao; Raveen S Pal; Charles R McKay; Yan G Gao; Ambarish Gopal; Naser Ahmadi; Janis Child; Sivi Carson; Junichiro Takasu; Behnaz Sarlak; Daniel Bechmann; Matthew Jay Budoff Journal: J Comput Assist Tomogr Date: 2009 Mar-Apr Impact factor: 1.826
Authors: Michael H Criqui; Julie O Denenberg; Joachim H Ix; Robyn L McClelland; Christina L Wassel; Dena E Rifkin; Jeffrey J Carr; Matthew J Budoff; Matthew A Allison Journal: JAMA Date: 2014-01-15 Impact factor: 56.272