Coronary Artery Calcium Volume Research Articles

Multicentre, open-label, randomised, controlled trial to compare early intervention with calcimimetics and conventional therapy in preventing coronary artery calcification in patients with secondary hyperparathyroidism (UPCOMING): a study protocol

IntroductionCoronary artery and heart valve calcification is a risk factor for cardiovascular death in haemodialysis patients, so calcification prevention should be started as early as possible. Treatment with concomitant calcimimetics...

Obstructive sleep apnea and its association with coronary artery calcium volume in asymptomatic male subjects

The aim of this study was to analyze the association between various parameters related to obstructive sleep apnea (OSA) and coronary artery calcium (CAC) volume. We retrospectively reviewed the medical records of 315 male subjects who underwent standard polysomnography (PSG) and coronary artery computed tomography. In this study, we found that only the apnea index (AI) and minimal oxygen saturation (minimal SaO2) were independently associated with CAC volume after adjustment for confounders; for a 1/h increase in the AI, the CAC volume increased by 1.311 mm3, and for a 1% increase in the minimal SaO2, the CAC volume decreased by 2.187 mm3. We also found that the CAC volume was significantly different between the habitual snorer and the severe OSA group (21.27 ± 40.79 vs 71.33 ± 175.00, p = 0.042). Moreover, the CAC volume was significantly different between the first and fourth quartile groups of the AI (32.42 ± 59.54% vs. 78.74 ± 198.50, p = 0.048), but not among groups according to the hypopnea index quartile. Therefore, we concluded that among various OSA-related PSG parameters, the AI and minimal SaO2 was independently associated with the CAC volume and significantly related to upcoming cardiovascular events in middle-aged men.

CT-derived coronary artery calcium density is affected by regional lesion distribution and image reconstruction parameters

PurposeThe prognostic relevance of coronary artery calcium (CAC) density, assessed from cardiac CT scans, is established. However, the influence of CAC distribution, volume, image reconstruction, and clinical factors on CAC density warrants further examination. MethodsIn this study, 120 patients underwent non-contrast ECG-gated cardiac CT scans using a prospectively defined CAC scoring protocol with 1-, 3-, and 5-mm thick image reconstructions, both with and without a 20% image overlap. We segmented CAC in all reconstructions and assessed the relationship between CAC density, volume, and number of detected calcifications/patient. ResultsOverall, 75/120 (63%) patients (66% men, mean age 63 ± 11 years) presented CAC across 342 segments. CAC density, CAC volume, and the number of detected calcifications decreased with increasing slice thickness (p < 0.001 for all); these effects were slightly reduced by image overlap (p < 0.001 for all). Higher CAC density correlated with greater CAC volume (ρ = 0.62; p < 0.001) and more calcified segments per person (ρ = 0.32; p = 0.006). Higher CAC density was also associated with lower patient weight (beta: -0.6, 95%CI: −1.1–-0.1, p = 0.022) and increased high-density lipoprotein (HDL) levels (beta: 0.7, 95%CI: 0.0–1.4, p = 0.046). In a multivariable analysis adjusted for clinical covariates, lower CAC density was associated with broader CAC distribution (i.e., a higher number of calcified segments at a given CAC volume; beta-coefficient: -58.9; 95%CI: −84.7 to −33.1; p < 0.001). ConclusionCAC density is significantly impacted by regional CAC distribution and image reconstruction, potentially confounding its prognostic value. Accounting for these factors may improve patient risk assessment, management, and cardiovascular health outcomes.

Photon-Counting Detector Computed Tomography Versus Energy-Integrating Detector Computed Tomography for Coronary Artery Calcium Quantitation.

Photon-counting detector (PCD) computed tomography (CT) offers improved spatial and contrast resolution, which can impact quantitative measurements. This work aims to determine in human subjects the effect of dual-source PCD-CT on the quantitation of coronary artery calcification (CAC) compared with dual-source energy-integrating detector (EID) CT in both 1- and 3-mm images. This prospective study enrolled patients receiving a clinical EID-CT CAC examination to undergo a research PCD-CT CAC examination. Axial images were reconstructed with a 512 × 512 matrix, 200-mm field of view, 3-mm section thickness/1.5-mm interval using a quantitative kernel (Qr36). Sharper kernels (Qr56/QIR strength 4 for PCD and Qr49/ADMIRE strength 5 for EID) were used to reconstruct images with 1-mm section thickness/0.5-mm interval. Pooled analysis was performed for all calcifications with nonzero values, and volume and Agatston scores were compared between EID-CT and PCD-CT. A Wilcoxon signed-rank test was performed with P < 0.05 considered statistically significant. In 21 subjects (median age, 58 years; range, 50-75 years; 13 male [62%]) with a total of 42 calcified arteries detected at 3 mm and 46 calcified arteries at 1-mm images, EID-CT CAC volume and Agatston scores were significantly lower than those of PCD-CT ( P ≤ 0.001). At 3-mm thickness, the mean (standard deviation) volume and Agatston score for EID-CT were 55.5 (63.4) mm 3 and 63.8 (76.9), respectively, and 61.5 (69.4) mm 3 and 70.4 (85.3) for PCD-CT ( P = 0.0001 and P = 0.0013). At 1-mm thickness, the mean (standard deviation) volume and score for EID-CT were 50.0 (56.3) mm 3 and 61.1 (69.3), respectively, and 59.5 (63.9) mm 3 and 72.5 (79.9) for PCD-CT ( P < 0.0001 for both). The applied radiation dose (volume CT dose index) for the PCD-CT scan was 2.1 ± 0.6 mGy, which was 13% lower than for the EID-CT scan (2.4 ± 0.7 mGy, P < 0.001). Relative to EID-CT, PCD-CT demonstrated a small but significant increase in coronary artery calcium volume and Agatston score.

Ex vivo coronary calcium volume quantification using a high-spatial-resolution clinical photon-counting-detector computed tomography.

Coronary artery calcification (CAC) is an important indicator of coronary disease. Accurate volume quantification of CAC is challenging using computed tomography (CT) due to calcium blooming, which is a consequence of limited spatial resolution. Ex vivo coronary specimens were scanned on an ultra-high-resolution (UHR) clinical photon-counting detector (PCD) CT scanner, and the accuracy of CAC volume estimation was compared with a state-of-the-art conventional energy-integrating detector (EID) CT, a previous-generation investigational PCD-CT, and micro-CT. CAC specimens () were scanned on EID-CT and PCD-CT using matched parameters (120kV, 9.3mGy ). EID-CT images were reconstructed using our institutional routine clinical protocol for CAC quantification. UHR PCD-CT data were reconstructed using a sharper kernel. An image-based denoising algorithm was applied to the PCD-CT images to achieve similar noise levels as EID-CT. Micro-CT images served as the volume reference standard. Calcification images were segmented, and their volume estimates were compared. The CT data were further compared with previous work using an investigational PCD-CT. Compared with micro-CT, CT volume estimates had a mean absolute percent error of for clinical PCD-CT, for EID-CT, and for previous-generation PCD-CT. Clinical PCD-CT absolute percent error was significantly () lower than both EID-CT and previous generation PCD-CT. The mean calcification CT number and contrast-to-noise ratio were both significantly () higher in clinical PCD-CT relative to EID-CT. UHR clinical PCD-CT showed reduced calcium blooming artifacts and further enabled improved accuracy of CAC quantification beyond that of conventional EID-CT and previous generation PCD-CT systems.

Lipoprotein(a) and coronary artery calcium in comparison with other lipid biomarkers: The multi-ethnic study of atherosclerosis

Coronary artery calcium (CAC) scoring is often used for atherosclerotic cardiovascular disease (ASCVD) risk stratification in individuals with elevated lipoprotein(a) [Lp(a)]. To evaluate associations between Lp(a) and baseline CAC (volume/density) and CAC progression compared to other lipid biomarkers. We utilized data from the Multi-Ethnic Study of Atherosclerosis (MESA), a cohort study of individuals without clinical ASCVD, excluding statin users. We evaluated the associations between Lp(a), low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), triglycerides, total cholesterol, apolipoprotein B, and non-HDL-C with baseline CAC and annual CAC progression using multivariable ordinal regression with adjustment for ASCVD risk factors. Analyses were also stratified by median age. In 5,597 participants (2,726 at median 9.5-year follow-up), Lp(a) was not associated with baseline CAC volume or density and was modestly associated with volume progression (OR 1.11, 95% CI 1.03-1.21). However, other biomarkers were positively associated with baseline volume and volume progression (LDL-C: OR 1.26, 95% CI: 1.19-1.33 and OR 1.22, 95% CI: 1.15-1.30, respectively), except HDL-C which was inversely associated. LDL-C, total cholesterol and non-HDL-C were inversely associated with baseline density. In participants <62 years of age, Lp(a) was modestly associated with baseline CAC volume (OR 1.10, 95% CI: 1.00-1.20) and volume progression (OR 1.16 95% CI: 1.04-1.30). In contrast to other lipid biomarkers, Lp(a) was not associated with baseline CAC volume or density and was only modestly associated with volume progression. Our findings suggest that Lp(a) is not as robustly associated with CAC as other lipid biomarkers.

Abstract P667: Association of Number of Calcified Coronary Arteries and Cardiovascular Outcomes Stratified by Calcification Volume: The Multi-Ethnic Study of Atherosclerosis (MESA)

Background: Coronary artery calcium (CAC) is a risk factor for atherosclerotic cardiovascular disease (ASCVD). Data suggests number of vessels with CAC independently improves risk prediction but impact by CAC volume remains unknown. Methods: Using data from 3256 MESA participants with CAC&gt;0 and clinical follow-up, we evaluated the association between number of arteries with CAC and risk for coronary heart disease (CHD), myocardial infarction (MI), and CVD events stratified by CAC volume (above/below median) using multivariable-adjusted Cox proportional hazards models. Results: Mean age was 63.3 years (SD 9.5) with 1363 (41.9%) women. There were 1079 (33%) with single-vessel, 822 (25%) with 2-vessel, and 1355 (42%) with 3-4 vessel CAC. Median CAC volume was 84.7 [IQR 24.5, 267.2] mm 3 . CAC in 3-4 vessels was independently associated with higher CHD risk ( Figure ) compared to 1-vessel (HR 2.01, 95% CI 1.1-3.6; p=0.018) and 2-vessels (HR 1.69, 95% CI 1.0-2.8; p=0.04) for lower CAC volumes, with similar findings for MI and CVD outcomes ( Table ). Conclusions: Number of arteries with CAC independently increases risk for ASCVD events only for those with lower CAC volumes.

Coronary Artery Calcium Density and Cardiovascular Events by Volume Level: The MESA.

The Agatston coronary artery calcium (CAC) score provides robust cardiovascular disease risk prediction but upweights plaque area by a density factor. Density, however, has been shown to be inversely associated with events. Using CAC volume and density separately improves risk prediction, but it is unclear how to apply this method clinically. We aimed to evaluate the association between CAC density and cardiovascular disease across the spectrum of CAC volume to better understand how to incorporate these metrics into a single score. We performed an analysis of MESA (Multi-Ethnic Study of Atherosclerosis) participants with detectable CAC to evaluate the association between CAC density and events by level of CAC volume using multivariable Cox regression models. In a cohort of 3316 participants, there was a significant interaction (P<0.001) between CAC volume and density for coronary heart disease (CHD) risk (myocardial infarction, CHD death, resuscitated cardiac arrest). Models using CAC volume and density resulted in improvement in the C-index (0.703, SE 0.012 versus 0.687, SE 0.013) and a significant net reclassification improvement (0.208 [95% CI, 0.102-0.306]) compared with the Agatston score for CHD risk prediction. Density was significantly associated with lower CHD risk at volumes ≤130 mm3 (hazard ratio, 0.57 per unit of density [95% CI, 0.43-0.75]), but the inverse association at volumes >130 mm3 was not significant (hazard ratio, 0.82 per unit of density [95% CI, 0.55-1.22]). The lower risk for CHD associated with higher CAC density varied by level of volume, and volume ≤130 mm3 is a potentially clinically useful cut point. Further study is needed to integrate these findings into a unified CAC scoring method.

Intra-individual comparison of coronary calcium scoring between photon counting detector- and energy integrating detector-CT: Effects on risk reclassification.

To compare coronary artery calcium volume and score (CACS) between photon-counting detector (PCD) and conventional energy integrating detector (EID) computed tomography (CT) in a phantom and prospective patient study. A commercially available CACS phantom was scanned with a standard CACS protocol (120 kVp, slice thickness/increment 3/1.5 mm, and a quantitative Qr36 kernel), with filtered back projection on the EID-CT, and with monoenergetic reconstruction at 70 keV and quantum iterative reconstruction off on the PCD-CT. The same settings were used to prospectively acquire data in patients (n = 23, 65 ± 12.1 years), who underwent PCD- and EID-CT scans with a median of 5.5 (3.0-12.5) days between the two scans in the period from August 2021 to March 2022. CACS was quantified using a commercially available software solution. A regression formula was obtained from the aforementioned comparison and applied to simulate risk reclassification in a pre-existing cohort of 514 patients who underwent a cardiac EID-CT between January and December 2021. Based on the phantom experiment, CACS PCD-CT showed a more accurate measurement of the reference CAC volumes (overestimation of physical volumes: PCD-CT 66.1 ± 1.6% vs. EID-CT: 77.2 ± 0.5%). CACS EID-CT and CACS PCD-CT were strongly correlated, however, the latter measured significantly lower values in the phantom (CACS PCD-CT : 60.5 (30.2-170.3) vs CACS EID-CT 74.7 (34.6-180.8), p = 0.0015, r = 0.99, mean bias -9.7, Limits of Agreement (LoA) -36.6/17.3) and in patients (non-significant) (CACS PCD-CT : 174.3 (11.1-872.7) vs CACS EID-CT 218.2 (18.5-876.4), p = 0.10, r = 0.94, mean bias -41.1, LoA -315.3/232.5). The systematic lower measurements of Agatston score on PCD-CT system led to reclassification of 5.25% of our simulated patient cohort to a lower classification class. CACS PCD-CT is feasible and correlates strongly with CACS EID-CT , however, leads to lower CACS values. PCD-CT may provide results that are more accurate for CACS than EID-CT.

High- vs. Low-Intensity Statin Therapy and Changes in Coronary Artery Calcification Density after One Year.

Statin therapy promotes the progression of coronary artery calcification (CAC). Comparing patients on high (HIST) vs. low-to-intermediate intensity statin therapy (LIST), randomized controlled trials with a one-year follow-up failed to document a relevant difference in the Agatston score and CAC volume. We evaluated whether statin intensity modifies CAC density at one year. We performed a pooled analysis of two randomized-controlled trials (BELLES, EBEAT), comparing the effects of HIST (Atorvastatin 80 mg) vs. LIST (Pravastatin 40 mg, Atorvastatin 10 mg) on CAC measures after one year. The differences in CAC density and its change were compared using the two-sided t-test. Data from 852 patients (66.7% female) with available baseline and follow-up CT were evaluated from both trials. HIST vs. LIST more effectively reduced LDL-cholesterol (annualized change: -45.8 ± 38.5 vs. -72.9 ± 46.0 mg/dL, p &lt; 0.001). Mean CAC density increased from 228.8 ± 35.4 HU to 232.6 ± 37.0 HU (p &lt; 0.0001) at one-year follow-up. Comparing patients on HIST vs. LIST, CAC density at follow-up (HIST: 231.9 ± 36.1 HU vs. LIST: 233.3 ± 37.7 HU, p = 0.59) and its change from baseline (HIST: 4.0 ± 19.1 HU vs. LIST: 3.6 ± 19.6 HU, p = 0.73) did not differ. Subgroup analyses, stratifying by LDL reduction (&lt;median: 2.0 ± 24.3 HU, ≥median: 3.6 ± 21.9 HU, p = 0.34), Agatston score at baseline (&lt;100: 2.6 ± 22.5 HU vs. 3.2 ± 25.6 HU, p = 0.82; ≥100: 4.8 ± 17.0 HU vs. 3.8 ± 16.6 HU, p = 0.44, for HIST vs. LIST; respectively), and equal number of lesions in both CT scans (3.7 ± 20.3 HU vs. 7.0 ± 22.2 HU, p = 0.24) showed similar results. HIST vs. LIST leads to a higher reduction in cholesterol levels, which does not translate into relevant differences in the change of CAC density at one-year follow-up.

Development and validation of a nonenhanced CT based radiomics model to detect brown adipose tissue.

Purpose: It has been reported that brown adipose tissue (BAT) has a protective effect regarding cardiovascular disease. Positron emission tomography-computed tomography (PET-CT) is the reference method for detecting active BAT; however, it is not feasible to screen for BAT due to the required radionuclides and high-cost. The purpose of this study is to develop and validate a nonenhanced CT based radiomics model to detect BAT and to explore the relationship between CT radiomics derived BAT and cardiovascular calcification. Patients and methods: 146 patients undergoing 18F-FDG PET-CT were retrospectively included from two centers for model development (n = 86) and external validation (n = 60). The data for the model development were randomly divided into a training cohort and an internal validation cohort with a 7:3 ratio, while the external validation data were divided 1:1 into a propensity score matching (PSM) cohort and a randomly sex matched cohort. Radiomics features of BAT and non-BAT depots were extracted from regions of interest (ROI) on nonenhanced CT corresponding to PET studies. Inter-class correlation coefficient (ICC) and Pearson's correlation analysis were performed to select radiomics features with high consistency. Next, least absolute shrinkage and selection operator (LASSO) with linear regression model was used to select radiomics features for model construction. Support vector machine (SVM) was used to develop the model and a radiomics score (RS) was calculated for each depot. The diagnostic performance of the radiomics model was evaluated both on a per-depot and per-patient basis by calculating the area under the receiver operating characteristic curve (AUROC). We further divided patients into BAT-RS group and non-BAT-RS group based on radiomics score and compared their cardiovascular calcification by calculating calcium volume and score. Results: A total of 22 radiomics features were selected for model construction. On a per-depot basis, the AUROCs were 0.87 (95% CI: 0.83-0.9), 0.85 (95% CI: 0.79-0.90), 0.72 (95% CI: 0.67-0.77) and 0.74 (95% CI: 0.69-0.79) for detecting BAT in the training, internal validation, external validation 1 and external validation 2 cohorts, respectively. On a per-patient basis, the radiomics model had high AUROCs of 0.91 (95% CI: 0.84-0.98), 0.77 (95% CI: 0.61-0.92) and 0.85 (95% CI: 0.72-0.98) in the training, external validation 1 and external validation 2 cohorts, respectively. When grouping based on the radiomics model, the BAT-RS group had lower odds of coronary artery calcium (CAC) and thoracic aorta calcium (TAC) compared with the non-BAT-RS group (CAC: 2.8% vs. 20.3%, p = 0.001; TAC: 19.4% vs. 39.2%, p = 0.009). The BAT-RS group had less CAC volume (4.1 ± 4.0 mm3 vs. 147.4 ± 274.3 mm3; p = 0.001), CAC score (2.8 ± 3.0 vs. 169.1 ± 311.5; p = 0.001), TAC volume (301.4 ± 450.2 mm3 vs. 635.3 ± 1100.7 mm3; p = 0.007) and TAC score (496.2 ± 132.6 vs. 749.2 ± 1297.3; p = 0.007) than the non-BAT-RS group. Conclusion: We developed and validated a nonenhanced CT based reliable radiomics model for detecting BAT with PET-CT findings as reference standard. Radiomics signatures from nonenhanced CT can reliably detect BAT and have promising potential to be used in routine clinical settings. Importantly, our study showed that patients with BAT had less cardiovascular calcification.

Impact of deep learning image reconstructions (DLIR) on coronary artery calcium quantification

BackgroundDeep learning image reconstructions (DLIR) have been recently introduced as an alternative to filtered back projection (FBP) and iterative reconstruction (IR) algorithms for computed tomography (CT) image reconstruction. The aim of this study was to evaluate the effect of DLIR on image quality and quantification of coronary artery calcium (CAC) in comparison to FBP.MethodsOne hundred patients were consecutively enrolled. Image quality–associated variables (noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR)) as well as CAC-derived parameters (Agatston score, mass, and volume) were calculated from images reconstructed by using FBP and three different strengths of DLIR (low (DLIR_L), medium (DLIR_M), and high (DLIR_H)). Patients were stratified into 4 risk categories according to the Coronary Artery Calcium - Data and Reporting System (CAC-DRS) classification: 0 Agatston score (very low risk), 1–99 Agatston score (mildly increased risk), Agatston 100–299 (moderately increased risk), and ≥ 300 Agatston score (moderately-to-severely increased risk).ResultsIn comparison to standard FBP, increasing strength of DLIR was associated with a significant and progressive decrease of image noise (p < 0.001) alongside a significant and progressive increase of both SNR and CNR (p < 0.001). The use of incremental levels of DLIR was associated with a significant decrease of Agatston CAC score and CAC volume (p < 0.001), while mass score remained unchanged when compared to FBP (p = 0.232). The underestimation of Agatston CAC led to a CAC-DRS misclassification rate of 8%.ConclusionDLIR systematically underestimates Agatston CAC score. Therefore, DLIR should be used cautiously for cardiovascular risk assessment.Key Points• In coronary artery calcium imaging, the implementation of deep learning image reconstructions improves image quality, by decreasing the level of image noise.• Deep learning image reconstructions systematically underestimate Agatston coronary artery calcium score.• Deep learning image reconstructions should be used cautiously in clinical routine to measure Agatston coronary artery calcium score for cardiovascular risk assessment.

Abstract 9971: Distribution of Coronary Artery Calcium and Risk for Cardiovascular Disease: The Multi-Ethnic Study of Atherosclerosis

Introduction: We tested the hypothesis that specific arteries with coronary artery calcium (CAC) would be associated with higher risk for incident cardiovascular disease (CVD) outcomes, even after accounting for traditional risk factors, and that adding this metric to current risk scores would improve event prediction. Methods: We analyzed data from 3,255 MESA participants with baseline CAC and event follow-up. Cox proportional hazards models assessed the independent associations between CAC presence in each of the main coronary arteries and incident myocardial infarction (MI), hard coronary artery disease (CHD), and hard CVD, adjusting for the ASCVD risk score and CAC volume and density. Area under the receiver operating characteristic curve (AUC) analyses assessed for risk discrimination by adding CAC distribution to existing risk models. Results: At baseline [mean age 66 years (SD 9.6); 1,893 female (58%)], 2,909 (89%) participants had CAC in the left anterior descending (LAD), 1,871 (58%) in the left circumflex (LCx), 1,691 (52%) in the right coronary artery (RCA), and 693 (21%) in the left main (LM). Over a median of 15.5 years, 275 developed MI, 408 CHD, and 598 CVD. After adjustment for the ASCVD risk score and CAC volume and density, only the RCA remained significant for MI and CHD, and was borderline for CVD (Table). AUC increased after adding RCA CAC presence to the ASCVD risk score for MI (0.5992 to 0.6660; 95% CI 0.031-0.102) and CHD (0.6483 to 0.6818; 95% CI, 0.003-0.064), but not for CVD, and there was no significant increase for any endpoints when added to models accounting for CAC volume and density. Conclusion: Prevalent CAC was most common in the LAD, followed by the LCx and RCA. Accounting for risk factors and CAC measures, the RCA was the only artery independently associated with additional MI and CHD risk. Moreover, MI and CHD risk prediction were improved with the addition of CAC distribution to the ASCVD score but not when also accounting for CAC volume and density.

Abstract 9969: Number of Calcified Coronary Arteries and Prediction of Cardiovascular Outcomes: The Multi-Ethnic Study of Atherosclerosis

Introduction: Current coronary artery calcium (CAC) scoring methods do not account for the number of vessels affected. We assessed the hypothesis that the number of vessels with CAC would be associated with higher risk for incident cardiovascular disease (CVD) outcomes, even after accounting for traditional risk factors, and that adding this metric to current risk scores would improve event prediction. Methods: We analyzed data from 3,255 MESA participants with baseline CAC and event follow-up. Cox proportional hazard regression analyses evaluated the association between number of affected vessels and incident myocardial infarction (MI), hard coronary artery disease (CHD), and hard CVD, adjusting for the ASCVD score and CAC volume and density. Area under the receiver operator curves (AUC) assessed event discrimination by adding number of vessels with CAC to current risk models. Results: At baseline [mean age 66 years (SD 9.6); 1,893 female (58%)], 1,086 participants (33%) had CAC in 1 vessel, 832 in 2 (26%), 987 in 3 (30%), and 385 in 4 (12%). Over a median of 15.5 years, 275 developed MI, 408 CHD, and 598 CVD. Multivariable-adjusted risk was higher with CAC in 3-4 vs 1 vessel for all outcomes (Table) and with 3-4 vs 2-vessels for CHD and CVD (HR 1.36, 95% CI 1.0-1.8 and HR 1.30, 95% CI 1.0-1.6). AUC increased after adding the number of vessels with CAC to the ASCVD score for MI (0.5992 to 0.6645, p=0.002), but not for CHD or CVD, and there was no significant increase for any endpoint when added to models already accounting for CAC volume and density. Conclusions: In a cohort free of baseline CVD, CAC had similar prevalence in 1, 2, and 3 vessels. After accounting for the ASCVD score and CAC volume and density, CAC in 3-4 vessels still conferred a significantly higher risk for adverse CVD outcomes compared to CAC in 1-2 vessels. Moreover, MI risk prediction was improved with adding the number of vessels with CAC to the ASCVD score, but not when also accounting for CAC volume and density.

Abstract 14174: Abnormal Exercise Electrocardiography With Normal Stress Echocardiography is Associated With Increased Subclinical Coronary Atherosclerosis: Insights From the Project Baseline Health Study

Introduction Patients with an abnormal (positive) exercise electrocardiography (ECG), but normal stress echocardiography (+ECG/-Echo) have more adverse cardiac events than patients with a negative ECG and normal stress Echo (-ECG/-Echo). However, it is unclear if ECG/Echo discordance is associated with a greater burden of concurrent subclinical coronary atherosclerosis. Methods In the Project Baseline Health Study (PBHS), participants underwent stress Echo and a coronary artery calcium (CAC) scan. For this PBHS substudy, participants with no known coronary artery disease (CAD) were analyzed by stress result: -ECG/-Echo, +ECG/-Echo, or +Echo (with or without +ECG). Patients with a submaximal stress test, uninterpretable ECG, resting wall motion abnormality, and/or baseline ejection fraction &lt;50% were excluded. Clinical characteristics, exercise performance, and CAC results were compared between the -ECG/-Echo and +ECG/-Echo groups using the chi-squared test and Student’s t-test for categorical and continuous variables, respectively. ANOVA or Kruskal-Wallis test was used, as appropriate, to compare all 3 groups. Results Among 1466 participants, 1357 (92.6%) had a -ECG/-Echo; 85 (5.8%) had a +ECG/-Echo; and 24 (1.6%) had a +Echo. Compared to the -ECG/-Echo group, participants in the +ECG/-Echo group were older with shorter exercise duration, but younger with fewer risk factors than participants with a +Echo. The median 10-year ASCVD risk score was 2% for -ECG/-Echo, 3% for +ECG/-Echo, and 10% for +Echo (p&lt;0.001). Greater abnormalities by exercise stress Echo were associated with an increased burden of concurrent coronary atherosclerosis as assessed by CAC score and CAC volume (Table). Conclusions Individuals with positive exercise ECG, even with normal stress Echo, have a higher burden of subclinical coronary atherosclerosis than those with -ECG/-Echo, which may explain the increased risk for adverse cardiac events in the +ECG/-Echo population.

Density of Calcified Coronary Artery Plaque and Risk of Incident Atrial Fibrillation (from the Multiethnic Study of Atherosclerosis)

Elevated coronary artery calcium (CAC) score, as assessed by the Agatston method, is associated with incident atrial fibrillation (AF). We aimed to evaluate the associations of CAC volume and density with incident AF. Participants from the Multiethnic Study of Atherosclerosis without baseline AF and CAC &amp;amp;gt;0 were included. The associations between baseline and progression (average annual change) of CAC measures and incident AF were evaluated using Cox proportional hazards models. CAC volume and Agatston scores were natural log (ln)-transformed, and hazard ratios (HRs) were calculated per standard deviation increment. The baseline analysis included 3,332 participants; 2,643 were included in the progression analysis. In multivariable models adjusted for cardiovascular risk factors, volume (HR 1.24, 95% confidence interval [CI] 1.14 to 1.36), density (HR 1.14, 95% CI 1.05 to 1.25), and Agatston score (HR 1.24, 95% CI 1.14 to 1.35) were associated with increased risk of incident AF. In models including both volume and density, the magnitude of association between volume and incident AF was unchanged, whereas the density association was eliminated (HR 0.99, 95% CI 0.89 to 1.11). Median time to follow-up CAC assessment was 1.9 (interquartile range 1.3, 3.0) years. Similar results were observed for the association of incident AF with annual change in volume and Agatston score. CAC volume, but not density, is associated with risk for incident AF when adjusting for both. In conclusion, our findings suggest that, although CAC may be a risk marker for AF, the association between CAC and AF appears to be independent of plaque density.

523 Association Between Coronary Artery Calcium And Calcified Plaque Volume And Their Ability To Predict Obstructive Coronary Artery Disease: Clarify Registry

Introduction: Agatston coronary artery calcium (CAC) score is a strong predictor of cardiovascular mortality. However, the relationship between CAC and calcified plaque volume (CPV), which is measured on coronary computed tomography angiography (CCTA) is not well understood. Furthermore, it is unknown whether there is a difference between CAC and CPV in predicting the obstructive CAD.

Association of Coronary Events with Burden and Distribution of Coronary Artery Calcification: Results from the Multi-Ethnic Study of Atherosclerosis

<h3>Lead Author's Financial Disclosures</h3> Nothing to disclose. <h3>Study Funding</h3> None. <h3>Background/Synopsis</h3> Coronary artery calcium (CAC), even when mild, is associated with increased risk for coronary heart disease (CHD) events. <h3>Objective/Purpose</h3> We sought to characterize the association between number of vessels with CAC and specific artery involvement with incident CHD. <h3>Methods</h3> We evaluated participants with baseline CAC >0, free of cardiovascular disease (CVD), and follow-up from the Multi-Ethnic Study of Atherosclerosis (MESA) Exam 1 visit until adjudicated CHD, death, or censoring date of December 31st, 2018. We used Cox proportional hazard regression analyses to characterize incident CHD by number of vessels with CAC and specific artery involvement with sequential multivariable models adjusting for ASCVD risk score, body mass index, and log-transformed total calcification volume. <h3>Results</h3> There were 3,290 participants (mean age, 66 years; 42% female) with baseline CAC >0. Among these, 33% had CAC >0 in only 1 artery, 25% in 2 arteries, 30% in 3 arteries, and 12% in all 4 coronary arteries. Of those with single-vessel involvement, CAC was most frequently in the left anterior descending artery (LAD) (75%), followed by the right coronary artery (RCA) (12%), left circumflex (LCx) (10%), and left main (LM) (3%). Over follow-up of 18.5 years, 589 participants (18%) developed CHD with a mean time to event of 12.6 years. In the multivariable- adjusted Cox model, CHD risk was 1.7x higher for 3- vs 1- (95% CI 1.2-2.3, p=0.002) and 1.6x higher for 3- vs 2-vessel involvement (95% CI 1.2-2.0, p=0.0004), though similar for 1- vs 2- (p=0.7) and 3- vs 4 (p=0.8) [Figure]. Single-vessel CAC in the LAD conferred a similar risk for CHD when compared to single-vessel CAC in the LM (p=0.66), LCx (p=0.83), and RCA (p=0.31). <h3>Conclusions</h3> Subclinical coronary artery disease was most commonly in 1, 2, and 3 number of arteries, and most frequently included the LAD. Compared with having CAC in only 1 to 2 arteries, those with CAC in 3 to 4 arteries had a 60-70% higher risk of incident CHD. In the context of the multivariable-adjusted model accounting for total CAC volume, no specific artery conferred a higher CHD risk than others. Number of vessels with CAC but not specific artery distribution were important characteristics for individualized risk stratification.

99-OR: HbA1c Variability Predicts Both Coronary Atherosclerosis and CVD Events in Type 1 Diabetes

Introduction: Interventions that decrease mean glucose have reduced rates of type 1 diabetes (T1D) vascular complications, but the difference in cardiovascular disease (CVD) risk between people with T1D and the general population endures. This suggests that factors beyond hemoglobin A1c (HbA1c) normalization may drive T1D CVD outcomes. HbA1c variability is an established predictor of T1D microvascular disease, but thus far only the FinnDiane Study has implicated it as a risk factor for T1D CVD events. No studies have examined the relationship of HbA1c variability to both CVD risk factors and events in a prospective T1D cohort. Methods: We used multivariable logistic regression to analyze the Coronary Artery Calcification in Type 1 Diabetes (CACTI) T1D cohort (N=597) . Primary outcomes were square root-transformed coronary artery calcium (CAC) volume and CVD events. CVD events were defined as myocardial infarction, coronary artery bypass grafting, angioplasty, or cardiovascular death. HbA1c variability was defined as a 1-standard deviation increment in HbA1c and calculated as standard deviation of all HbA1c values for each subject. Results: After adjustment for age, sex, and T1D duration, HbA1c variability predicted both CVD events (HR: 1.562, 95% CI: 1.052-2.318, P=0.0269) and CAC volume (rpartial= 0.3346, P&amp;lt;0.001) , while mean HbA1c predicted CVD events (HR: 1.399, 95% CI: 1.079-1.816, P=0.0114) but not CAC volume (rpartial= 0.0934, P=0.2886) . Further investigation revealed that the relationship between HbA1c variability and CVD events was strongest in those with good glycemic control (HR: 6.330 at mean HbA1c of 6.0%, HR: 3.920 at mean HbA1c of 7.0%, HR: 2.428 at mean HbA1c of 8.0%, HR: 1.5at mean HbA1c of 9.0%, and HR: 0.931 at mean HbA1c of 10.0%) . Conclusion: HbA1c variability may be a risk factor for both coronary atherosclerosis and CVD events in T1D, and the appropriate care strategy for this population may include maintaining an HbA1c value over time that is both at-target and stable. Disclosure W.B.Horton: None. J.K.Snell-bergeon: Stock/Shareholder; GlaxoSmithKline plc. Funding National Institutes of Health (R01DK116731) National Institutes of Health (R01HL113029)

Coronary artery calcium and cardiovascular disease prediction by scanner type: the multi-ethnic study of atherosclerosis

To evaluate the predictive value of coronary artery calcium (CAC) scoring methods across cardiac computed tomography (CT) scanner types. CAC was measured in participants from the MESA (Multi-Ethnic Study of Atherosclerosis), a prospective cohort study of participants free of baseline cardiovascular disease (CVD), using either EBCT (electron beam CT) or MDCT (multidetector CT). The risks for incident coronary heart disease (CHD) and CVD events were compared for CAC scores per SD using Cox proportional hazards models with multivariable adjustment in 3,362 MESA participants with detectable CAC. Using the Agatston score, the hazard ratio (HR) and 95% confidence interval (CI) for CHD was 1.50 (1.27,1.78) for EBCT and 1.60 (1.37,1.87) for MDCT. Using volume and density scores, the HR for CHD was 2.14 (1.71,2.68) for volume and 0.61 (0.48,0.76) for density on EBCT and 1.73 (1.42,2.11) for volume and 0.88 (0.71,1.10) for density on MDCT. Similar results were seen for CVD risk and in analyses stratified by sex, body mass index (BMI), and age. The volume and density score model demonstrated higher areas under the curve (AUC) for CHD than the Agatston score with EBCT (0.702, 95% CI: 0.666,0.738 versus 0.677, 95% CI: 0.638,0.715, p<0.001) and MDCT (0.669, 95% CI: 0.632,0.705 versus 0.660, 95% CI: 0.622,0.697, p=0.216). The CAC volume and density scores provide better risk prediction than the Agatston score for CHD and CVD events, regardless of CT scanner type. CAC density was strongly and inversely associated with CHD risk. Both density and volume score prediction were stronger for EBCT than MDCT.