Quantification Of Coronary Artery Calcium Research Articles

Adaptive Iterative Dose Reduction 3D Integrated with Automatic Tube Current Modulation for CT Coronary Artery Calcium Quantification: Comparison to Traditional Filtered Back Projection in an Anthropomorphic Phantom and Patients

We aimed to evaluate integrated adaptive iterative dose reduction 3D (AIDR 3D) algorithm in automatic tube current modulation (ATCM) for the quantification of coronary artery calcium score (CACS) and cardiac risk stratification. A thoracic phantom with calcium inserts of known densities was scanned with filtered back projection (FBP) and AIDR 3D algorithms in small- and medium-sized phantoms. Twenty-four patients underwent two consecutive scans of CACS with FBP and AIDR 3D algorithms. The absolute Agatston score, Agatston score risk, volume score, and Agatston score percentile-based risk were compared, and concordance coefficients and agreement plots were made. Agatston and volume scores were significantly different between the phantom sizes (P < .01). There were no significant differences in the Agatston scores between FBP and AIDR 3D for the medium phantoms (P = .25). In the patients, there were no significant differences in Agatston and volume scores between FBP and AIDR 3D (P = .06 and P = .09, respectively). The correlation coefficients of Agatston and volume scores with AIDR 3D were excellent compared to those of FBP. There were no significant differences in Agatston score risk and Agatston score percentile-based risk between FBP and AIDR 3D (P = .74 and P = 1, respectively). There was mean dose reduction of 57.8% ± 18.6% for AIDR 3D. The absolute Agatston score differed between FBP and AIDR 3D reconstructions. However, the cardiac risk categorizations of the two methods were comparable. An integrated AIDR 3D algorithm with automatic tube current modulation enables radiation dose savings at a consistent noise level without sacrificing CACS.

Coronary artery calcium quantification on first, second and third generation dual source CT: A comparison study

BackgroundDifferences in coronary artery calcium (CAC) quantification of successive CT systems of one vendor could impact results of CAC screening and progression studies. The purpose of this study is to compare CAC quantification between three generations of dual-source computed tomography (DSCT) systems. MethodsThree DSCT generations were used to repeatedly scan an anthropomorphic chest phantom and three inserts. The first and second insert contained 100 small and nine large calcifications, respectively, to determine detectability, and the Agatston and (calibrated) mass score, respectively. A third insert containing a moving artificial coronary artery was used to determine impact of movement on calcium scoring. Data were acquired at 120 kVp, 90 reference mAs with prospective electrocardiographic(ECG)-gating at sequential and high-pitch spiral mode, for respectively first and second/third generation DSCT. Differences and variability in detectability and calcium scores were analyzed. ResultsAlthough noise levels differed (p=<0.002), no differences in detectability were found between the three DSCT generations; median (range) for first, second and third generation were 11 (8), 11 (4) and 12 (2) out of 100 calcifications (p > 0.272). Between second and third generation no difference was found in Agatston score for the large calcification phantom (p > 0.05). The intra-scanner variability and inter-scanner median relative difference ranged for Agatston score from 2.1 to 8.3% and 0.5–12.7% and for mass score from 1.4% to 4.4% and 0.7–5.6%. Overall, intra-scanner variability was lowest for third generation DSCT. ConclusionThe three DSCT generations have similar detectability of calcifications. Median Agatston and mass score differed by no more than 12.7% and 5.6%.

Iterative beam-hardening correction with advanced modeled iterative reconstruction in low voltage CT coronary calcium scoring with tin filtration: Impact on coronary artery calcium quantification and image quality

ObjectiveWe investigated the impact of iterative beam-hardening correction (IBHC) with advanced modeled iterative reconstruction (ADMIRE) of ultra-low radiation-dose tin filtered (Sn100 kVp) CACS acquisitions on image quality, calcium quantification, and risk classification. MethodsCT data of 60 patients (55% male, age 62.3 ± 9.8years) who underwent a 3rd generation dual-source CACS scan using a prospectively ECG-triggered 100 kVp sequential acquisition protocol with tin filtration (Sn100 kVp) were reconstructed using IBHC with filtered back projection (FBP) and ADMIRE with strength levels of three and five. Image noise was calculated and Agatston scores were derived from all reconstructions. Image noise, Agatston score categories, and percentile-based cardiac risk categorization of the respective reconstruction techniques were compared. ResultsThe mean estimated radiation dose equivalent of CACS acquisitions in the study population was 0.20 ± 0.07 mSv. Mean image noise significantly decreased with ADMIRE compared to FBP (both p < 0.0001). Agatston scores derived from the respective reconstructions were significantly different in a paired comparison (median [25th and 75th percentile]): FBP 34.7 [1.9, 153.6], ADMIRE 3 28.6 [1.1, 134.5], ADMIRE 5 22.7 [0.3, 116.8]; both p < 0.0001). Agatston score categories and cardiac risk categorization showed excellent agreement of ADMIRE 3 and ADMIRE 5 with FBP (ĸ = 0.92 [0.86–0.98] and ĸ = 0.86 [0.79–0.94]; ĸ = 0.94 [0.87–1.00] and ĸ = 0.91 [0.83–0.99]; however, modest cardiac risk reclassifications of 3% and 7% for ADMIRE 3 and ADMIRE 5, respectively, were observed. ConclusionIterative reconstruction using IBHC ADMIRE in low voltage, ultra-low dose CACS with tin filtration significantly decreased image noise. However, it also reduced Agatston scores compared to FBP, which may have an impact on subsequent cardiac risk classification, although risk reclassification occurred only in a modest number of subjects.

Achilles tendon xanthomas are associated with the presence and burden of subclinical coronary atherosclerosis in heterozygous familial hypercholesterolemia: A pilot study

Background and aimsAchilles tendon xanthomas (ATX) are a sign of long-term exposure to high blood cholesterol in familial hypercholesterolemia (FH) patients, which have been associated with cardiovascular disease. We evaluated the ATX association with the presence and extent of subclinical coronary atherosclerosis in heterozygous FH patients. Methods102 FH patients diagnosed by US-MEDPED criteria (67% with genetically proven FH), with median LDL-C 279 mg/dL (interquartile range: 240; 313), asymptomatic for cardiovascular disease, underwent computed tomography angiography and coronary artery calcium (CAC) quantification. Subclinical coronary atherosclerosis was quantified by CAC, segment-stenosis (SSS) and segment-involvement (SIS) scores. Adjusted Poisson regression was used to assess the association of ATX with subclinical atherosclerosis burden as continuous variables. ResultsPatients with ATX (n = 21, 21%) had higher LDL-C and lipoprotein(a) [Lp(a)] concentrations as well as greater CAC scores, SIS and SSS (p < 0.05). After adjusting for age, sex, smoking, hypertension, previous statin use, HDL-C, LDL-C and Lp(a) concentrations, there was an independent positive association of ATX presence with CAC scores (β = 1.017, p < 0.001), SSS (β = 0.809, p < 0.001) and SIS (β = 0.640, p < 0.001). ConclusionsATX are independently associated with the extension of subclinical coronary atherosclerosis quantified by tomographic scores in FH patients.

Relationship between cardiac calcification and left ventricular hypertrophy in patients with chronic kidney disease at hemodialysis initiation.

Coronary artery calcification (CAC), cardiac valve calcification (CVC) and left ventricular hypertrophy (LVH) are frequently observed in chronic kidney disease (CKD) patients. These abnormalities significantly affect morbidity and mortality. The aim of this study was to investigate the relationship between CAC, CVC and LVH in CKD patients. This study included 96 patients who were hospitalized and initiated hemodialysis between December 2011 and July 2014 at our five institutions. Multi-detector computed tomography for the quantification of CAC using the Agatston score and transthoracic echocardiography for assessing CVC and LVH were performed for all patients included in the study. We semi-quantitatively evaluated the severity of CVC as a valvular calcification score. We also assessed the presence of LVH in patients with CAC and/or CVC. Among the 96 patients, the prevalence of CAC was 81.3% and CVC was 65.0%. The severity of CAC was closely and significantly associated with that of CVC. The percentage of patients with LVH was the greatest in those with both severe CAC and CVC. CAC was significantly more severe in patients with concentric hypertrophy compared to those with normal geometry. At the initiation of hemodialysis, most CKD patients had CAC, CVC and LVH. In addition, cardiac calcification was significantly associated with LVH in these patients.

Impact of Advanced Modeled Iterative Reconstruction on Coronary Artery Calcium Quantification

To evaluate the influence of advanced modeled iterative reconstruction (ADMIRE) on the coronary artery calcium (CAC) scores by computed tomography (CT). Sixty patients underwent CAC imaging with dual-source 192-slice CT. Agatston, volume and mass score were calculated from filtered back projection (FBP) and iterative reconstructions with different levels of ADMIRE. Friedman test and Wilcoxon rank sum test were used for multiple comparisons of CAC values and the difference ratio among different ADMIRE groups using FBP as reference. The median Agatston score (range) using FBP was 115 (0.1-3047) and significantly decreased with incremental ADMIRE levels 1-5: 96 (0.1-2813), 91 (0-2764), 87 (0-2699), 80 (0-2590), 70 (0-2440); all P < 0.001. In comparison with FBP Agatston, volume and mass scores significantly decreased with increasing ADMIRE levels 1-5 (P < 0.001): from -12% to -39%, from -14% to -41%, and from -13% to -40%, respectively. In four patients with low calcium burden, the use of ADMIRE 2 or higher resulted in the disappearance of calcium that was detectable using FBP or ADMIRE 1. The decrease of CAC in high-level ADMIRE resulted in a reassignment to a lower Agatston risk group in 27%. ADMIRE causes a substantial reduction of the CAC scores measured by cardiac CT, which leads to an underestimation of cardiovascular risk scores in some patients.

CT calcium scoring. History, current status and outlook.

Cardiovascular risk assessment has assumed a prominent role in the course of preventive care of all adults. Traditionally cardiovascular risk assessment has been performed using risk factors including gender, age, smoking history, lipid status, diabetes status, and family history. Increasingly, imaging has been deployed to directly detect coronary atherosclerotic disease. Quantification of coronary calcium (e.g., Agatston method, calcium mass and volume) is readily detected using helical CT scanners. Large multicenter cohort studies have enabled a better understanding of the relevance of coronary calcium detection. The purpose of this review is to review the methods for quantification of coronary artery calcium, as well as to present current and future perspectives on calcium scoring for cardiovascular risk stratification.

Noncoronary Measures Enhance the Predictive Value of Cardiac CT Above Traditional Risk Factors and CAC Score in the General Population

ObjectivesThe aim of this study was to determine whether noncoronary measures from cardiac computed tomography (CT) may enhance the prognostic value of this imaging technology. BackgroundWhen cardiac CT is performed for quantification of coronary artery calcium (CAC) score, information on other cardiac and thoracic structures is available. MethodsParticipants without known cardiovascular disease from the prospective population based Heinz Nixdorf Recall study underwent noncontrast cardiac CT for CAC score quantification. From CT, epicardial adipose tissue (EAT) volume, left ventricular and left atrial (LA) axial area index, ascending and descending aortic diameters, as well as aortic valve, mitral ring, and thoracic aortic calcification (TAC) were assessed. Incident cardiovascular events included myocardial infarction, stroke, and cardiovascular death. The prognostic value of CT-derived parameters was assessed by Cox regression analysis, receiver operating characteristics, and net reclassification improvement. ResultsFrom 3,630 subjects (59 ± 8 years of age, 46% male), 241 (6.6%) developed a cardiovascular event during 9.9 ± 2.6 years of follow-up. In multivariable Cox regression analysis including Framingham Risk Score, CAC (as log[CAC + 1]), and CT parameters, LA index (hazard ratio [HR]: 1.22 [95% confidence interval [CI]: 1.05 to 1.41] per SD; p = 0.010) and EAT volume (HR: 1.15 [95% CI: 1.01 to 1.30] per SD; p = 0.031) were significantly associated with incident events. In addition, presence of TAC showed an elevated event rate (HR: 1.33 [95% CI: 0.97 to 1.81]; p = 0.08), whereas all other CT-derived parameters showed no relevant association. The LA index, EAT volume, and presence of TAC together improved the prediction of events over Framingham Risk Score and CAC in receiver operating characteristics analysis (area under the curve: 0.749 to 0.764; p = 0.011), and let to a significant net reclassification improvement (HR: 38.0%; 95% CI: 25.1% to 50.8%). ConclusionAssessment of LA index, EAT volume, and TAC from non–contrast-enhanced cardiac CT improves the prediction of incident hard cardiovascular events above CAC and established risk factors, indicating that quantification of these noncoronary measures may improve the prognostic value of this imaging technology.

TH‐CD‐206‐12: Image‐Based Motion Estimation for Plaque Visualization in Coronary Computed Tomography Angiography

Purpose:Visualization and quantification of coronary artery calcification and atherosclerotic plaque benefits from coronary artery motion (CAM) artifact elimination. This work applies a rigid linear motion model to a Volume of Interest (VoI) for estimating motion estimation and compensation of image degradation in Coronary Computed Tomography Angiography (CCTA).Methods:In both simulation and testbench experiments, translational CAM was generated by displacement of the imaging object (i.e. simulated coronary artery and explanted human heart) by ∼8 mm, approximating the motion of a main coronary branch. Rotation was assumed to be negligible. A motion degraded region containing a calcification was selected as the VoI. Local residual motion was assumed to be rigid and linear over the acquisition window, simulating motion observed during diastasis. The (negative) magnitude of the image gradient of the reconstructed VoI was chosen as the motion estimation objective and was minimized with Covariance Matrix Adaptation Evolution Strategy (CMAES).Results:Reconstruction incorporated the estimated CAM yielded signification recovery of fine calcification structures as well as reduced motion artifacts within the selected local region. The compensated reconstruction was further evaluated using two image similarity metrics, the structural similarity index (SSIM) and Root Mean Square Error (RMSE). At the calcification site, the compensated data achieved a 3% increase in SSIM and a 91.2% decrease in RMSE in comparison with the uncompensated reconstruction.Conclusion:Results demonstrate the feasibility of our image‐based motion estimation method exploiting a local rigid linear model for CAM compensation. The method shows promising preliminary results for the application of such estimation in CCTA. Further work will involve motion estimation of complex motion corrupted patient data acquired from clinical CT scanner.

Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks.

The amount of coronary artery calcification (CAC) is a strong and independent predictor of cardiovascular events. CAC is clinically quantified in cardiac calcium scoring CT (CSCT), but it has been shown that cardiac CT angiography (CCTA) may also be used for this purpose. We present a method for automatic CAC quantification in CCTA. This method uses supervised learning to directly identify and quantify CAC without a need for coronary artery extraction commonly used in existing methods. The study included cardiac CT exams of 250 patients for whom both a CCTA and a CSCT scan were available. To restrict the volume-of-interest for analysis, a bounding box around the heart is automatically determined. The bounding box detection algorithm employs a combination of three ConvNets, where each detects the heart in a different orthogonal plane (axial, sagittal, coronal). These ConvNets were trained using 50 cardiac CT exams. In the remaining 200 exams, a reference standard for CAC was defined in CSCT and CCTA. Out of these, 100 CCTA scans were used for training, and the remaining 100 for evaluation of a voxel classification method for CAC identification. The method uses ConvPairs, pairs of convolutional neural networks (ConvNets). The first ConvNet in a pair identifies voxels likely to be CAC, thereby discarding the majority of non-CAC-like voxels such as lung and fatty tissue. The identified CAC-like voxels are further classified by the second ConvNet in the pair, which distinguishes between CAC and CAC-like negatives. Given the different task of each ConvNet, they share their architecture, but not their weights. Input patches are either 2.5D or 3D. The ConvNets are purely convolutional, i.e. no pooling layers are present and fully connected layers are implemented as convolutions, thereby allowing efficient voxel classification. The performance of individual 2.5D and 3D ConvPairs with input sizes of 15 and 25 voxels, as well as the performance of ensembles of these ConvPairs, were evaluated by a comparison with reference annotations in CCTA and CSCT. In all cases, ensembles of ConvPairs outperformed their individual members. The best performing individual ConvPair detected 72% of lesions in the test set, with on average 0.85 false positive (FP) errors per scan. The best performing ensemble combined all ConvPairs and obtained a sensitivity of 71% at 0.48 FP errors per scan. For this ensemble, agreement with the reference mass score in CSCT was excellent (ICC 0.944 [0.918-0.962]). Aditionally, based on the Agatston score in CCTA, this ensemble assigned 83% of patients to the same cardiovascular risk category as reference CSCT. In conclusion, CAC can be accurately automatically identified and quantified in CCTA using the proposed pattern recognition method. This might obviate the need to acquire a dedicated CSCT scan for CAC scoring, which is regularly acquired prior to a CCTA, and thus reduce the CT radiation dose received by patients.

The density of calcified plaques and the volume of calcium predict mortality in hemodialysis patients

Background and aimIn the general population lipid-rich plaques are prone to rupture and healing of the plaque involves calcification. Patients undergoing hemodialysis have a severe derangement of mineral metabolism and calcification of the arterial tree may have different implications. MethodsBetween 2004 and 2005, 125 hemodialysis patients (60 men) underwent computed tomography imaging for quantification of coronary artery calcium via the Agatston and the Volume methods. Since the Agatston score is derived by multiplying the density by the volume of a calcified lesion, the Agatston/Volume ratio (AVR) is an indication of the density (i.e. calcium accumulation) within the plaque. ResultsPatients were classified as high AVR (>1) or low (≤1) AVR. Survival analyses tested the association between AVR and all-cause mortality during a median follow-up of 5 years. The mean age was 57.2±13.5 years; 75% of the patients had AVR >1. The mortality rate of patients with AVR >1 was significantly higher than in patients with AVR ≤1 (Hazard Ratio(HR): 2.46; 95% Confidence Intervals(CI): 1.16–5.21, p ≤0.018). After adjustment for confounders, AVR >1 remained independently associated with all-cause mortality (HR: 2.24; 95% CI: 1.02–4.88, p ≤0.042). There was a significant interaction of plaque density and calcium volume on mortality. ConclusionsIncreased plaque density is an independent predictor of all-cause mortality in hemodialysis patients. These data suggest that increased calcium content in the coronary arteries of patients in dialysis is an index of high-risk rather than a marker of plaque stabilization.

Coronary Artery Calcium Analysis and Reporting on Noncontrast Chest CT Scans: a Paradigm Shift in Prevention

The quantification of coronary artery calcium (CAC) on gated noncontrast cardiac CT, as a screening test for subclinical coronary artery disease, has been consistently proven to be superior to risk factors and biomarkers for the prediction of long-term cardiovascular risk. Coronary artery calcium is also readily evaluable in every noncontrast (nongated) chest CT scan, yet there are no recommendations for reporting CAC in scans done for noncardiac indications. Lung CT scanning has been approved for lung cancer screening, and almost all the candidates are intermediate to high risk for coronary artery disease, which can be powerfully evaluated by the assessment of CAC at no additional radiation or cost. There are technical requirements for scanner detectors, slice thickness, and voltage which are easily satisfied. EKG gating provides the highest quality studies but will be more difficult to universally implement. Agatston scoring, ordinal scoring, and visual estimation of nongated scans offer alternatives and are supported by varying degrees of data. Similarly, newer reconstruction algorithms are available but are not yet widely used. Barriers to reporting include increased time and lack of increased reimbursement for CAC analysis, difficulties inherent to reporting abnormal results, and referring physician understanding and utilization of the results to alter patient education and management.

Evaluation of coronary artery calcification using multislice computed tomography in patients on dialysis: association with fetuin-A and osteoprotegerin

Introduction Cardiovascular disease is the leading cause of mortality in patients with end-stage renal disease (ESRD) and is attributed to a combination of traditional and nontraditional risk factors. In recent years, there has been an increasing recognition of a very high prevalence of cardiovascular calcification in the ESRD population, including patients receiving hemodialysis (HD) and peritoneal dialysis. The mechanism is multifactorial, including structural and functional abnormalities in the large vessels, disorders in calcium (Ca 2+ ) and phosphate (P) metabolism, vascular smooth muscle cells changes, and regulatory markers such as fetuin-A and osteoprotegerin (OPG). Aim of the work The aim of the present study was to determine the utility of multislice computed tomography (MSCT) for the assessment of coronary artery calcifications (CACs) and to identify the potential risks for CAC, including calcification regulating proteins such as fetuin-A and OPG, among patients with ESRD on maintenance dialysis (HD and peritoneal dialysis). Patients and methods This study included 70 patients who were divided into four groups: 20 patients on continuous ambulatory peritoneal dialysis (CAPD), 10 patients with ESRD stage 4 and 5, 30 patients on HD (subdivided into three subgroups according to the duration of HD: for 1–5 years, for 5–10 years, and for more than 10 years), and 10 healthy controls. They were subjected to complete history-taking, thorough clinical examination, investigations including serum level of fetuin-A, serum level of OPG by using the enzyme-linked immunosorbent assay technique, as well as MSCT imaging using 128-detector scanners for the quantification of CAC (calcium scoring) by using the Agatston method. Results There was a significant decrease in the serum level of fetuin-A in patients on HD compared with patients on CAPD, as well as in healthy controls. Moreover, there was a significant increase in the serum level of OPG in patients on HD compared with its level in CAPD patients as well as in healthy controls. The calcium scoring was significantly high in the HD group of patients (group IIa) ( P = 0.032), with a low calcium score in CAPD patients group (group I) ( P = 0.036) compared with healthy controls in group IV. CAC scoring was correlated positively and significantly with serum level of OPG in the total samples ( r = 0.345* and P = 0.0270). On the other hand, it was negatively and significantly correlated with the serum level of fetuin-A in the total samples ( r = −0.411* and P = 0.002). Conclusion Fetuin-A and OPG can be early and important markers of vascular calcifications in patients on dialysis; in addition, calcium scoring using MSCT provides a noninvasive method of assessment of the vascular calcification in these patients. Vascular calcification is more evident in patients on HD than in patients treated using CAPD; this can help in the selection of the modality of treatment of patients with ESRD, as well as early detection and prevention of cardiovascular (CVS) diseases in patients with ESRD treated with dialysis either HD or CAPD.

Rationale, Design, and Methodological Aspects of the BUDAPEST-GLOBAL Study (Burden of Atherosclerotic Plaques Study in Twins-Genetic Loci and the Burden of Atherosclerotic Lesions).

The heritability of coronary atherosclerotic plaque burden, coronary geometry, and phenotypes associated with increased cardiometabolic risk are largely unknown. The primary aim of the Burden of Atherosclerotic Plaques Study in Twins-Genetic Loci and the Burden of Atherosclerotic Lesions (BUDAPEST-GLOBAL) study is to evaluate the influence of genetic and environmental factors on the burden of coronary artery disease. By design this is a prospective, single-center, classical twin study. In total, 202 twins (61 monozygotic pairs, 40 dizygotic same-sex pairs) were enrolled from the Hungarian Twin Registry database. All twins underwent non-contrast-enhanced computed tomography (CT) for the detection and quantification of coronary artery calcium and for the measurement of epicardial fat volumes. In addition, a single non-contrast-enhanced image slice was acquired at the level of L3-L4 to assess abdominal fat distribution. Coronary CT angiography was used for the detection and quantification of plaque, stenosis, and overall coronary artery disease burden. For the primary analysis, we will assess the presence and volume of atherosclerotic plaques. Furthermore, the 3-dimensional coronary geometry will be assessed based on the coronary CT angiography datasets. Additional phenotypic analyses will include per-patient epicardial and abdominal fat quantity measurements. Measurements obtained from monozygotic and dizygotic twin pairs will be compared to evaluate the genetic or environmental effects of the given phenotype. The BUDAPEST-GLOBAL study provides a unique framework to shed some light on the genetic and environmental influences of cardiometabolic disorders.

The effect of iterative model reconstruction on coronary artery calcium quantification.

Coronary artery calcium (CAC) scoring with computed tomography (CT) is an established tool for quantifying calcified atherosclerotic plaque burden. Despite the widespread use of novel image reconstruction techniques in CT, the effect of iterative model reconstruction on CAC score remains unclear. We sought to assess the impact of iterative model based reconstruction (IMR) on coronary artery calcium quantification as compared to the standard filtered back projection (FBP) algorithm and hybrid iterative reconstruction (HIR). In addition, we aimed to simulate the impact of iterative reconstruction techniques on calcium scoring based risk stratification of a larger asymptomatic population. We studied 63 individuals who underwent CAC scoring. Images were reconstructed with FBP, HIR and IMR and CAC scores were measured. We estimated the cardiovascular risk reclassification rate of IMR versus HIR and FBP in a larger asymptomatic population (n = 504). The median CAC scores were 147.7 (IQR 9.6-582.9), 107.0 (IQR 5.9-526.6) and 115.1 (IQR 9.3-508.3) for FBP, HIR and IMR, respectively. The HIR and IMR resulted in lower CAC scores as compared to FBP (both p < 0.001), however there was no difference between HIR and IMR (p = 0.855). The CAC score decreased by 7.2 % in HIR and 7.3 % in IMR as compared to FBP, resulting in a risk reclassification rate of 2.4 % for both HIR and IMR. The utilization of IMR for CAC scoring reduces the measured calcium quantity. However, the CAC score based risk stratification demonstrated modest reclassification in IMR and HIR versus FBP.

Single low-dose CT scan optimized for rest-stress PET attenuation correction and quantification of coronary artery calcium

BackgroundCoronary artery calcium is an important marker of coronary artery disease. Myocardial perfusion imaging (MPI) using PET-CT technology requires a CT scan for attenuation correction (CTAC) but is not used routinely to measure coronary calcium burden. This study aimed to determine if a low-dose CTAC scan can also accurately quantify coronary artery calcium. MethodsTwenty-three patients underwent both a traditional coronary artery calcium scan on a dedicated cardiac CT scanner (CAC-CT) and a myocardial perfusion scan on a hybrid PET-CT scanner. The standard MPI protocol includes rest and stress-matched PET and CTAC scans. The post-stress CTAC scan was modified to approximate the CAC-CT scan protocol while maintaining ~0.5 mSv dose. Coronary artery calcium scores were compared between the Ca-CTAC and CAC-CT scans. ResultsThe modified Ca-CTAC scan showed a trend toward slight decreases in segmental stress perfusion of 2-3.5% in the anterior wall segments (P < 0.05). Correlation and agreement between the proposed Ca-CTAC and standard CAC-CT calcium scores at the optimal threshold of 110 HU were also excellent (r2 = 0.99, κ = 1.0). There was a small difference in the regression slope vs unity: Ca-CTAC = 0.96 × CAC (P < 0.05), but the categorical classification of calcium was accurate in all twenty-three patients (κ = 1.0). ConclusionA single low-dose rest CTAC scan can be used for accurate attenuation correction of rest and stress PET perfusion images, thus allowing a post-stress CTAC scan to be optimized for improved quantification of coronary artery calcium without increasing radiation dose vs standard protocols.

The feasibility of low-dose CT protocols for coronary artery calcium scoring and PET attenuation correction in cardiac PET/CT.

The purpose of this study was to investigate the feasibility of using low-dose computed tomography (CT) in coronary artery calcium scoring and PET attenuation correction for patients in different weight categories undergoing cardiac PET/CT examinations. Calcium scoring computed tomography (CSCT) scans and PET scans of anthropomorphic cardiac phantoms simulating normal-weight, mildly obese, and severely obese patients were acquired with a hybrid PET/CT scanner. CSCT images were acquired at 120 kVp, with tube current ranging from 10 to 550 mA. PET scans were performed in three-dimensional mode, with acquisition time of 3 min/bed position. The image quality of cardiac PET/CT was evaluated by assessing the signal-to-noise ratio. CT-based coronary artery calcium quantification was performed using the Agatston scoring system. On the basis of our results, the CSCT protocols using tube currents of 50 and 150 mA should be able to achieve the lowest possible radiation dose while maintaining the desired image quality for normal-weight and mildly obese patients undergoing cardiac PET/CT examinations, respectively. When the proposed low-dose CSCT protocols were performed, radiation dose could be reduced by 83.34 and 50% compared with those from CSCT scans acquired with standard tube current settings for normal-weight and mildly obese patients, respectively. In the scanning of severely obese patients, an increase in tube voltage or current would help improve the reliability of image information provided by cardiac PET/CT. Our study demonstrated the feasibility of low-dose CT protocols for coronary artery calcium scoring and PET attenuation correction in cardiac PET/CT to examine patients in different weight categories. The calculations performed in this work should be able to provide practical information to achieve necessary diagnostic information while keeping radiation dose as low as reasonably achievable.

Coronary calcium score in 12-year breast cancer survivors after adjuvant radiotherapy with low to moderate heart exposure – Relationship to cardiac radiation dose and cardiovascular risk factors

Background/purposeWe explored the relation between coronary artery calcium (CAC) and cardiac radiation doses in breast cancer survivors (BCS) treated with radiotherapy (RT). Additionally, we examined the impact of other risk factors and biomarkers of coronary artery disease (CAD). Materials and methods236 BCS (median age 51years [range 30–70], median observation time 12years [9.2–15.7]), treated with 4-field RT of 50GY, were included and examined in 2004 (T1), 2007 (T2) and 2011 (T3) with clinical examination, blood tests and questionnaires. At T3, cardiac computed tomography was performed with quantification of CAC using Agatston score (AS). For 106 patients cardiac dose volume histograms were available. ResultsThe cohort-based median of the mean cardiac dose was 2.5 (range 0.5–7.0) Gy. There was no correlation between measures of cardiac dose and AS. AS was correlated with high cholesterol at T1/T2 (p=0.022), high proBNP at T1/T2 (p<0.022) and T3 (p<0.022) and high HbA1c at T3 (p=0.022). In addition, a high AS was significantly associated with hypertension (p=0.022). Age (p<0.001) and cholesterol at T1/T2 (p=0.001) retained significant associations in multivariate analysis. ConclusionsTraditional, modifiable risk factors of CAD correlate with CAC and may be important for the long term risk of CAD after RT. With low to moderate cardiac radiation exposure, a contribution of radiation dose to CAC could not be demonstrated.

Quantification of coronary artery calcium in nongated CT to predict cardiovascular events in male lung cancer screening participants: Results of the NELSON study

ObjectiveTo evaluate the incremental prognostic value of the number and maximum volume of coronary artery calcifications over modified Agatston score strata, age, pack-years, and smoking status for predicting cardiovascular events. MethodsA total of 3559 male current and former smokers received a CT examination for lung cancer screening. Smoking characteristics, patient demographics, and physician-diagnosed cardiovascular events were collected. Images were acquired without electrocardiography gating on 16-slice CT scanners. The association between the presence of both fatal and nonfatal cardiovascular events and the predictors was quantified using Cox proportional hazard analysis. ResultsMedian follow-up period was 2.9 years. Incident cardiovascular events occurred in 186 participants. Adjusted hazard ratios for modified Agatston score strata of 1 to 10, 11 to 100, 101 to 400, and >400 were 3.39 (95% confidence interval [CI], 1.20–9.59), 6.52 (95% CI, 2.73–15.60), 6.58 (95% CI, 2.75–15.78), and 12.58 (95% CI, 5.42–29.16), respectively. Moreover, comparing the models with and without modified Agatston score strata to the model with age, pack-years, and smoking status yielded a significantly better net reclassification improvement (NRI; 27.3%; P < .0001). Adding the number of calcifications to the model with age, pack-years, smoking status, and modified Agatston score strata resulted in a slightly better NRI (1.68%; P = .0490) with a hazard ratio of 1.13 (95% CI, 1.05–1.21) per 10 calcifications. The incremental prognostic information contained in the volume of the largest calcification was not statistically significant (NRI, 0.14%; P = .3458). ConclusionCardiovascular event rate increased with higher numbers of calcified lesions. The number but not maximum volume of calcifications has independent, although minimal, prognostic value over age, pack-years, smoking status, and modified Agatston score strata in our population.

Precision phenotyping, panomics, and system-level bioinformatics to delineate complex biologies of atherosclerosis: Rationale and design of the “Genetic Loci and the Burden of Atherosclerotic Lesions” study

BackgroundComplex biological networks of atherosclerosis are largely unknown. ObjectiveThe main objective of the Genetic Loci and the Burden of Atherosclerotic Lesions study is to assemble comprehensive biological networks of atherosclerosis using advanced cardiovascular imaging for phenotyping, a panomic approach to identify underlying genomic, proteomic, metabolomic, and lipidomic underpinnings, analyzed by systems biology–driven bioinformatics. MethodsBy design, this is a hypothesis-free unbiased discovery study collecting a large number of biologically related factors to examine biological associations between genomic, proteomic, metabolomic, lipidomic, and phenotypic factors of atherosclerosis. The Genetic Loci and the Burden of Atherosclerotic Lesions study (NCT01738828) is a prospective, multicenter, international observational study of atherosclerotic coronary artery disease. Approximately 7500 patients are enrolled and undergo non–contrast-enhanced coronary calcium scanning by CT for the detection and quantification of coronary artery calcium, as well as coronary artery CT angiography for the detection and quantification of plaque, stenosis, and overall coronary artery disease burden. In addition, patients undergo whole genome sequencing, DNA methylation, whole blood–based transcriptome sequencing, unbiased proteomics based on mass spectrometry, as well as metabolomics and lipidomics on a mass spectrometry platform. The study is analyzed in 3 subsequent phases, and each phase consists of a discovery cohort and an independent validation cohort. For the primary analysis, the primary phenotype will be the presence of any atherosclerotic plaque, as detected by cardiac CT. Additional phenotypic analyses will include per patient maximal luminal stenosis defined as 50% and 70% diameter stenosis. Single-omic and multi-omic associations will be examined for each phenotype; putative biomarkers will be assessed for association, calibration, discrimination, and reclassification.