Quantification Of Coronary Calcium Research Articles

Associations Between Hypothyroidism and Subclinical Atherosclerosis Among Male and Female Patients Without Clinical Disease Referred to Computed Tomography

ObjectivesHypothyroidism is recognized as a risk factor for coronary artery disease (CAD). However, reports are conflicting when the results are stratified by sex and the underlying risk of CAD. We examine the sex-specific associations of hypothyroidism with coronary calcification and plaques. MethodsRetrospective cross-sectional study was conducted among adult patients referred to (64 multidetector spiral) computed tomography. Those with pre-existing CAD were excluded. Hypothyroidism was defined as thyroid-stimulating hormone ≥ 4.5 mU/L. Plaques were determined based on quantification of coronary calcium and coronary computed tomography angiography. ResultsA total of 2499 patients (1544 male and 955 female) were included. The prevalence of hypothyroidism was significantly higher in female than in male patients (18.0% vs 12.9%, P < .001), in all patients and those <65 years. Hypothyroidism in male patients was significantly associated with higher coronary calcium score > 0, higher coronary calcium score groups, and both soft and calcified plaques (P = .027, P = .032, P = .005, and P = .017, respectively). After adjusting for traditional coronary risk factors, the higher risk in male patients remained significant for coronary plaque but not for coronary calcium score >0 (odds ratios and CIs were 1.77, 1.08-2.90, P = .023 and .98, 0.63-1.52, P = .925, respectively). On the other hand, hypothyroidism in female patients was not significantly associated with coronary calcification nor plaques in both univariate and multivariate analyses. ConclusionsThere are sex-specific differences in the association of hypothyroidism with subclinical atherosclerosis. The higher risk of coronary plaques but not calcification in male patients was independent of traditional coronary risk factors. The lack of associations in female patients may be related to lower underlying risk of CAD.

Extracranial Carotid Plaque Calcification and Cerebrovascular Ischemia: A Systematic Review and Meta-Analysis.

Although coronary calcification quantification is an established approach for cardiovascular risk assessment, the value of quantifying carotid calcification is less clear. As a result, we performed a systematic review and meta-analysis to evaluate the association between extracranial carotid artery plaque calcification burden and ipsilateral cerebrovascular ischemic events. A comprehensive literature search was performed in the following databases: Ovid MEDLINE(R) 1946 to July 6, 2022; OVID Embase 1974 to July 6, 2022; and The Cochrane Library (Wiley). We performed meta-analyses including studies in which investigators performed a computed tomography assessment of calcification volume, percentage, or other total calcium burden summarizable in a single continuous imaging biomarker and determined the association of these features with the occurrence of ipsilateral stroke or transient ischemic attack. Our overall meta-analysis consisted of 2239 carotid arteries and 9 studies. The presence of calcification in carotid arteries ipsilateral to ischemic stroke or in stroke patients compared with asymptomatic patients did not demonstrate a significant association with ischemic cerebrovascular events (relative risk of 0.75 [95% CI, 0.44-1.28]; P=0.29). When restricted to studies of significant carotid artery stenosis (>50%), the presence of calcification was associated with a reduced risk of ischemic stroke (relative risk of 0.56 [95% CI, 0.38-0.85]; P=0.006). When the analysis was limited to studies of patients with mainly nonstenotic plaques, there was an increased relative risk of ipsilateral ischemic stroke of 1.72 ([95% CI, 1.01-2.91]; P=0.04). Subgroup meta-analyses of total calcium burden and morphological features of calcium showed wide variability in their strength of association with ischemic stroke and demonstrated significant heterogeneity. The presence of calcification in carotid plaque confers a reduced association with ipsilateral ischemic events, although these results seem to be limited among carotid arteries with higher degrees of stenosis. Adoption of carotid calcification measures in clinical decision-making will require additional studies providing more reproducible and standardized methods of calcium characterization and testing these imaging strategies in prospective studies.

#3724 CHANGES IN CARDIOVASCULAR CALCIFICATION AFTER PARATHYROIDECTOMY IN DIALYSIS-DEPENDENT PATIENTS

Abstract Background and Aims Vascular calcification (VC) is common in patients with end stage kidney disease on dialysis and with secondary hyperparathyroidism (SHPT). There is a lack of knowledge regarding dynamics of VC after surgical treatment of SHPT. We aimed to evaluate evolution of coronary artery calcification (CAC) and abdominal aortic calcification (AAC) after parathyroidectomy (PTx) in dialysis patients with SHPT. Method The prospective cohort study included 33 dialysis-dependent patients (mean age of 50±13 years) with severe SHPT who underwent subtotal (n = 16) or total PTx with autotransplantation of parathyroid tissue (n = 17). Cardiac computed tomography scan (quantification of coronary calcium by Agatston method) and lateral lumbar X-ray (semi-quantitative Kauppila score) were used to assess prevalence of VC before and 18 months after surgery. Levels of serum total calcium, phosphorus, parathyroid hormone (PTH), and alkaline phosphatase (AP) before and 18 months after surgery were also evaluated. Results In our cohort median dialysis vintage before surgery was 71 [Q1-Q3: 29; 136] months, total serum Ca was 2.47±0.23 mmol/l, median PTH was 139 [Q1-Q3: 90; 161] pg/ml. Prevalence of CAC before PTx was 79% (n = 26), and 61% (n = 20) of patients had AAC. Of note, 54.5% of the patients had severe coronary calcification (&amp;gt;400 AU), while only 12% were considered to have severe calcification using Kauppila score (&amp;gt;12). We observed moderate positive correlation between CAC and AAC scores (Spearman's ρ = 0.699 [95% CI: 0.48; 0.84], р&amp;lt;0.0001). Both CAC and AAC scores correlated moderately with age of the patients (ρ = 0.57 [95% CI: 0.3; 0.76], р = 0.0002, and ρ = 0.64 [95% CI: 0.39; 0.8], р&amp;lt;0.0001, respectively), AAC had weak correlation with their dialysis vintage (ρ = 0.45 [95% CI: 0.14; 0.68], р = 0.005. Median of baseline CAC was 458 [Q1-Q3: 23; 1585] AU, after 18 months - 491 [Q1-Q3: 58; 1956] AU, no statistically significant differences were observed (p = 0.91, Wilcoxon test). We did not find statistically significant differences between median of Kauppila scores before and after PTx as well: 3 [Q1-Q3: 0; 10] and 2 [Q1-Q3: 0; 10], correspondingly, p = 0.17 (Wilcoxon test) – Fig. 1. As it can be seen from Fig. 1, dynamics of both CAC and AAC values before and after PTx varied markedly across subjects. To investigate the factors that can promote VC we divided patients into 2 groups based on dynamics of САС (as the most accurate assessment method) 18 months after surgery: group 1 with CAC progression of more than 50 AU (n = 9) and group 2 with regression or progression less than 50 AU (n = 24). Patients who had progression of coronary calcification by the end of the follow-up had higher age (59±11 vs 46±12 years in 2nd group, p = 0.0128) higher serum calcium levels (2.57±0.24 vs 2.29±0.32 mmol/l in 2nd group, p = 0.0267), and higher AP levels at follow-up (69.8 [Q1-Q3: 62.8, 96.0] vs 51.7 [Q1-Q3: 41.4; 57.1] U/ml in 2nd group, p = 0.003). Univariate analysis showed no significant differences between groups comparing dialysis vintage (p = 0.53), phosphate levels (p = 0.54), PTH levels (p = 0.32). In addition, CAC progression risk was not associated with type of surgery (total vs subtotal PTx RR = 1.11 [95% CI: 0.71; 1.8], OR = 1.48 [95% CI: 0.3; 5.7], p = 0.708). Conclusion Prevalence of vascular calcification in dialysis-dependent patients with severe SHPT is high. Progression of CAC by 18 months after PTx was associated with higher age of the patients, higher follow-up levels of serum total Ca and AP.

Automated cardiovascular risk categorization through AI-driven coronary calcium quantification in cardiac PET acquired attenuation correction CT

BackgroundWe present an automatic method for coronary artery calcium (CAC) quantification and cardiovascular risk categorization in CT attenuation correction (CTAC) scans acquired at rest and stress during cardiac PET/CT. The method segments CAC according to visual assessment rather than the commonly used CT-number threshold. MethodsThe method decomposes an image containing CAC into a synthetic image without CAC and an image showing only CAC. Extensive evaluation was performed in a set of 98 patients, each having rest and stress CTAC scans and a dedicated calcium scoring CT (CSCT). Standard manual calcium scoring in CSCT provided the reference standard. ResultsThe interscan reproducibility of CAC quantification computed as average absolute relative differences between CTAC and CSCT scan pairs was 75% and 85% at rest and stress using the automatic method compared to 121% and 114% using clinical calcium scoring. Agreement between automatic risk assessment in CTAC and clinical risk categorization in CSCT resulted in linearly weighted kappa of 0.65 compared to 0.40 between CTAC and CSCT using clinically used calcium scoring. ConclusionThe increased interscan reproducibility achieved by our method may allow routine cardiovascular risk assessment in CTAC, potentially relieving the need for dedicated CSCT.

Deep learning applications in coronary anatomy imaging: a systematic review and meta-analysis.

The application of deep learning on medical imaging is growing in prevalence in the recent literature. One of the most studied areas is coronary artery disease (CAD). Imaging of coronary artery anatomy is fundamental, which has led to a high number of publications describing a variety of techniques. The aim of this systematic review is to review the evidence behind the accuracy of deep learning applications in coronary anatomy imaging. The search for the relevant studies, which applied deep learning on coronary anatomy imaging, was performed in a systematic approach on MEDLINE and EMBASE databases, followed by reviewing of abstracts and full texts. The data from the final studies was retrieved using data extraction forms. A meta-analysis was performed on a subgroup of studies, which looked at fractional flow reserve (FFR) prediction. Heterogeneity was tested using tau2, I2 and Q tests. Finally, a risk of bias was performed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS) approach. A total of 81 studies met the inclusion criteria. The most common imaging modality was coronary computed tomography angiography (CCTA) (58%) and the most common deep learning method was convolutional neural network (CNN) (52%). The majority of studies demonstrated good performance metrics. The most common outputs were focused on coronary artery segmentation, clinical outcome prediction, coronary calcium quantification and FFR prediction, and most studies reported area under the curve (AUC) of ≥80%. The pooled diagnostic odds ratio (DOR) derived from 8 studies looking at FFR prediction using CCTA was 12.5 using the Mantel-Haenszel (MH) method. There was no significant heterogeneity amongst studies according to Q test (P=0.2496). Deep learning has been used in many applications on coronary anatomy imaging, most of which are yet to be externally validated and prepared for clinical use. The performance of deep learning, especially CNN models, proved to be powerful and some applications have already translated into medical practice, such as computed tomography (CT)-FFR. These applications have the potential to translate technology into better care of CAD patients.

Systematic assessment of coronary calcium detectability and quantification on four generations of CT reconstruction techniques: a patient and phantom study

In computed tomography, coronary artery calcium (CAC) scores are influenced by image reconstruction. The effect of a newly introduced deep learning-based reconstruction (DLR) on CAC scoring in relation to other algorithms is unknown. The aim of this study was to evaluate the effect of four generations of image reconstruction techniques (filtered back projection (FBP), hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), and DLR) on CAC detectability, quantification, and risk classification. First, CAC detectability was assessed with a dedicated static phantom containing 100 small calcifications varying in size and density. Second, CAC quantification was assessed with a dynamic coronary phantom with velocities equivalent to heart rates of 60–75 bpm. Both phantoms were scanned and reconstructed with four techniques. Last, scans of fifty patients were included and the Agatston calcium score was calculated for all four reconstruction techniques. FBP was used as a reference. In the phantom studies, all reconstruction techniques resulted in less detected small calcifications, up to 22%. No clinically relevant quantification changes occurred with different reconstruction techniques (less than 10%). In the patient study, the cardiovascular risk classification resulted, for all reconstruction techniques, in excellent agreement with the reference (κ = 0.96–0.97). However, MBIR resulted in significantly higher Agatston scores (61 (5.5–435.0) vs. 81.5 (9.25–435.0); p < 0.001) and 6% reclassification rate. In conclusion, HIR and DLR reconstructed scans resulted in similar Agatston scores with excellent agreement and low-risk reclassification rate compared with routine reconstructed scans (FBP). However, caution should be taken with low Agatston scores, as based on phantom study, detectability of small calcifications varies with the used reconstruction algorithm, especially with MBIR and DLR.

Association of blood lipids with coronary artery plaque among Saudi patients referred to computed tomography

BackgroundBlood lipids are strong risk factors for the progression of atherosclerotic plaques. However, data on gender-specific associations are limited.ObjectivesTo examine gender-specific associations of coronary plaque with blood lipids among a large sample of Saudi patients without CAD.MethodsRetrospective cross-sectional study was conducted among adult patients referred to (64 multidetector spiral) computed tomography (CT) for standard indications at the Prince Sultan Cardiac Centre (Riyadh, Saudi Arabia) between July 2007 and December 2017. Those with pre-existing CAD were excluded. Plaques were determined based on quantification of coronary calcium and Coronary CT angiography.ResultsA total 2421 patients (1498 males and 923 females) were included. The prevalence of any plaque was 36.6% with higher burden in males than females (41.3% versus 28.9%, p < 0.001). Approximately 78.9% of all plaques were calcified. Blood lipids (mmol/L) were 4.75 ± 1.14 for total cholesterol, 2.90 ± 0.96 for LDL cholesterol, 1.20 ± 0.36 for HDL cholesterol, and 1.64 ± 1.09 for triglycerides. Males had significantly higher triglycerides and lower HDL cholesterol compared with females. In adjusted models in males and all patients, soft and/or calcified plaques were significantly associated with lower HDL cholesterol and higher triglycerides. In females, the only significant association was between soft plaques and higher triglycerides.ConclusionsMiddle-aged patients without clinical CAD in Saudi Arabia have a high burden of plaques, specially calcified ones. The findings may impact the use of lipid lowering mediations, by underscoring the importance of assessing the risk of CAD in patients without clinical CAD even in case of lack of coronary calcification.

Improved coronary calcium detection and quantification with low-dose full field-of-view photon-counting CT: a phantom study.

The aim of the current study was to systematically assess coronary artery calcium (CAC) detection and quantification for spectral photon-counting CT (SPCCT) in comparison to conventional CT and, in addition, to evaluate the possibility of radiation dose reduction. Routine clinical CAC CT protocols were used for data acquisition and reconstruction of two CAC containing cylindrical inserts which were positioned within an anthropomorphic thorax phantom. In addition, data was acquired at 50% lower radiation dose by reducing tube current, and slice thickness was decreased. Calcifications were considered detectable when three adjacent voxels exceeded the CAC scoring threshold of 130 Hounsfield units (HU). Quantification of CAC (as volume and mass score) was assessed by comparison with known physical quantities. In comparison with CT, SPCCT detected 33% and 7% more calcifications for the small and large phantoms, respectively. At reduced radiation dose and reduced slice thickness, small phantom CAC detection increased by 108% and 150% for CT and SPCCT, respectively. For the large phantom size, noise levels interfered with CAC detection. Although comparable between CT and SPCCT, routine protocols CAC quantification showed large deviations (up to 134%) from physical CAC volume. At reduced radiation dose and slice thickness, physical volume overestimations decreased to 96% and 72% for CT and SPCCT, respectively. In comparison with volume scores, mass score deviations from physical quantities were smaller. CAC detection on SPCCT is superior to CT, and was even preserved at a reduced radiation dose. Furthermore, SPCCT allows for improved physical volume estimation. • In comparison with conventional CT, increased coronary artery calcium detection (up to 156%) for spectral photon-counting CT was found, even at 50% radiation dose reduction. • Spectral photon-counting CT can more accurately measure physical volumes than conventional CT, especially at reduced slice thickness and for high-density coronary artery calcium. • For both conventional and spectral photon-counting CT, reduced slice thickness reconstructions result in more accurate physical mass approximation.

Influence Of Slice Thickness And Iterative Reconstruction On Coronary Artery Calcification Quantification

Introduction: Reconstruction parameters including iterative reconstruction algorithms and slice thickness influence the quantification of coronary calcification. Moreover, with modern scanner platforms and increasing use of iterative reconstruction algorithms, assessment of coronary calcium quantification will ultimately be affected. We sought to analyze the influence of slice thickness and iterative reconstruction on quantitative parameters of coronary calcification.

Postmortem coronary artery calcium score in cases of myocardial infarction.

Sudden cardiac death (SCD) related to atherosclerotic coronary artery disease (ACAD) resulting in myocardial infarction is the most prevalent cause of death in western countries. In clinical practice, coronary artery calcium score (CACS) is considered an independent predictor of coronary events, closely related to atherosclerotic burden and is quantified radiologically by the Agatston score being calculated through computed tomography. Postmortem computed tomography (PMCT) allows the visualization and quantification of coronary calcifications before the autopsy. However, it was reported that some patients who died from severe ACAD had a zero CACS in PMCT. In this study, a retrospective evaluation of CACS in adult’s myocardial infarction cases related to ACAD, with available CACS and histological slides of coronary arteries, was performed in order to gain a deeper understanding of coronary calcifications and their role in myocardial infarction cases. The CACS was calculated by using the software Smartscore 4.0 after the radiological examination on a 64-row CT unit using a specific cardiac protocol. Thirty-six cases were identified out of 582 autopsies, recorded during a 2-year study period (29 men, 7 women; age 56.3 ± 11.7). CACS was 0–10 in 5 cases (5 men, 44.8 ± 13.7), 11–100 in 8 cases (6 men, 2 women, 53.1 ± 7.7), 101–400 in 13 cases (11 men, 2 women, 57.4 ± 9.6), and > 400 in 10 cases (9 men, 1 woman, 63.1 ± 11.9). Coronary thrombosis was found in 28 cases, histologically identified as plaque erosions in 6 cases and as plaque ruptures in 22 cases. Statistical analyses showed that CACS increases significantly with age (p-value < 0.05) and does not show significant correlation with gender, body weight, body mass index, and heart weight. CACS was significantly higher in plaque ruptures than in plaque erosions (p-value < 0.01). Zero or low CACS on unenhanced PMCT cannot exclude the presence of myocardial infarction related to ACAD. This paradoxical discrepancy between imaging and autopsy findings can be explained considering the histological aspect of fatal coronary plaques.

Improved coronary calcification quantification using photon-counting-detector CT: an ex vivo study in cadaveric specimens.

To compare the accuracy of coronary calcium quantification of cadaveric specimens imaged from a photon-counting detector (PCD)-CT and an energy-integrating detector (EID)-CT. Excised coronary specimens were scanned on a PCD-CT scanner, using both the PCD and EID subsystems. The scanning and reconstruction parameters for EID-CT and PCD-CT were matched: 120 kV, 9.3-9.4 mGy CTDIvol, and a quantitative kernel (D50). PCD-CT images were also reconstructed using a sharper kernel (D60). Scanning the same specimens using micro-CT served as a reference standard for calcified volumes. Calcifications were segmented with a half-maximum thresholding technique. Segmented calcified volume differences were analyzed using the Friedman test and post hoc pairwise Wilcoxon signed rank test with the Bonferroni correction. Image noise measurements were compared between EID-CT and PCD-CT with a repeated-measures ANOVA test and post hoc pairwise comparison with the Bonferroni correction. A p < 0.05 was considered statistically significant. The volume measurements in 12/13 calcifications followed a similar trend: EID-D50 > PCD-D50 > PCD-D60 > micro-CT. The median calcified volumes in EID-D50, PCD-D50, PCD-D60, and micro-CT were 22.1 (IQR 10.2-64.8), 21.0 (IQR 9.0-56.5), 18.2 (IQR 8.3-49.3), and 14.6 (IQR 5.1-42.4) mm3, respectively (p < 0.05 for all pairwise comparisons). The average image noise in EID-D50, PCD-D50, and PCD-D60 was 60.4 (± 3.5), 56.0 (± 4.2), and 113.6 (± 8.5) HU, respectively (p < 0.01 for all pairwise comparisons). The PCT-CT systemquantified coronary calcifications more accurately than EID-CT, and a sharp PCD-CT kernel further improved the accuracy. The PCD-CT images exhibited lower noise than the EID-CT images. • High spatial resolution offered by PCD-CT reduces partial volume averaging and consequently leads to better morphological depiction of coronary calcifications. • Improved quantitative accuracy for coronary calcification volumes could be achieved using high-resolution PCD-CT compared to conventional EID-CT. • PCD-CT images exhibit lower image noise than conventional EID-CT at matched radiation dose and reconstruction kernel.

Sinogram-Affirmed Iterative Reconstruction Negatively Impacts the Risk Category Based on Agatston Score: A Study Combining Coronary Calcium Score Measurement and Coronary CT Angiography.

Purpose To assess the impact of sinogram-affirmed iterative reconstruction (SAFIRE) on risk category for coronary artery disease by combining coronary calcium score measurement and coronary CT angiography (CCTA). Materials and Methods Eighty-nine patients (64.0% male) older than 18 years (64.4 ± 10.3 years) underwent coronary artery calcium scanning and prospectively ECG-triggered sequential CCTA examination. All raw data acquired in coronary artery calcium scanning were reconstructed by both filtered back projection (FBP) and SAFIRE algorithms with 5 different levels. Objective image quality and calcium quantification were evaluated and compared between FBP and all SAFIRE levels by the Sphericity Assumed test or Greenhouse-Geisser ε correction coefficient. Coronary artery stenosis was assessed in CCTA. Risk categories of all patients and of the patients with coronary artery stenosis in CCTA were compared between FBP and all SAFIRE levels by the Friedman test. Results The reconstruction protocol from traditional FBP to SAFIRE 5 was associated with a gradual reduction in CT value and image noise (P < 0.001) but associated with a gradual improvement in the signal-to-noise ratio (P < 0.001). There was a gradual reduction in coronary calcification quantification (Agatston score: from 73.5 in FBP to 38.1 in SAFIRE 5, P < 0.001) from traditional FBP to SAFIRE 5. There was a significant difference for the risk category between FBP and all levels of SAFIRE in all patients (from 3.5 in FBP to 3.2 in SAFIRE 5, P < 0.001) and in the patients with coronary artery stenosis in CCTA (from 4.0 in FBP to 3.6 in SAFIRE 5, P < 0.001). Conclusions SAFIRE significantly reduces coronary calcification quantification compared to FBP, resulting in the reduction of risk categories based on the Agatston score. The risk categories of the patients with coronary artery stenosis in CCTA may also decline. Thus, SAFIRE may lead risk categories to underestimate the existence of significant coronary artery stenosis.

Reduced Radiation Dose and IR-impact on Coronary Calcium Quantification

Reduced Radiation Dose and IR-impact on Coronary Calcium Quantification

Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols.

Background Although several deep learning (DL) calcium scoring methods have achieved excellent performance for specific CT protocols, their performance in a range of CT examination types is unknown. Purpose To evaluate the performance of a DL method for automatic calcium scoring across a wide range of CT examination types and to investigate whether the method can adapt to different types of CT examinations when representative images are added to the existing training data set. Materials and Methods The study included 7240 participants who underwent various types of nonenhanced CT examinations that included the heart: coronary artery calcium (CAC) scoring CT, diagnostic CT of the chest, PET attenuation correction CT, radiation therapy treatment planning CT, CAC screening CT, and low-dose CT of the chest. CAC and thoracic aorta calcification (TAC) were quantified using a convolutional neural network trained with (a) 1181 low-dose chest CT examinations (baseline), (b) a small set of examinations of the respective type supplemented to the baseline (data specific), and (c) a combination of examinations of all available types (combined). Supplemental training sets contained 199-568 CT images depending on the calcium burden of each population. The DL algorithm performance was evaluated with intraclass correlation coefficients (ICCs) between DL and manual (Agatston) CAC and (volume) TAC scoring and with linearly weighted κ values for cardiovascular risk categories (Agatston score; cardiovascular disease risk categories: 0, 1-10, 11-100, 101-400, >400). Results At baseline, the DL algorithm yielded ICCs of 0.79-0.97 for CAC and 0.66-0.98 for TAC across the range of different types of CT examinations. ICCs improved to 0.84-0.99 (CAC) and 0.92-0.99 (TAC) for CT protocol-specific training and to 0.85-0.99 (CAC) and 0.96-0.99 (TAC) for combined training. For assignment of cardiovascular disease risk category, the κ value for all test CT scans was 0.90 (95% confidence interval [CI]: 0.89, 0.91) for the baseline training. It increased to 0.92 (95% CI: 0.91, 0.93) for both data-specific and combined training. Conclusion A deep learning calcium scoring algorithm for quantification of coronary and thoracic calcium was robust, despite substantial differences in CT protocol and variations in subject population. Augmenting the algorithm training with CT protocol-specific images further improved algorithm performance. © RSNA, 2020 See also the editorial by Vannier in this issue.

30Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium and epicardial adipose tissue: a prospective study

Abstract Background/Introduction Machine learning (ML) allows objective integration of clinical and imaging data for the prediction of events. ML prediction of cardiovascular events in asymptomatic subjects over long-term follow-up, utilizing quantitative CT measures of coronary artery calcium (CAC) and epicardial adipose tissue (EAT) have not yet been evaluated. Purpose To analyze the ability of machine learning to integrate clinical parameters with coronary calcium and EAT quantification in order to improve prediction of myocardial infarction (MI) and cardiac death in asymptomatic subjects. Methods We assessed 2071 consecutive subjects [1230 (59%) male, age: 56.049.03] from the EISNER (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) trial with long-term follow-up after non-enhanced cardiac CT. CAC (Agatston) score, age-and-gender-adjusted CAC percentile, and aortic calcium scores were obtained. EAT volume and density were quantified using a fully automated deep learning method. Extreme gradient boosting, a ML algorithm, was trained using demographic variables, plasma lipid panel measurements, risk factors as well as CAC, aortic calcium and EAT measures from CAC CT scans. ML was validated using 10-fold cross validation; event prediction was evaluated using area-under-receiver operating characteristic curve (AUC) analysis and Cox proportional hazards regression. Optimal ML cut-point for risk of MI and cardiac death was determined by highest Youden's index (sensitivity + specificity – 1). Results At 152 years' follow-up, 76 events of MI and/or cardiac death had occurred. ML obtained a significantly higher AUC than the ASCVD risk and CAC score in predicting events (ML: 0.81; ASCVD: 0.76, p&lt;0.05; CAC: 0.75, p&lt;0.01, Figure A). ML performance was mostly driven by age, ASCVD risk and calcium as shown by the variable importance (Figure B); however, all variables with non-zero gain contributed to the ML performance. ML achieved a sensitivity and specificity of 77.6% and 73.5%, respectively. For an equal specificity, ASCVD and CAC scores obtained a sensitivity of 61.8% and 67.1%, respectively. High ML risk was associated with a high risk of suffering an event by Cox regression (HR: 9.25 [95% CI: 5.39–15.87], p&lt;0.001; survival curves in Figure C). The relationships persisted when adjusted for age, gender, CAC, CAC percentile, aortic calcium score, and ASCVD risk score; with a hazard ratio of 3.42 for high ML risk (HR: 3.42 [95% CI: 1.54–7.57], p=0.002). Conclusion(s) Machine learning used to integrate clinical and quantitative imaging-based variables significantly improves prediction of MI and cardiac death in asymptomatic subjects undergoing CAC assessment, compared to standard risk assessment methods. Acknowledgement/Funding NHLBI 1R01HL13361, Bundesministerium für Bildung und Forschung (01EX1012B), Dr. Miriam and Sheldon G. Adelson Medical Research Foundation

Comparison of Nongated Chest CT and Dedicated Calcium Scoring CT for Coronary Calcium Quantification Using a 256-Dector Row CT Scanner

Coronary artery calcification (CAC) is a marker of atherosclerosis and an independent risk factor for cardiac-related mortality and frequently detected on noncontrast chest CT. We aimed to investigate the reliability and accuracy of determining CAC using noncontrast, nongated chest CT with 256-detector row. A total of 1318 patients for chest examination were enrolled to undergo both nongated chest CT and dedicated calcium-scoring CT (CSCT) on a 256-detector row CT scanner. The chest CT was scanned in fast-helical mode with 8 cm collimation, 0.28 second rotation speed and pitch 0.992:1 to cover entire chest. CSCT used single prospective ECG-triggered cardiac axial mode with 0.28 second rotation speed covering only the heart. CAC scores (Agatston, mass, and volume) were determined using both image sets and were statistically compared. Sensitivity and specificity of nongated chest CT for determining positive CAC was 94.8% (182/192) and 100%, respectively. The agreement in assessing the quantitative Agatston, volume, and mass scores between the nongated chest CT and CSCT was almost perfect, with the intraclass correlation coefficient values of 0.998, 0.999, and 0.999, respectively. Additionally, there was a good agreement in CAC quantification between the nongated chest CT and dedicated CSCT with small coefficient of variation: mass score (9.0%), volume score (9.5%), and Agatston score (12.6%). Nongated chest CT with 256-detector row is a reliable imaging mode for detecting and quantifying calcifications in coronary arteries compared with dedicated calcium-scoring CT.

Subclinical cardiovascular disease and Systemic Sclerosis: A comparison between risk charts, quantification of coronary calcium and carotid ultrasonography.

Recently published population-based cohort studies have shown a high prevalence of cardiovascular disease in Systemic Sclerosis (SSc) patients. The aim of this study is to compare three different methods to measure cardiovascular risk in patients with scleroderma. Forty-three SSc patients were included. A prospective study was performed for evaluation of cardiovascular risk and subclinical atheromatosis using 3 non-invasive methods: cardiovascular risk tables, carotid Doppler ultrasonography and quantification of coronary calcium by computerized tomography (CT). The cardiovascular risk charts for the Spanish population did not identify patients at high cardiovascular risk. Framingham-REGICOR identified 13 intermediate-risk patients. Twenty-two patients (51.2%) had plaques on carotid ultrasonography. We performed a ROC curve to identify the best cutoff point for the quantification of coronary artery calcium (CACscore), the value of CACscore > 28 AU (Agatston Units) had the highest sensitivity (73%) and specificity (81%) for the diagnosis of subclinical atheromatosis. In the multiple regression study, age and decreased HDL cholesterol levels were identified as independent factors for subclinical atherosclerotic disease. No disease-related factors were associated with increased subclinical arteriosclerosis. Carotid ultrasound and CACscore are useful for identifying subclinical atheromatosis in patients with SSc and are superior compared to risk charts used for general population. HDL cholesterol and age were independent factors for the presence of subclinical atherosclerotic disease. A carotid ultrasound or CT should be performed for early detection of subclinical atheromatosis if these factors are present.

High-pitch versus sequential mode for coronary calcium in individuals with a high heart rate: Potential for dose reduction

BackgroundTo determine the impact of high-pitch spiral acquisition on radiation dose and cardiovascular disease (CVD) risk stratification by coronary artery calcium (CAC) assessment with computed tomography in individuals with a high heart rate. MethodsOf the ROBINSCA trial, 1990 participants with regular rhythm and heart rates >65 beats per minute (bpm) were included. As reference, 390 participants with regular heart rates ≤65 bpm were used. All participants underwent prospectively electrocardiographically(ECG)-triggered imaging of the coronary arteries using dual source CT at 120 kVp, 80 ref mAs using both high-pitch spiral mode and sequential mode. Radiation dose, Agatston score, number of positive scores, as well as median absolute difference of the Agatston score were determined and participants were stratified into CVD risk categories. ResultsA similar percentage of participants with low heart rates and high heart rates had a positive CAC score in data sets acquired in high-pitch spiral (low heart rate: 57.7%, high heart rate: 55.8%) and sequential mode (58.0%, 54.7%, p = n.s.). The median absolute difference in Agatston scores between acquisition modes was 14.2% and 9.2%, for the high and low heart rate groups, respectively. Excellent agreement for risk categorization between the two data acquisition modes was found for the high (κ = 0.927) and low (κ = 0.946) heart rate groups. Radiation dose was 48% lower for high-pitch spiral versus sequential acquisitions. ConclusionRadiation dose for the quantification of coronary calcium can be reduced by 48% when using the high-pitch spiral acquisition mode compared to the sequential mode in participants with a regular high heart rate. CVD risk stratification agreement between the two modes of data acquisition is excellent.

German cardiac CT registry: indications, procedural data and clinical consequences in 7061 patients undergoing cardiac computed tomography.

Cardiac computed tomography permits quantification of coronary calcification as well as detection of coronary artery stenoses after contrast enhancement. Moreover, cardiac CT offers high-resolution morphologic and functional imaging of cardiac structures which is valuable for various structural heart disease interventions and electrophysiology procedures. So far, only limited data exist regarding the spectrum of indications, image acquisition parameters as well as results and clinical consequences of cardiac CT examinations using state-of-the-art CT systems in experienced centers. Twelve cardiology centers with profound expertise in cardiovascular imaging participated in the German Cardiac CT Registry. Criteria for participation included adequate experience in cardiac CT as well of the availability of a 64-slice or newer CT system. Between 2009 and 2014, 7061 patients were prospectively enrolled. For all cardiac CT examinations, patient parameters, procedural data, indication and clinical consequences of the examination were documented. Mean patient age was 61 ± 12 years, 63% were males. The majority (63%) of all cardiac CT examinations were performed in an outpatient setting, 37% were performed during an inpatient stay. 91% were elective and 9% were scheduled in an acute setting. In most examinations (48%), reporting was performed by cardiologists, in 4% by radiologists and in 47% of the cases as a consensus reading. Cardiac CT was limited to native acquisitions for assessment of coronary artery calcification in 9% of patients, only contrast-enhanced coronary CT angiography was performed in 16.6% and combined native and contrast-enhanced coronary CT angiography was performed in 57.7% of patients. Non-coronary cardiac CT examinations constituted 16.6% of all cases. Coronary artery calcification assessment was performed using prospectively ECG-triggered acquisition in 76.9% of all cases. The median dose length product (DLP) was 42mGycm (estimated effective radiation dose of 0.6mSv). Coronary CT angiography was performed using prospectively ECG-triggered acquisition in 77.3% of all cases. Tube voltage was 120kV in 67.8% of patients and 100kV in 30.7% of patients, with a resultant median DLP of 256mGycm (estimated effective dose of 3.6mSv). Clinical consequences of cardiac CT were as follows: in 46.8% of the cases, invasive coronary angiography could be avoided; ischemia testing was recommended in 4.7% of the cases, invasive coronary angiography was recommended in 16.4% of the cases and change in medication in 21.6% of the examinations. Cardiac CT is performed in the majority of patients for non-invasive evaluation of the coronary arteries. CT frequently resulted in medication change, and otherwise planned downstream testing including invasive angiography could be avoided in a high percentage of patients. Radiation exposure in experienced centers is relatively low.

Detection and quantification of coronary calcium from dual energy chest x-rays: Phantom feasibility study.

We have demonstrated the ability to identify coronary calcium, a reliable biomarker of coronary artery disease, using nongated, 2-shot, dual energy (DE) chest x-ray imaging. Here we will use digital simulations, backed up by measurements, to characterize DE calcium signals and the role of potential confounds such as beam hardening, x-ray scatter, cardiac motion, and pulmonary artery pulsation. For the DE calcium signal, we will consider quantification, as compared to CT calcium score, and visualization. We created stylized and anatomical digital 3D phantoms including heart, lung, coronary calcium, spine, ribs, pulmonary artery, and adipose. We simulated high and low kVp x-ray acquisitions with x-ray spectra, energy dependent attenuation, scatter, ideal detector, and automatic exposure control (AEC). Phantoms allowed us to vary adipose thickness, cardiac motion, etc. We used specialized dual energy coronary calcium (DECC) processing that includes corrections for scatter and beam hardening. Beam hardening over a wide range of adipose thickness (0-30 cm) reduced the change in intensity of a coronary artery calcification (ΔICAC ) by < 3% in DECC images. Scatter correction errors of ±50% affected the calcium signal (ΔICAC ) in DECC images ±9%. If a simulated pulmonary artery fills with blood between exposures, it can give rise to a residual signal in DECC images, explaining pulmonary artery visibility in some clinical images. Residual misregistration can be mostly compensated by integrating signals in an enlarged region encompassing registration artifacts. DECC calcium score compared favorably to CT mass and volume scores over a number of phantom perturbations. Simulations indicate that proper DECC processing can faithfully recover coronary calcium signals. Beam hardening, errors in scatter estimation, cardiac motion, calcium residual misregistration etc., are all manageable. Simulations are valuable as we continue to optimize DE coronary calcium image processing and quantitative analysis.