Prognostic significance of subtle coronary calcification in patients with zero coronary artery calcium score: From the CONFIRM registry

Influence of deep learning-based super-resolution reconstruction on Agatston score

OBJECTIVE

To evaluate the impact of deep learning-based super-resolution reconstruction (DLSRR) on image quality and Agatston score.

METHODS

Consecutive patients who underwent cardiac CT, including unenhanced CT for Agatston scoring, were enrolled. Four types of non-contrast CT images were reconstructed using filtered back projection (FBP) and three strengths of DLSRR. Image quality was assessed by measuring image noise, signal-to-noise ratio (SNR) of the aorta, contrast-to-noise ratio (CNR), and edge rise slope (ERS) of coronary artery calcium (CAC). Agatston score and CAC volume were also measured. These results were compared among the four CT datasets. Patients were categorized into four risk levels based on the Coronary Artery Calcium Data and Reporting System (CAC-DRS), and the concordance rate between FBP and DLSRR classifications was evaluated.

RESULTS

For the 111 patients enrolled, DLSRR significantly reduced image noise (p < 0.001) and improved SNR and CNR (p < 0.001), with stronger effects at higher DLSRR strengths (p < 0.01). ERS was significantly enhanced using DLSRR compared with FBP (p < 0.001), whereas there was no significant difference among the three strengths of DLSRR (p = 0.90-0.98). Agatston score and CAC volume were not significantly affected by DLSRR (p = 0.952 and 0.901, respectively). The concordance rate of CAC-DRS classification between FBP and DLSRR was 93%.

CONCLUSION

DLSRR significantly improves image quality by reducing noise and enhancing sharpness without significantly altering Agatston scores or CAC volumes. The concordance rate of CAC-DRS classification with FBP was high, although some reclassifications were observed.

KEY POINTS

Question The utility of deep learning-based super-resolution reconstruction (DLSRR) in coronary CT angiography is well known, but its impact on the Agatston score remains unclear. Findings DLSRR significantly improved image quality without altering the Agatston scores, but some reclassifications of Coronary Artery Calcium Data and Reporting System (CAC-DRS) were observed. Clinical relevance DLSRR should be cautiously used in clinical settings owing to the occurrence of some cases of CAC-DRS reclassification.

Coronary Artery Calcium Density and Risk of Cardiovascular Events: A Systematic Review and Meta-Analysis

BACKGROUND

There is increasing evidence that coronary artery calcium (CAC) density is inversely associated with plaque vulnerability and atherosclerotic cardiovascular disease risk.

OBJECTIVES

A systematic review and meta-analysis were performed to examine the predictive value of CAC density for future cardiovascular events in asymptomatic individuals undergoing noncontrast CAC scoring computed tomography.

METHODS

Electronic databases were searched for studies reporting CAC density and subsequent cardiovascular disease (CVD) or coronary heart disease (CHD) events. Two independent reviewers performed data extraction. Random-effects models were used to estimate pooled HRs and 95% CIs. Subgroup analyses were performed with studies stratified by CVD vs CHD events and by statin use.

RESULTS

Of 5,029 citations, 5 studies with 6 cohorts met inclusion criteria. In total, 1,309 (6.1%) cardiovascular events occurred in 21,346 participants with median follow-up ranging from 5.2 to 16.7 years. Higher CAC density was inversely associated with risk of cardiovascular events following adjustment for clinical risk factors and CAC volume (HR: 0.80 per SD of density [95% CI: 0.72-0.89]; P < 0.01; I2 = 0%). There was no significant difference in the pooled HRs for CVD vs CHD events (HR: 0.80 per SD [95% CI: 0.71-0.90] vs 0.74 per SD [95% CI: 0.59-0.94] respectively; P = 0.59). The protective association between CAC density and event risk persisted among statin-naive patients (HR: 0.79 per SD [95% CI: 0.70-0.89]; P < 0.01) but not statin-treated patients (HR: 0.97 per SD [95% CI: 0.77-1.22]; P = 0.78); the test for interaction indicated no significant between-group differences (P = 0.12).

CONCLUSIONS

Higher CAC density is associated with a lower risk of cardiovascular events when adjusted for risk factors and CAC volume. Future work may expand the contribution of CAC density in CAC scoring, and enhance its role in CVD risk assessment, treatment, and prevention.

Phenotyping atherosclerotic plaque and perivascular adipose tissue: signalling pathways and clinical biomarkers in atherosclerosis

Computed tomography coronary angiography provides a non-invasive evaluation of coronary artery disease that includes phenotyping of atherosclerotic plaques and the surrounding perivascular adipose tissue (PVAT). Image analysis techniques have been developed to quantify atherosclerotic plaque burden and morphology as well as the associated PVAT attenuation, and emerging radiomic approaches can add further contextual information. PVAT attenuation might provide a novel measure of vascular health that could be indicative of the pathogenetic processes implicated in atherosclerosis such as inflammation, fibrosis or increased vascularity. Bidirectional signalling between the coronary artery and adjacent PVAT has been hypothesized to contribute to coronary artery disease progression and provide a potential novel measure of the risk of future cardiovascular events. However, despite the development of more advanced radiomic and artificial intelligence-based algorithms, studies involving large datasets suggest that the measurement of PVAT attenuation contributes only modest additional predictive discrimination to standard cardiovascular risk scores. In this Review, we explore the pathobiology of coronary atherosclerotic plaques and PVAT, describe their phenotyping with computed tomography coronary angiography, and discuss potential future applications in clinical risk prediction and patient management.

Diagnostic utility of coronary artery calcium score percentiles and categories to exclude abnormal scans and relevant ischemia in rubidium positron emission tomography

Background

Despite clinical suspicion, most non-invasive ischemia tests for coronary artery disease (CAD) reveal unremarkable results. Patients with a coronary artery calcium score (CACS) of zero rarely have an abnormal positron emission tomography (PET) and could be deferred from further testing. However, most patients have some extent of coronary calcification.

Objectives

CACS percentiles could be useful to exclude abnormal perfusion in patients with CACS >0, but data from patients with 82Rb PET are lacking. The aim of this study was to assess the diagnostic utility of CACS percentiles in comparison to zero calcium and absolute CACS classes.

Methods

Consecutive patients with suspected CAD (n = 1,792) referred for 82Rb PET were included and analyzed for abnormal PET (SSS ≥4) and relevant ischemia (>10% myocardium). Test characteristics were calculated.

Results

The mean age was 65 ± 11 years, 43% were female, and typical angina was reported in 21%. Abnormal PET/relevant ischemia (>10%) were observed in 19.8%/9.3%. Overall, the sensitivity/negative predictive value (NPV) of a <25th percentile CACS to rule out abnormal PET and relevant ischemia were 93.0%/95.7% and 98.2%/99.5%, respectively. The sensitivity/NPV of CACS 1-9 to rule out abnormal PET and relevant ischemia were 96.0%/91.8% and 97.6%/97.6%, respectively. Except for patients <50 years old, sensitivity for abnormal PET was >90.9% in all age groups.

Conclusion

In patients >50 years, the <25th percentile and CACS 1-9 had good test characteristics to rule out abnormal PET and relevant ischemia (>10%). They could be used to extend the scope of application of CACS 0 by 8%-10% to 32%-34% overall of patients who could be deferred from further testing.

Rationale and Design of SCOT-HEART 2 Trial: CT Angiography for the Prevention of Myocardial Infarction

Coronary artery disease continues to be the leading cause of death globally. Identifying patients who are at risk of coronary artery disease remains a public health priority. At present, the focus of cardiovascular disease prevention relies heavily on probabilistic risk scoring despite no randomized controlled trials demonstrating their efficacy. The concept of using imaging to guide preventative therapy is not new, but has previously focused on indirect measures such as carotid intima-media thickening or coronary artery calcification. In recent trials, patients found to have coronary artery disease on computed tomography (CT) coronary angiography were more likely to be started on preventative therapy and had lower rates of cardiac events. This led to the design of the SCOT-HEART 2 (Scottish Computed Tomography of the Heart 2) trial, which aims to determine whether screening with the use of CT coronary angiography is more clinically effective than cardiovascular risk scoring to guide the use of primary preventative therapies and reduce the risk of myocardial infarction.

Machine learning-based coronary artery calcium score predicted from clinical variables as a prognostic indicator in patients referred for invasive coronary angiography

OBJECTIVES

Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance.

METHODS

This retrospective study enrolled patients who underwent coronary CT angiography and subsequent invasive coronary angiography. Multiple ML algorithms were used to train the models for predicting severe coronary calcification (cardiac CT-measured coronary artery calcium [CT-CAC] score ≥ 400). The ML-based CAC (ML-CAC) score derived from the ML predictive probability was stratified into quartiles for prognostic analysis. The primary endpoint was a composite of all-cause death, nonfatal myocardial infarction, or nonfatal stroke.

RESULTS

Overall, 5785 patients were divided into training (80%) and test sets (20%). For clinical practicability, we selected the nine-feature support vector machine model with good and satisfactory performance regarding both discrimination and calibration based on five repetitions of the 10-fold cross-validation in the training set (mean AUC = 0.715, Brier score = 0.202), and based on the test in the test set (AUC = 0.753, Brier score = 0.191). In the test set cohort (n = 1137), the primary endpoint was observed in 50 (4.4%) patients during a median 2.8 years' follow-up. The ML-CAC system was significantly associated with an increased risk of the primary endpoint (adjusted hazard ratio for trend 2.26, 95% CI 1.35-3.79, p = 0.002). There was no significant difference in the prognostic value between the ML-CAC and CT-CAC systems (C-index, 0.67 vs. 0.69; p = 0.618).

CONCLUSION

ML-CAC score predicted from clinical variables can serve as a novel prognostic indicator in patients referred for invasive coronary angiography.

CLINICAL RELEVANCE STATEMENT

In patients referred for invasive coronary angiography who have not undergone preoperative CT-measured coronary artery calcium scoring, machine learning-based coronary artery calcium score assessment can serve as an alternative for predicting the prognosis.

KEY POINTS

• The coronary artery calcium (CAC) score, a solid prognostic indicator, can be predicted using non-CT methods. • We developed a machine learning (ML)-CAC model utilising nine clinical variables to predict severe coronary calcification. • The ML-CAC system offers significant prognostic value in patients referred for invasive coronary angiography.

Improved Detection of Small and Low-Density Plaques in Virtual Noncontrast Imaging-based Calcium Scoring at Photon-Counting Detector CT

Purpose To investigate the impact of plaque size and density on virtual noncontrast (VNC)-based coronary artery calcium scoring (CACS) using photon-counting detector CT and to provide safety net reconstructions for improved detection of subtle plaques in patients whose VNC-based CACS would otherwise be erroneously zero when compared with true noncontrast (TNC)-based CACS. Materials and Methods In this prospective study, CACS was evaluated in a phantom containing calcifications with different diameters (5, 3, and 1 mm) and densities (800, 400, and 200 mg/cm3) and in participants who underwent TNC and contrast-enhanced cardiac photon-counting detector CT (July 2021-March 2022). VNC images were reconstructed at different virtual monoenergetic imaging (55-80 keV) and quantum iterative reconstruction (QIR) levels (QIR,1-4). TNC scans at 70 keV with QIR off served as the reference standard. In vitro CACS was analyzed using standard settings (3.0-mm sections, kernel Qr36, 130-HU threshold). Calcification detectability and CACS of small and low-density plaques were also evaluated using 1.0-mm sections, kernel Qr44, and 120- or 110-HU thresholds. Safety net reconstructions were defined based on background Agatston scores and evaluated in vivo in TNC plaques initially nondetectable using standard VNC reconstructions. Results The in vivo cohort included 63 participants (57.8 years ± 15.5 [SD]; 37 [59%] male, 26 [41%] female). Correlation and agreement between standard CACSVNC and CACSTNC were higher in large- and medium-sized and high- and medium-density than in low-density plaques (in vitro: intraclass correlation coefficient [ICC] ≥ 0.90; r > 0.9 vs ICC = 0.20-0.48; r = 0.5-0.6). Small plaques were not detectable using standard VNC reconstructions. Calcification detectability was highest using 1.0-mm sections, kernel Qr44, 120- and 110-HU thresholds, and QIR level of 2 or less VNC reconstructions. Compared with standard VNC, using safety net reconstructions (55 keV, QIR 2, 110-HU threshold) for in vivo subtle plaque detection led to higher detection (increased by 89% [50 of 56]) and improved correlation and agreement of CACSVNC with CACSTNC (in vivo: ICC = 0.51-0.61; r = 0.6). Conclusion Compared with TNC-based calcium scoring, VNC-based calcium scoring was limited for small and low-density plaques but improved using safety net reconstructions, which may be particularly useful in patients with low calcium scores who would otherwise be treated based on potentially false-negative results. Keywords: Coronary Artery Calcium CT, Photon-Counting Detector CT, Virtual Noncontrast, Plaque Size, Plaque Density Supplemental material is available for this article. © RSNA, 2024.

Cardiac CT: Competition, complimentary or confounder

Coronary CT angiography (CCTA) has been gradually adopted into clinical practice over the last two decades. CCTA has high diagnostic accuracy, prognostic value, and unique features such as assessment of plaque composition. CCTA-derived functional assessment techniques such as fractional flow reserve and CT perfusion are also available and can increase the diagnostic specificity of the modality. These properties propound CCTA as a competitor of functional testing in diagnosis of obstructive CAD, however, utilizing CCTA in a concomitant fashion to potentiate the performance of the latter can lead to better patient care and may provide more accurate prognostic information. Although multiple diagnostic challenges such as evaluation of calcified segments, stents, and small distal vessels still exist, the technologic developments in hardware as well as growing incorporation of artificial intelligence to daily practice are all set to augment the diagnostic and prognostic role of CCTA in cardiovascular disorders.

Quantitative analysis of aortic Na[18F]F uptake in macrocalcifications and microcalcifications in PET/CT scans

BACKGROUND

Currently, computed tomography (CT) is used for risk profiling of (asymptomatic) individuals by calculating coronary artery calcium scores. Although this score is a strong predictor of major adverse cardiovascular events, this method has limitations. Sodium [18F]fluoride (Na[18F]F) positron emission tomography (PET) has shown promise as an early marker for atherosclerotic progression. However, evidence on Na[18F]F as a marker for high-risk plaques is limited, particularly on its presentation in clinical PET/CT. Besides, the relationship between microcalcifications visualized by Na[18F]F PET and macrocalcifications detectable on CT is unknown.

PURPOSE

To establish a match/mismatch score in the aorta between macrocalcified plaque content on CT and microcalcification Na[18F]F PET uptake.

METHODS

Na[18F]F-PET/CT scans acquired in our centre in 2019-2020 were retrospectively collected. The aorta of each low-dose CT was manually segmented. Background measurements were placed in the superior vena cava. The vertebrae were automatically segmented using an open-source convolutional neural network, dilated with 10 mm, and subtracted from the aortic mask. Per patient, calcium and Na[18F]F-hotspot masks were retrieved using an in-house developed algorithm. Three match/mismatch analyses were performed: a population analysis, a per slice analysis, and an overlap score. To generate a population image of calcium and Na[18F]F hotspot distribution, all aortic masks were aligned. Then, a heatmap of calcium HU and Na[18F]F-uptake on the surface was obtained by outward projection of HU and uptake values from the centerline. In each slice of the aortic wall of each patient, the calcium mass score and target-to-bloodpool ratios (TBR) were calculated within the calcium masks, in the aortic wall except the calcium masks, and in the aortic wall in slices without calcium. For the overlap score, three volumes were identified in the calcium and Na[18F]F masks: volume of PET (PET+/CT-), volume of CT (PET-/CT+), and overlapping volumes (PET+/CT+). A Spearman's correlation analysis with Bonferroni correction was performed on the population image, assessing the correlation between all HU and Na[18F]F vertex values. In the per slice analysis, a paired Wilcoxon signed-rank test was used to compare TBR values within each slice, while an ANOVA with post-hoc Kruskal-Wallis test was employed to compare TBR values between slices. p-values < 0.05 were considered significant.

RESULTS

In total, 186 Na[18F]F-PET/CT scans were included. A moderate positive exponential correlation was observed between total aortic calcium mass and total aortic TBR (r = 0.68, p < 0.001). A strong positive correlation (r = 0.77, p < 0.0001) was observed between CT values and Na[18F]F values on the population image. Significantly higher TBR values were found outside calcium masks than inside calcium masks (p < 0.0001). TBR values in slices where no calcium was present, were significantly lower compared with outside calcium and inside calcium (both p < 0.0001). On average, only 3.7% of the mask volumes were overlapping.

CONCLUSIONS

Na[18F]F-uptake in the aorta behaves similarly to macrocalcification detectable on CT. Na[18F]F-uptake values are also moderately correlated to calcium mass scores (match). Higher uptake values were found just outside macrocalcification masks instead of inside the macrocalcification masks (mismatch). Also, only a small percentage of the Na[18F]F-uptake volumes overlapped with the calcium volumes (mismatch).

Risk stratifying individuals with zero, minimal, and mild coronary artery calcium for cardiovascular disease by determining coronary plaque burden

BACKGROUND AND AIMS

Use of coronary artery calcium (CAC) continues to expand, and several different categories of risk have been developed. Some categorize CAC as <10, 11-100 and ​> ​100, while others use CAC ​= ​0,1-10, 11-100 and ​> ​100 as categories. We sought to evaluate the plaque burden in patients with CAC 0, 1-10 and 11-100 to evaluate the best use of CAC scoring for risk assessment.

METHODS

Patients were recruited from existing prospective CCTA trials with CAC scores ≤100 and quantitative coronary plaque analysis (QAngio, Medis). CAC was categorized into three groups: zero (CAC ​= ​0), minimal (CAC 1-10), and mild (CAC 11-100). Plaque levels (low attenuated, fibrous, fibro-fatty, dense calcified, total non-calcified) were assessed using multivariable linear regression adjusted for cardiovascular risk factors (age, ethnicity, BMI, gender, hypertension, dyslipidemia, diabetes mellitus, past smoking).

RESULTS

378 subjects were included, with an average age of 53.9 ​± ​10.7 years and 53 ​% female. Among them, 51 ​% had 0 CAC, 16 ​% had minimal CAC (scores 1-10), and 33 ​% had mild CAC (scores 11-100). The minimal and mild CAC groups were significantly older, with higher rates of diabetes, hypertension, and hyperlipidemia. Multivariable analysis found no significant difference in low attenuated, fibro-fatty, and dense calcified plaque levels between the minimal and zero CAC groups. However, minimal CAC subjects had significantly higher fibrous, total non-calcified, and total plaque volumes than zero CAC. All plaque types were significantly higher in the mild group when comparing mild CAC to minimal CAC.

CONCLUSION

Individuals with minimal calcium scores (1-10) had greater noncalcified coronary plaque (NCAP) and total plaque volume than individuals with a calcium score of zero. The increased presence of NCAP and total plaque volume in the minimal CAC (1-10) is clinically significant and place those patients at higher coronary vascular disease (CVD) risk than individuals with absent CAC (CAC ​= ​zero). Therefore, the use of CAC ​= ​0, 1-10 and 11-100 is prudent to better categorize CVD risk.

Association of coronary artery calcium with heart rate variability in the Brazilian Longitudinal Study of Adult Health - ELSA-Brasil

Current data shows that the autonomic and vascular systems can influence each other. However, only a few studies have addressed this association in the general population. We aimed to investigate whether heart rate variability (HRV) was associated with coronary artery calcium (CAC) in a cross-sectional analysis of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). We examined baseline data from 3138 participants (aged 35 to 74 years) without previous cardiovascular disease who underwent CAC score assessment and had validated HRV recordings. Prevalent CAC was defined as a CAC score>0, and HRV analyses were performed over 5-min segments. We detected CAC score>0 in 765 (24.4%) participants. Subgroup analyses in older participants (≥49 years) adjusted for sociodemographic and clinical variables revealed that CAC score>0 was associated with lower values of standard deviation of NN intervals (SDNN) (odds ratio [OR]=1.32; 95%CI: 1.05,1.65), root mean square of successive differences between adjacent NN intervals (RMSSD) (OR=1.28; 95%CI: 1.02,1.61), and low frequency (LF) (OR=1.53, 95%CI: 1.21,1.92). Interaction analysis between HRV indices and sex in age-stratified groups revealed significant effect modification: women showed increased OR for prevalent CAC in the younger group, while for men, the associations were in the older group. In conclusion, participants aged ≥49 years with low SDNN, RMSSD, and LF values were more likely to present prevalent CAC, suggesting a complex interaction between these markers in the pathogenesis of atherosclerosis. Furthermore, our results suggested that the relationship between CAC and HRV might be sex- and age-related.

Identification and Validation of Key Gene Modules and Pathways in Coronary Artery Disease Development and Progression

The development and progression of atherosclerosis represent a chronic process involving complex molecular interactions. Therefore, identifying the potential hub genes and pathways contributing to coronary artery disease (CAD) development is essential for understanding its underlying molecular mechanisms. To this end, we performed transcriptome analysis of peripheral venous blood collected from 100 patients who were divided into four groups according to disease severity, including 27 patients in the atherosclerosis group, 22 patients in the stable angina group, 35 patients in the acute myocardial infarction group, and 16 controls. Weighted gene co-expression network analysis was performed using R programming. Significant module-trait correlations were identified according to module membership and genetic significance. Metascape was used for the functional enrichment of differentially expressed genes between groups, and the hub genes were identified via protein-protein interaction network analysis. The hub genes were further validated by analyzing Gene Expression Omnibus (GSE48060 and GSE141512) datasets. A total of 9,633 messenger ribonucleic acids were detected in three modules, among which the blue module was highly correlated with the Gensini score. The hub genes were significantly enriched in the myeloid leukocyte activation pathway, suggesting its important role in the progression of atherosclerosis. Among these genes, the Mediterranean fever gene (MEFV) may play a key role in the progression of atherosclerosis and CAD severity.

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.

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine

Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow. An interdisciplinary, multicentric team of medical experts and computer scientists designed a pipeline, comprising AI-based tools for the automated detection, quantification and characterization of the most common pulmonary, metabolic, cardiovascular and musculoskeletal comorbidities in chest computed tomography (CT). To provide a comprehensive evaluation of each patient, a multidimensional workflow was established with algorithms operating synchronously on a decentralized Joined Imaging Platform (JIP). The results of each patient are transferred to a dedicated database and summarized as a structured report with reference to available reference values and annotated sample images of detected pathologies. Hence, this tool allows for the comprehensive, large-scale analysis of imaging-biomarkers of comorbidities in chest CT, first in science and then in clinical routine. Moreover, this tool accommodates the quantitative analysis and classification of each pathology, providing integral diagnostic and prognostic value, and subsequently leading to improved preventive patient care and further possibilities for future studies.

Progostic value of coronary artery calcium scores from 1.5 mm slice reconstructions of electrocardiogram-gated computed tomography scans in asymptomatic individuals

It is unknown whether the thinner slice reconstruction has added value relative to 3 mm reconstructions in predicting major adverse cardiac events (MACEs). This retrospective study included 550 asymptomatic individuals who underwent cardiac CT. Coronary artery calcium (CAC) scores and severity categories were assessed from 1.5 and 3 mm scans. CAC scores obtained from 1.5 and 3 mm scans were compared using Wilcoxon signed-rank tests. Cox proportional hazard models were developed to predict MACEs based on the degree of coronary artery stenosis on coronary CT angiography and the presence of CAC on both scans. Model performances were compared using the time-dependent ROC curve and integrated area under the curve (iAUC) methods. The CAC scores obtained from 1.5 mm scans were significantly higher than those from 3 mm scans (median, interquartile range 4.5[0–71] vs. 0[0–48.4]; p < 0.001). Models showed no difference in predictive accuracy of the presence of CAC between 1.5 and 3 mm scans (iAUC, 0.625 vs. 0.672). In conclusion, CAC scores obtained from 1.5 mm scans are significantly higher than those from 3 mm scans, but do not provide added prognostic value relative to 3 mm scans.

Coronary Artery Calcium Scoring: Toward a New Standard

OBJECTIVES

Although the Agatston score is a commonly used quantification method, rescan reproducibility is suboptimal, and different CT scanners result in different scores. In 2007, McCollough et al (Radiology 2007;243:527-538) proposed a standard for coronary artery calcium quantification. Advancements in CT technology over the last decade, however, allow for improved acquisition and reconstruction methods. This study aims to investigate the feasibility of a reproducible reduced dose alternative of the standardized approach for coronary artery calcium quantification on state-of-the-art CT systems from 4 major vendors.

MATERIALS AND METHODS

An anthropomorphic phantom containing 9 calcifications and 2 extension rings were used. Images were acquired with 4 state-of-the-art CT systems using routine protocols and a variety of tube voltages (80-120 kV), tube currents (100% to 25% dose levels), slice thicknesses (3/2.5 and 1/1.25 mm), and reconstruction techniques (filtered back projection and iterative reconstruction). Every protocol was scanned 5 times after repositioning the phantom to assess reproducibility. Calcifications were quantified as Agatston scores.

RESULTS

Reducing tube voltage to 100 kV, dose to 75%, and slice thickness to 1 or 1.25 mm combined with higher iterative reconstruction levels resulted in an on average 36% lower intrascanner variability (interquartile range) compared with the standard 120 kV protocol. Interscanner variability per phantom size decreased by 34% on average. With the standard protocol, on average, 6.2 ± 0.4 calcifications were detected, whereas 7.0 ± 0.4 were detected with the proposed protocol. Pairwise comparisons of Agatston scores between scanners within the same phantom size demonstrated 3 significantly different comparisons at the standard protocol (P < 0.05), whereas no significantly different comparisons arose at the proposed protocol (P > 0.05).

CONCLUSIONS

On state-of-the-art CT systems of 4 different vendors, a 25% reduced dose, thin-slice calcium scoring protocol led to improved intrascanner and interscanner reproducibility and increased detectability of small and low-density calcifications in this phantom. The protocol should be extensively validated before clinical use, but it could potentially improve clinical interscanner/interinstitutional reproducibility and enable more consistent risk assessment and treatment strategies.

Detection of small coronary calcifications in patients with Agatston coronary artery calcium score of zero

BACKGROUND

A coronary artery calcium score (CACS) of 0 is associated with a very low risk of cardiac event. However, the Agatston CACS may fail to detect very small or less dense calcifications. We investigated if an alteration of the Agatston criteria would affect the ability to detect such plaques.

METHODS

We evaluated 322 patients, 161 who had a baseline scan with CACS ​= ​0 and a follow-up scan with CACS>0 and 161 with two serial CACS ​= ​0 scans (control group), to identify subtle calcification not detected in the baseline scan because it was not meeting the Agatston size and HU thresholds (≥1 ​mm² and ≥130HU). Size threshold was set to <1 ​mm² and the HU threshold modified in a stepwise manner to 120, 110, 100 and 90. New lesions were classified as true positive or false positive(noise) using the follow-up scan.

RESULTS

We identified 69 visually suspected subtle calcified lesions in 65/322 (20.2%) patients with CAC ​= ​0 by the Agatston criteria. When size threshold was set as <1 ​mm² and HU ​≥ ​130, 36 lesions scored CACS>0, 34 (94.4%) true positive and 2 (5.6%) false positive. When decrease in HU (120HU, 110HU, 100HU, and 90HU) threshold was added to the reduced size threshold, the number of lesions scoring>0 increased (46, 55, 59, and 69, respectively) at a cost of increased false positive rate (8.7%, 20%, 22%, and 30.4% respectively). Eliminating size or both size and HU threshold to ≥120HU correctly reclassified 9.6% and 12.1% of patients respectively.

CONCLUSION

Eliminating size and reducing HU thresholds to ≥120HU improved the detection of subtle calcification when compared to the Agatston CACS method.