Coronary calcium screening with dual-source CT: reliability of ungated, high-pitch chest CT in comparison with dedicated calcium-scoring CT

Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?

PURPOSE OF REVIEW

This review evaluates how Artificial Intelligence (AI) enhances atherosclerotic cardiovascular disease (ASCVD) risk assessment, allows for opportunistic screening, and improves adherence to guidelines through the analysis of unstructured clinical data and patient-generated data. Additionally, it discusses strategies for integrating AI into clinical practice in preventive cardiology.

RECENT FINDINGS

AI models have shown superior performance in personalized ASCVD risk evaluations compared to traditional risk scores. These models now support automated detection of ASCVD risk markers, including coronary artery calcium (CAC), across various imaging modalities such as dedicated ECG-gated CT scans, chest X-rays, mammograms, coronary angiography, and non-gated chest CT scans. Moreover, large language model (LLM) pipelines are effective in identifying and addressing gaps and disparities in ASCVD preventive care, and can also enhance patient education. AI applications are proving invaluable in preventing and managing ASCVD and are primed for clinical use, provided they are implemented within well-regulated, iterative clinical pathways.

Prevalence and clinical implications of coronary artery calcium scoring on non-gated thoracic computed tomography: a systematic review and meta-analysis

OBJECTIVES

Coronary artery calcifications (CACs) indicate the presence of coronary artery disease. CAC can be found on thoracic computed tomography (CT) conducted for non-cardiac reasons. This systematic review and meta-analysis of non-gated thoracic CT aims to assess the clinical impact and prevalence of CAC.

METHODS

Online databases were searched for articles assessing prevalence, demographic characteristics, accuracy and prognosis of incidental CAC on non-gated thoracic CT. Meta-analysis was performed using a random effects model.

RESULTS

A total of 108 studies (113,406 patients) were included (38% female). Prevalence of CAC ranged from 2.7 to 100% (pooled prevalence 52%, 95% confidence interval [CI] 46-58%). Patients with CAC were older (pooled standardised mean difference 0.88, 95% CI 0.65-1.11, p < 0.001), and more likely to be male (pooled odds ratio [OR] 1.95, 95% CI 1.55-2.45, p < 0.001), with diabetes (pooled OR 2.63, 95% CI 1.95-3.54, p < 0.001), hypercholesterolaemia (pooled OR 2.28, 95% CI 1.33-3.93, p < 0.01) and hypertension (pooled OR 3.89, 95% CI 2.26-6.70, p < 0.001), but not higher body mass index or smoking. Non-gated CT assessment of CAC had excellent agreement with electrocardiogram-gated CT (pooled correlation coefficient 0.96, 95% CI 0.92-0.98, p < 0.001). In 51,582 patients, followed-up for 51.6 ± 27.4 months, patients with CAC had increased all cause mortality (pooled relative risk [RR] 2.13, 95% CI 1.57-2.90, p = 0.004) and major adverse cardiovascular events (pooled RR 2.91, 95% CI 2.26-3.93, p < 0.001). When CAC was present on CT, it was reported in between 18.6% and 93% of reports.

CONCLUSION

CAC is a common, but underreported, finding on non-gated CT with important prognostic implications.

CLINICAL RELEVANCE STATEMENT

Coronary artery calcium is an important prognostic indicator of cardiovascular disease. It can be assessed on non-gated thoracic CT and is a commonly underreported finding. This represents a significant population where there is a potential missed opportunity for lifestyle modification recommendations and preventative therapies. This study aims to highlight the importance of reporting incidental coronary artery calcium on non-gated thoracic CT.

KEY POINTS

• Coronary artery calcification is a common finding on non-gated thoracic CT and can be reliably identified compared to gated-CT. • Coronary artery calcification on thoracic CT is associated with an increased risk of all cause mortality and major adverse cardiovascsular events. • Coronary artery calcification is frequently not reported on non-gated thoracic CT.

Performance of calcium quantifications on low-dose photon-counting detector CT with high-pitch: A phantom study

Purpose

To evaluate the performance of calcium quantification on photon-counting detector CT (PCD-CT) with high-pitch at low radiation doses compared to third-generation dual-source energy-integrating detector CT (EID-CT).

Materials and methods

The phantom with three calcium inserts (50, 100, and 300 mg of calcium per milliliter), with and without the elliptical outer layer, was evaluated using high-pitch (3.2) and standard pitch (0.8) on PCD-CT, and standard pitch on EID-CT. Scans were performed with different tube voltages (PCD-CT: 120 and 140 kilo-voltage peak [kVp]; EID-CT: 70/Sn150 and 100/Sn150 kVp) and four radiation doses (1, 3, 5, and, 10 milli-Gray [mGy]). Utilizing the true calcium concentrations (CCtrue) of the phantom as the gold standard references, regression equations for each kVp setting were formulated to convert CT attenuations (CaCT) into measured calcium concentrations (CCm). The correlation analysis between CaCT and CCtrue was performed. The percentage absolute bias (PAB) was calculated from the differences between CCm and CCtrue and used to analyze the effects of scanning parameters on calcium quantification accuracy.

Results

A strong correlation was found between CaCT and CCtrue on PCD-CT (r > 0.99) and EID-CT (r > 0.98). For high- and standard-pitch scans on PCD-CT, the accuracy of calcium quantification is comparable (p = 0.615): the median (interquartile range [IQR]) of PAB was 5.59% (2.79%-8.31%) and 4.87 % (2.62%-8.01%), respectively. The PAB median (IQR) was 7.43% (3.77%-11.75%) for EID-CT. The calcium quantification accuracy of PCD-CT is superior to EID-CT at the large phantom (5.46% [2.68%-9.55%] versus 9.01% [6.22%-12.74%]), and at the radiation dose of 1 mGy (4.43% [2.08%-8.59%] versus 13.89% [8.93%-23.09%]) and 3 mGy (4.61% [2.75%-6.51%] versus 9.97% [5.17%-14.41%]), all p < 0.001.

Conclusions

Calcium quantification using low-dose PCD-CT with high-pitch scanning is feasible and accurate, and superior to EID-CT.

Opportunistic Screening for Coronary Artery Disease: An Untapped Population Health Resource

BACKGROUND

Coronary artery disease is the leading cause of death in the United States. At-risk asymptomatic adults are eligible for screening with electrocardiogram-gated coronary artery calcium (CAC) CT, which aids in risk stratification and management decision-making. Incidental CAC (iCAC) is easily quantified on chest CT in patients imaged for noncardiac indications; however, radiologists do not routinely report the finding.

OBJECTIVE

To determine the clinical significance of CAC identified incidentally on routine chest CT performed for noncardiac indications.

DESIGN

An informationist developed search strategies in MEDLINE, Embase, and SCOPUS, and two reviewers independently screened results at both the abstract and full text levels. Data extracted from eligible articles included age, rate of iCAC identification, radiologist reporting frequency, impact on downstream medical management, and association of iCAC with patient outcomes.

RESULTS

From 359 unique citations, 83 research publications met inclusion criteria. The percentage of patients with iCAC ranged from 9% to 100%. Thirty-one investigations measured association(s) between iCAC and cardiovascular morbidity and mortality, and 29 identified significant correlations, including nonfatal myocardial infarction, fatal myocardial infarction, major adverse cardiovascular event, cardiovascular death, and all-cause death. iCAC was present in 20% to 100% of the patients in these cohorts, but when present, iCAC was reported by radiologists in only 31% to 44% of cases. Between 18% and 77% of patients with iCAC were not on preventive medications in studies that reported these data. Seven studies measured the effect of reporting on guideline directed medical therapy, and 5 (71%) reported an increase in medication prescriptions after diagnosis of iCAC, with one confirming reductions in low-density lipoprotein levels. Twelve investigations reported good concordance between CAC grade on noncardiac CT and Agatston score on electrocardiogram-gated cardiac CT, and 10 demonstrated that artificial intelligence tools can reliably calculate an Agatston score on noncardiac CT.

CONCLUSION

A body of evidence demonstrates that patients with iCAC on routine chest CT are at risk for cardiovascular disease events and death, but they are often undiagnosed. Uniform reporting of iCAC in the chest CT impression represents an opportunity for radiology to contribute to early identification of high-risk individuals and potentially reduce morbidity and mortality. AI tools have been validated to calculate Agatston score on routine chest CT and hold the best potential for facilitating broad adoption.

Measurement and Application of Incidentally Detected Coronary Calcium: JACC Review Topic of the Week

Coronary artery calcium (CAC) scoring is a powerful tool for atherosclerotic cardiovascular disease risk stratification. The nongated, noncontrast chest computed tomography scan (NCCT) has emerged as a source of CAC characterization with tremendous potential due to the high volume of NCCT scans. Application of incidental CAC characterization from NCCT has raised questions around score accuracy, standardization of methodology including the possibility of deep learning to automate the process, and the risk stratification potential of an NCCT-derived score. In this review, the authors aim to summarize the role of NCCT-derived CAC in preventive cardiovascular health today as well as explore future avenues for eventual clinical applicability in specific patient populations and broader health systems.

A machine learning approach to predicting vascular calcification risk of type 2 diabetes: A retrospective study

BACKGROUND

Recently, patients with type 2 diabetes mellitus (T2DM) have experienced a higher incidence and severer degree of vascular calcification (VC), which leads to an increase in the incidence and mortality of vascular complications in patients with T2DM.

HYPOTHESIS

To construct and validate prediction models for the risk of VC in patients with T2DM.

METHODS

Twenty-three baseline demographic and clinical characteristics were extracted from the electronic medical record system. Ten clinical features were screened with least absolute shrinkage and selection operator method and were used to develop prediction models based on eight machine learning (ML) algorithms (k-nearest neighbor [k-NN], light gradient boosting machine, logistic regression [LR], multilayer perception [(MLP], Naive Bayes [NB], random forest [RF], support vector machine [SVM], XGBoost [XGB]). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, and precision.

RESULTS

A total of 1407 and 352 patients were retrospectively collected in the training and test sets, respectively. Among the eight models, the AUC value in the NB model was higher than the other models (NB: 0.753, LGB: 0.719, LR: 0.749, MLP: 0.715, RF: 0.722, SVM: 0.689, XGB:0.707, p < .05 for all). The k-NN model achieved the highest sensitivity of 0.75 (95% confidence interval [CI]: 0.633-0.857), the MLP model achieved the highest accuracy of 0.81 (95% CI: 0.767-0.852) and specificity of 0.875 (95% CI: 0.836-0.912).

CONCLUSIONS

This study developed a predictive model of VC based on ML and clinical features in type 2 diabetic patients. The NB model is a tool with potential to facilitate clinicians in identifying VC in high-risk patients.

Low-dose, high-pitch, spiral (FLASH) mode versus conventional sequential method for coronary artery calcium scoring: A derivation-validation study

Introduction

The present study sought to compare the diagnostic accuracy and radiation dose of ECG-gated, ultra-fast, low-dose, high-pitch, spiral (FLASH) mode versus conventional, ECG-gated, sequential coronary artery calcium (CAC) scoring in patients with suspected coronary artery disease (CAD).

Methods

The study included 120 patients who underwent both conventional scanning and FLASH mode scanning and were subdivided into derivation and validation cohorts. In the conventional sequential (step-and-shoot) protocol, prospective ECG-gated, non-contrast acquisition was performed at 70% of R-R interval. The spiral (FLASH) mode utilized a high-pitch and high-speed gantry rotation scanning mode where acquisition of the entire heart was done within a single cardiac cycle with prospective ECG-gating at 70% of R-R interval.

Results

Correlation between CAC scores derived from conventional (cCAC) and FLASH mode (fCAC) in derivation cohort was excellent (r=0.99; P<0.001). A linear regression model was used to develop a formula for deriving the estimated CAC score (eCAC) from fCAC (eCAC=0.978 x fCAC). In validation cohort, eCAC showed excellent agreement with cCAC (ICC=0.9983; 95%CI: 0.9972 - 0.9990). Excellent agreement for risk classification (weighted kappa=0.93898; 95%CI: 0.86833 - 1.0000) was observed with 95% (57/60) scores falling within the same risk category. Effective dose was significantly lower in FLASH mode (conventional, 0.58±0.21 mSv vs. FLASH, 0.34±0.12 mSv; P<0.0001).

Conclusion

CAC scoring using FLASH mode is feasible with high accuracy and shows excellent agreement with conventional CAC scores at significantly reduced radiation doses.

Coronary artery calcium scoring assessment in ultra-low-dose chest computed tomography

OBJECTIVES

To investigate the effect of non-electrocardiogram (ECG) -triggered ultra-low-dose CT (ULD-CT) with different reconstruction protocols on coronary artery calcium (CAC) scoring assessment, compared with ECG-triggered CAC CT (CAC-CT).

METHODS

This prospective study included 115 patients who underwent CAC-CT and ULD-CT scans under the same topogram images. CAC-CT adopted a prospective ECG-triggered sequential acquisition with a tube potential of 120 kV, and the reconstruction protocol was standard Qr36 + slice 3 mm (CACQr-3mm group). ULD-CT adopted a non-ECG-triggered high-pitch acquisition with a tube potential of Sn100 kV, and four groups of images (named ULDQr-3mm, ULDSa-3mm, ULDQr-1.5mm, and ULDSa-1.5mm) were reconstructed using different reconstruction algorithms (standard Qr36, kV-independent Sa36) and slice thicknesses (3 mm, 1.5 mm). The accuracy of CAC detection by ULD-CT was calculated. The agreement of the CAC score between ULD-CT and CAC-CT scans was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plot, and the agreement of risk categorization was assessed using weighted kappa.

RESULTS

The sensitivity and specificity of the ULDSa-1.5mm group for detecting positive CAC were 100% and 97.4%, respectively (k = 0.980). The CAC score for the ULDSa-3mm and ULDSa-1.5mm groups demonstrated excellent agreement with the CACQr-3mm group (ICC = 0.992, 0.990, respectively), with a mean difference of -12.3 and - 12.4. The agreement of risk categorization based on absolute and percentile CAC score between the ULDSa-1.5mm and CACQr-3mm groups was excellent (weighted k = 0.954, 0.983, respectively), and risk reclassification rates were low (3.5%, 2.8%, respectively). The effective dose was reduced by approximately 77.2% for the ULD-CT compared to the CAC-CT (0.18 mSv vs. 0.79 mSv, p < 0.001).

CONCLUSION

Reconstruction with a 1.5-mm slice thickness and kV-independent iterative algorithmic protocol in ULD-CT yielded excellent agreement in CAC score quantification and risk categorization compared with ECG-triggered CAC-CT.

Opportunistic Extraction of Quantitative CT Biomarkers: Turning the Incidental Into Prognostic Information

The past two decades have seen a significant increase in the use of CT, with a corresponding rise in the mean population radiation dose. This rise in CT use has caused improved diagnostic certainty in conditions that were not previously routinely evaluated using CT, such as headaches, back pain, and chest pain. Unused data, unrelated to the primary diagnosis, embedded within these scans have the potential to provide organ-specific measurements that can be used to prognosticate or risk-profile patients for a wide variety of conditions. The recent increased availability of computing power, expertise and software for automated segmentation and measurements, assisted by artificial intelligence, provides a conducive environment for the deployment of these analyses into routine use. Data gathering from CT has the potential to add value to examinations and help offset the public perception of harm from radiation exposure. We review the potential for the collection of these data and propose the incorporation of this strategy into routine clinical practice.

Enhanced CT imaging artificial neural network coronary artery calcification score assisted diagnosis

BACKGROUND

The study of coronary artery calcification (CAC) may assist in identifying additional coronary artery problem protective factors. On the contrary side, due to the wide variety of CAC as individuals, CAC research is difficult. Due to this, evaluating data for investigation is becoming complicated.

OBJECTIVE

To use a multi-layer perceptron, we investigated the accuracy and reliability of synthetic CAC coursework or hazard classification in pre or alors chest computerized tomography (CT) of arrangements resolutions in this analysis.

method

Photographs of the chest from similar individuals as well as calcium-just and non-gated pictures were incorporated. This cut thickness ordered CT pictures (bunch A: 1 mm; bunch B: 3 mm). The CAC rating was determined utilizing calcification score picture information, and became standard for tests. While the control treatment's machine learning program was created using 170 computed tomography pictures and evaluated using 144 scans, group A's machine learning algorithm was created using 150 chest CT diagnostic tests.

RESULTS

334 external related pictures (100 μm: 117; 0.5 mm x: 117) of 117 individuals and 612 inside design organizing (1 mm: 294; mm3: 314) of 406 patients were surveyed. Pack B had 0.94, however, tests An and b had 0.90 (95% CI: 0.85-0.93) ICCs between significant learning and gold expenses (0.92-0.96). Dull Altman plots agreed well. A machine teaching approach successfully identified 71% of cases in category A is 81% of patients in section B again for cardiac risk class.

CONCLUSION

Regression risk evaluation algorithms could assist in categorizing cardiorespiratory individuals into distinct risk groups and conveniently personalize the treatments to the patient's circumstances. The models would be based on information gathered through CAC. On both 1 and 3-mm scanners, the automatic determination of a CAC value and cardiovascular events categorization that used a depth teaching approach was reliable and precise. The layer thickness of 0.5 mm on chest CT was slightly less accurate in CAC detection and risk evaluation.

Automated total and vessel-specific coronary artery calcium (CAC) quantification on chest CT: direct comparison with CAC scoring on non-contrast cardiac CT

BACKGROUND

This study aimed to evaluate the artificial intelligence (AI)-based coronary artery calcium (CAC) quantification and regional distribution of CAC on non-gated chest CT, using standard electrocardiograph (ECG)-gated CAC scoring as the reference.

METHODS

In this retrospective study, a total of 405 patients underwent non-gated chest CT and standard ECG-gated cardiac CT. An AI-based algorithm was used for automated CAC scoring on chest CT, and Agatston score on cardiac CT was manually quantified. Bland-Altman plots were used to evaluate the agreement of absolute Agatston score between the two scans at the patient and vessel levels. Linearly weighted kappa (κ) was calculated to assess the reliability of AI-based CAC risk categorization and the number of involved vessels on chest CT.

RESULTS

The AI-based algorithm showed moderate reliability for the number of involved vessels in comparison to measures on cardiac CT (κ = 0.75, 95% CI 0.70-0.79, P < 0.001) and an assignment agreement of 76%. Considerable coronary arteries with CAC were not identified with a per-vessel false-negative rate of 59.3%, 17.8%, 34.9%, and 34.7% for LM, LAD, CX, and RCA on chest CT. The leading causes for false negatives of LM were motion artifact (56.3%, 18/32) and segmentation error (43.8%, 14/32). The motion artifact was almost the only cause for false negatives of LAD (96.6%, 28/29), CX (96.7%, 29/30), and RCA (100%, 34/34). Absolute Agatston scores on chest CT were underestimated either for the patient and individual vessels except for LAD (median difference: - 12.5, - 11.3, - 5.6, - 18.6 for total, LM, CX, and RCA, all P < 0.01; - 2.5 for LAD, P = 0.18). AI-based total Agatston score yielded good reliability for risk categorization (weighted κ 0.86, P < 0.001) and an assignment agreement of 86.7% on chest CT, with a per-patient false-negative rate of 15.2% (28/184) and false-positive rate of 0.5% (1/221) respectively.

CONCLUSIONS

AI-based per-patient CAC quantification on non-gated chest CT achieved a good agreement with dedicated ECG-gated CAC scoring overall and highly reliable CVD risk categorization, despite a slight but significant underestimation. However, it is challenging to evaluate the regional distribution of CAC without ECG-synchronization.

Coronary Artery Calcium Scoring: Current Status and Future Directions

Coronary artery calcium (CAC) scores obtained from CT scans have been shown to be prognostic in assessment of the risk for development of cardiovascular diseases, facilitating the prediction of outcome in asymptomatic individuals. Currently, several methods to calculate the CAC score exist, and each has its own set of advantages and disadvantages. Agatston CAC scoring is the most extensively used method. CAC scoring is currently recommended for use in asymptomatic individuals to predict the risk of developing cardiovascular diseases and the disease-specific mortality. In specific subsets of patients, the CAC score has also been recommended for reclassifying cardiovascular risk and aiding in decision making when planning primary prevention interventions such as statin therapy. The progression of CAC scores on follow-up images has been shown to be linked to risk of myocardial infarction and cardiovascular mortality. While the CAC score is a validated tool used clinically, several challenges, including various pitfalls associated with the acquisition, calculation, and interpretation of the score, prevent more widespread adoption of this metric. Recent research has been focused extensively on strategies to improve existing scoring methods, including measuring calcium attenuation, detecting microcalcifications, and focusing on extracoronary calcifications, and on strategies to improve image acquisition. A better understanding of CAC scoring approaches will help radiologists and other physicians better use and interpret these scores in their workflows. An invited commentary by S. Gupta is available online. Online supplemental material is available for this article. ^©RSNA, 2022.

Performance of artificial intelligence-based coronary artery calcium scoring in non-gated chest CT

OBJECTIVES

To evaluate the risk category performance of artificial intelligence-based coronary artery calcium score (AI-CACS) software used in non-gated chest computed tomography (CT) on three types of CT machines, considering the manual method as the standard.

METHODS

A total of 901 patients who underwent both chest CT and electrocardiogram (ECG)-gated non-contrast-enhanced cardiac CT with the same equipment within a 3-month period were enrolled in the study. AI-CACS software was based on a deep learning algorithm and was trained on multi-vendor, multi-scanner, and multi-hospital anonymized data from the chest CT database. The AI-CACS was automatically obtained from chest CT data by the AI-CACS software, while the manual CACS was obtained from cardiac CT data by the manual method. The correlation of the AI-CACS and manual CACS, concordance rate and kappa value of the risk categories determined by the two methods were calculated. The chi-square test was used to evaluate the differences in risk categories among the three types of CT machines from different manufacturers. The risk category performance of the AI-CACS for dichotomous risk categories bounded by 0, 100 and 400 was assessed.

RESULTS

The correlation of the AI-CACS with the manual CACS was ρ = 0.893 (p < 0.001). The Bland-Altman plot (AI-CACS minus manual CACS) showed a mean difference of -27.2 and 95% limits of agreement of -290.0 to 235.6. The agreement of risk categories for the CACS was kappa (κ) = 0.679 (p < 0.001), and the concordance rate was 80.6%. The risk categories determined by the AI-CACS software on three types of CT machines were not significantly different (p = 0.7543). As dichotomous risk categories bounded by 0, 100 and 400, the accuracy, kappa value, and area under the curve of the AI-CACS were 88.6% vs. 92.9% vs. 97.9%, 0.77 vs. 0.77 vs. 0.83, and 0.885 vs. 0.964 vs. 0.981, respectively.

CONCLUSIONS

There was good correlation and agreement between the AI-CACS and manual CACS in terms of the risk category. It is feasible to obtain the CACS using AI software based on non-gated chest CT data in a short time without increasing the radiation dose or economic burden. The AI-CACS software algorithm has good clinical universality and can be applied to CT machines from different manufacturers.

Reliability of Coronary Artery Calcium Severity Assessment on Non-Electrocardiogram-Gated CT: A Meta-Analysis

OBJECTIVE

The purpose of this meta-analysis was to investigate the pooled agreements of the coronary artery calcium (CAC) severities assessed by electrocardiogram (ECG)-gated and non-ECG-gated CT and evaluate the impact of the scan parameters.

MATERIALS AND METHODS

PubMed, EMBASE, and the Cochrane library were systematically searched. A modified Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to evaluate the quality of the studies. Meta-analytic methods were utilized to determine the pooled weighted bias, limits of agreement (LOA), and the correlation coefficient of the CAC scores or the weighted kappa for the categorization of the CAC severities detected by the two modalities. The heterogeneity among the studies was also assessed. Subgroup analyses were performed based on factors that could affect the measurement of the CAC score and severity: slice thickness, reconstruction kernel, and radiation dose for non-ECG-gated CT.

RESULTS

A total of 4000 patients from 16 studies were included. The pooled bias was 62.60, 95% LOA were -36.19 to 161.40, and the pooled correlation coefficient was 0.94 (95% confidence interval [CI] = 0.89-0.97) for the CAC score. The pooled weighted kappa of the CAC severity was 0.85 (95% CI = 0.79-0.91). Heterogeneity was observed in the studies (I² > 50%, p < 0.1). In the subgroup analysis, the agreement between the CAC categorizations was better when the two CT examinations had reconstructions based on the same slice thickness and kernel.

CONCLUSION

The pooled agreement of the CAC severities assessed by the ECG-gated and non-ECG-gated CT was excellent; however, it was significantly affected by scan parameters, such as slice thickness and the reconstruction kernel.

Coronary artery calcium scoring on non-gated, non-contrast chest computed tomography (CT) using wide-detector, high-pitch and fast gantry rotation: comparison with dedicated calcium scoring CT

Background

Our study assessed the reliability of non-gated, non-contrast chest computed tomography (NCCT) (with high pitch, wide coverage, and fast gantry rotation time, reconstructed at various slice thicknesses), compared with the electrocardiography (ECG)-gated calcium scoring cardiac computed tomography (CaCT), for quantifying coronary artery calcification (CAC).

Methods

Patients aged ≥50 years who required clinical NCCT were prospectively enrolled. All CT scans were performed with 256-detector rows; z-axis coverage, 8 cm; pitch, 1.5; and gantry rotation time, 280 ms (table feed, 42.86 cm/s). NCCT was followed by ECG-gated CaCT. The NCCT images were reconstructed at 0.625-, 1.25-, and 2.5-mm slice intervals. The CAC score was calculated on four sets of CT images with a commercially available software using the Agatston method. The CAC scores were divided into four standard Agatston scoring categories (Agatston scores: 0, 1–100, 101–400, and >400). The inter-observer and inter-technique agreements were evaluated for the CAC scores.

Results

Twenty-six patients (M:F, 14:12; mean age, 66.04±6.97 years) were evaluated. Agatston scores showed near-perfect correlation between CaCT and NCCT for each slice thickness. On Bland-Altman analysis, the mean differences of Agatston scores between CaCT and NCCT (slice thicknesses: 0.625, 1.25, and 2.5 mm) were 37.54, 6.67, and −41.04, respectively. Inter-technique concordance was high for the four Agatston scoring categories with linear-weighted kappa values of 0.599, 0.609, and 0.597 for NCCT (slice thicknesses: 0.625, 1.25, and 2.5 mm, respectively). NCCT with 1.25-mm slice thickness showed the strongest correlation with CaCT.

Conclusions

CAC quantification with NCCT using a wide detector, high pitch, and high temporal resolution scanning modes correlates very highly with ECG-gated CaCT, and 1.25-mm slice thickness NCCT images are more reliable than other NCCT images.

Reporting incidental coronary, aortic valve and cardiac calcification on non-gated thoracic computed tomography, a consensus statement from the BSCI/BSCCT and BSTI

Incidental coronary and cardiac calcification are frequent findings on non-gated thoracic CT. We recommend that the heart is reviewed on all CT scans where it is visualised. Coronary artery calcification is a marker of coronary artery disease and it is associated with an adverse prognosis on dedicated cardiac imaging and on non-gated thoracic CT performed for non-cardiac indications, both with and without contrast. We recommend that coronary artery calcification is reported on all non-gated thoracic CT using a simple patient-based score (none, mild, moderate, severe). Furthermore, we recommend that reports include recommendations for subsequent management, namely the assessment of modifiable cardiovascular risk factors and, if the patient has chest pain, assessment as per standard guidelines. In most cases, this will not necessitate additional investigations. Incidental aortic valve calcification may also be identified on non-gated thoracic CT and should be reported, along with ancillary findings such as aortic root dilation. Calcification may occur in other parts of the heart including mitral valve/annulus, pericardium and myocardium, but in many cases these are an incidental finding without clinical significance.

High-pitch dual-source CT for coronary artery calcium scoring: A head-to-head comparison of non-triggered chest versus triggered cardiac acquisition

BACKGROUND

To determine the effect of low-dose, high-pitch non-electrocardiographic (ECG)-triggered chest CT on coronary artery calcium (CAC) detection, quantification and risk stratification, compared to ECG-triggered cardiac CT.

METHODS

We selected 1,000 participants from the ImaLife study, 50% with coronary calcification on cardiac CT. All participants underwent non-contrast cardiac CT followed by chest CT using third-generation dual-source technology. Reconstruction settings were equal for both acquisitions. CAC scores were determined by Agatston's method, and divided dichotomously (0, >0), and into risk categories (0, 1-99, 100-399, ≥400). We investigated the influence of heart rate and body mass index (BMI) on risk reclassification.

RESULTS

Positive CAC scores on cardiac CT ranged from 1 to 6926 (median 39). Compared to cardiac CT, chest CT had sensitivity of 0.96 (95%CI 0.94-0.98) and specificity of 0.99 (95%CI 0.97-0.99) for CAC detection (κ = 0.95). In participants with coronary calcification on cardiac CT, CAC score on chest CT was lower than on cardiac CT (median 30 versus 40, p˂0.001). Agreement in CAC-based risk strata was excellent (weighted κ = 0.95). Sixty-five cases (6.5%) were reclassified by one risk category in chest CT, with fifty-five (84.6%) shifting downward. Higher BMI resulted in higher reclassification rate (13% for BMI ≥30 versus 5.2% for BMI <30, p = 0.001), but there was no effect of heart rate.

CONCLUSION

Low-dose, high-pitch chest CT, using third-generation dual-source technology shows almost perfect agreement with cardiac CT in CAC detection and risk stratification. However, low-dose chest CT mainly underestimates the CAC score as compared to cardiac CT, and results in inaccurate risk categorization in BMI ≥30.

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

BACKGROUND

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.

MATERIALS AND METHODS

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.

RESULTS

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%).

CONCLUSION

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.

Visual Estimate of Coronary Artery Calcium Predicts Cardiovascular Disease in COPD

BACKGROUND

COPD is associated with cardiovascular disease (CVD), and coronary artery calcification (CAC) provides additional prognostic information. With increasing use of nongated CT scans in clinical practice, this study hypothesized that the visual Weston CAC score would perform as well as the Agatston score in predicting prevalent and incident coronary artery disease (CAD) and CVD in COPD.

METHODS

CAC was measured by using Agatston and Weston scores on baseline CT scans in 1,875 current and former smokers enrolled in the Genetic Epidemiology of COPD (COPDGene) study. Baseline cardiovascular disease and incident cardiac events on longitudinal follow-up were recorded. Accuracy of the CAC scores was measured by using receiver-operating characteristic analysis, and Cox proportional hazards analyses were used to estimate the risk of incident cardiac events.

RESULTS

CAD was reported by 133 (7.1%) subjects at baseline. A total of 413 (22.0%) and 241 (12.9%) patients had significant CAC according to the Weston (≥ 7) and Agatston (≥ 400) scores, respectively; the two methods were significantly correlated (r = 0.84; P < .001). Over 5 years of follow-up, 127 patients (6.8%) developed incident CVD. For predicting prevalent CAD, c-indices for the Weston and Agatston scores were 0.78 and 0.74 and for predicting incident CVD, they were 0.62 and 0.61. After adjustment for age, race, sex, smoking pack-years, FEV₁, percent emphysema, and CT scanner type, a Weston score ≥ 7 was associated with time to first acute coronary event (hazard ratio, 2.16 [95% CI, 1.32 to 3.53]; P = .002), but a Agatston score ≥ 400 was not (hazard ratio, 1.75 [95% CI, 0.99-3.09]; P = .053).

CONCLUSIONS

A simple visual score for CAC performed well in predicting incident CAD in smokers with and without COPD.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.

Coronary artery calcification in lung cancer screening

Lung cancer screening has been shown in the National Lung Screening Trial (NLST) to result in a statistically significant decrease in lung cancer specific mortality. Also within that trial there was shown to be a 7% decrease in all-cause mortality. While the reasons for this benefit are not entirely clear, it may relate to the detection and treatment of other important findings. Smokers not only have a higher risk of lung cancer, but also increased risk of atherosclerosis. The latter can be detected by the discovery of aortic and/or coronary artery calcium on unenhanced CT. As coronary artery calcium scoring can be used as a screening tool to detect asymptomatic coronary artery atherosclerosis, its detection on lung cancer screening exams has the potential to provide both a teachable moment and treatment aimed at the reduction of major coronary artery events and mortality. In this review we will discuss the use of coronary artery calcium scoring for the detection of atherosclerotic disease and its potential application to lung cancer screening populations.

Coronary Artery Calcium Scoring: Is It Time for a Change in Methodology?

Quantification of coronary artery calcium (CAC) has been shown to be reliable, reproducible, and predictive of cardiovascular risk. Formal CAC scoring was introduced in 1990, with early scoring algorithms notable for their simplicity and elegance. Yet, with little evidence available on how to best build a score, and without a conceptual model guiding score development, these scores were, to a large degree, arbitrary. In this review, we describe the traditional approaches for clinical CAC scoring, noting their strengths, weaknesses, and limitations. We then discuss a conceptual model for developing an improved CAC score, reviewing the evidence supporting approaches most likely to lead to meaningful score improvement (for example, accounting for CAC density and regional distribution). After discussing the potential implementation of an improved score in clinical practice, we follow with a discussion of the future of CAC scoring, asking the central question: do we really need a new CAC score?

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

BACKGROUND

To 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.

METHODS

Of 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.

RESULTS

A 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.

CONCLUSION

Radiation 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.

Tin-filtered low-dose chest CT to quantify macroscopic calcification burden of the thoracic aorta

OBJECTIVES

To compare a low-dose, tin-filtered, nonenhanced, high-pitch Sn100 kVp CT protocol (Sn100) with a standard protocol (STP) for the detection of calcifications in the ascending aorta in patients scheduled for cardiac surgery.

METHODS

Institutional Review Board approval for this retrospective study was waived and the study was HIPAA-compliant. The study included 192 patients (128 men; age 68.8 ± 9.9 years), of whom 87 received the STP and 105 the Sn100 protocol. Size-specific dose estimates (SSDE) and radiation doses were obtained using dose monitoring software. Two blinded readers evaluated image quality on a scale from 1 (low) to 5 (high) and the extent of calcifications of the ascending aorta on a scale from 0 (none) to 10 (high), subdivided into 12 anatomic segments.

RESULTS

The Sn100 protocol achieved a mean SSDE of only 0.5 ± 0.1 mGy and 0.20 ± 0.04 mSv compared with the mean SSDE of 5.4 ± 2.2 mGy achieved with the STP protocol (p < 0.0001). Calcification burden was associated with age (p < 0.0001), but was independent of protocol with mean calcification scores of 0.48 ± 1.23 (STP) and 0.55 ± 1.25 (Sn100, p = 0.18). Reader agreement was very good (STP κ = 0.87 ± 0.02, Sn100 κ = 0.88 ± 0.01). The STP protocol provided a higher subjective image quality than the Sn100 protocol: STP median 4, interquartile range 4-5, vs. SN100 3, 3-4; p < 0.0001) and a slightly better depiction of calcification (STP 5, 4-5, vs. Sn100 4, 4-5; p < 0.0001).

CONCLUSIONS

The optimized Sn100 protocol achieved a mean SSDE of only 0.5 ± 0.1 mGy while the depiction of calcifications remained good, and there was no systematic difference in calcification burden between the two protocols.

KEY POINTS

• Tin-filtered, low-dose CT can be used to assess aortic calcifications before cardiac surgery • An optimized Sn100 protocol achieved a mean SSDE of only 0.5 ± 0.1 mGy • The depiction of atherosclerosis of the thoracic aorta was similar with both protocols • The depiction of relevant thoracic pathologies before cardiac surgery was similar with both protocols.

Improved assessment of mediastinal and pulmonary pathologies in combined staging CT examinations using a fast-speed acquisition dual-source CT protocol

OBJECTIVES

To demonstrate the feasibility of fast Dual-Source CT (DSCT) and to evaluate the clinical utility in chest/abdomen/pelvis staging CT studies.

METHODS

45 cancer patients with two follow-up combined chest/abdomen/pelvis staging CT examinations (maximally ±10 kV difference in tube potential) were included. The first scan had to be performed with our standard protocol (fixed pitch 0.6), the second one using a novel fast-speed DSCT protocol (fixed pitch 1.55). Effective doses (ED) were calculated, noise measurements performed. Scan times were compared, motion artefacts and the diagnostic confidence rated in consensus reading.

RESULTS

ED for the standard and fast-speed scans was 9.1 (7.0-11.1) mSv and 9.2 (7.4-12.8) mSv, respectively (P = 0.075). Image noise was comparable (abdomen; all P > 0.05) or reduced for fast-speed CTs (trachea, P = 0.001; ascending aorta, P < 0.001). Motion artefacts of the heart/the ascending aorta (all P < 0.001) and breathing artefacts (P < 0.031) were reduced in fast DSCT. The diagnostic confidence for the evaluation of mediastinal (P < 0.001) and pulmonary (P = 0.008) pathologies was improved for fast DSCT.

CONCLUSIONS

Fast DSCT for chest/abdomen/pelvis staging CT examinations is performed within 2 seconds scan time and eliminates relevant intrathoracic motion/breathing artefacts. Mediastinal/pulmonary pathologies can thus be assessed with high diagnostic confidence. Abdominal image quality remains excellent.

KEY POINTS

• Fast dual-source CT provides chest/abdomen/pelvis staging examinations within 2 seconds scan time. • The sevenfold scan time reduction eliminates relevant intrathoracic motion/breathing artefacts. • Mediastinal/pulmonary pathologies can now be assessed with high diagnostic confidence. • The coverage of the peripheral soft tissues is comparable to single-source CT. • Fast and large-volume oncologic DSCT can be performed with 9 mSv effective dose.

A comparative assessment of coronary artery calcification on chest CT scans of patients referred to a cardio-oncology clinic

BACKGROUND

The presence and burden of coronary artery calcium (CAC) is a strong predictor of cardiovascular events. In an effort to gain insight into the utility of CAC for coronary artery disease (CAD) screening in cancer patients with heart disease, we sought to determine the presence and burden of CAC detected on routine chest CT in patients referred to a cardio-oncology clinic, comparing them to a conventional cardiology clinic with the general population as controls.

METHODS

Patients from the cardio-oncology clinic, general cardiology clinic, and the general clinic population at Rush University Medical Center who had a chest CT as part of their previous treatment were identified. Each CT scan was evaluated for presence, extent, and severity of CAC by 3 independent readers.

RESULTS

In multivariate analysis, when compared with cardio-oncology clinic, CAC was more prevalent in the CT scans of cardiology patients (p = 0.04), but not the general clinic population (p = 0.5); CAC extent (p = 0.05) and severity (p = 0.05) was significantly higher in the cardiology patients but the extent (p = 0.05) and severity (p = 0.92) was similar in the general clinic population.

CONCLUSION

Despite being matched by age and sex, controlling for other major cardiovascular risk factors, patients referred to our cardio-oncology clinic had similar and less prevalent/severe CAC burden compared with the general population and conventional cardiology clinics respectively. Whether this translates to less utility of CAC for CAD screening, or to less overall coronary events in a cardio-oncology clinic, is of interest.

Feasibility of spectral shaping for detection and quantification of coronary calcifications in ultra-low dose CT

Objectives

To evaluate detectability and quantification of coronary calcifications for CT with a tin filter for spectral shaping.

Methods

Phantom inserts with 100 small and 9 large calcifications, and a moving artificial artery with 3 calcifications (speed 0–30 mm/s) were placed in a thorax phantom simulating different patient sizes. The phantom was scanned in high-pitch spiral mode at 100 kVp with tin filter (Sn100 kVp), and at a reference of 120 kVp, with electrocardiographic (ECG) gating. Detectability and quantification of calcifications were analyzed for standard (130 HU) and adapted thresholds.

Results

Sn100 kVp yielded lower detectability of calcifications (9 % versus 12 %, p = 0.027) and lower Agatston scores (p < 0.008), irrespective of calcification, patient size and speed. Volume scores of the moving calcifications for Sn100 kVp at speed 10–30 mm/s were lower (p < 0.001), while mass scores were similar (p = 0.131). For Sn100 kVp with adapted threshold of 117 HU, detectability (p = 1.000) and Agatston score (p > 0.206) were similar to 120 kVp. Spectral shaping resulted in median dose reduction of 62.3 % (range 59.0–73.4 %).

Conclusions

Coronary calcium scanning with spectral shaping yields lower detectability of calcifications and lower Agatston scores compared to 120 kVp scanning, for which a HU threshold correction should be developed.

Key points

• Sn100kVp yields lower detectability and lower Agatston scores compared to 120kVp

• Adapted HU threshold for Sn100kVp provides Agatston scores comparable to 120kVp

• Sn100 kVp considerably reduces dose in calcium scoring versus 120 kVp

High pitch third generation dual-source CT: Coronary and cardiac visualization on routine chest CT

BACKGROUND

Chest CT scans are frequently performed in radiology departments but have not previously contained detailed depiction of cardiac structures.

OBJECTIVES

To evaluate myocardial and coronary visualization on high-pitch non-gated CT of the chest using 3rd generation dual-source computed tomography (CT).

METHODS

Cardiac anatomy of patients who had 3rd generation, non-gated high pitch contrast enhanced chest CT and who also had prior conventional (low pitch) chest CT as part of a chest abdomen pelvis exam was evaluated. Cardiac image features were scored by reviewers blinded to diagnosis and pitch. Paired analysis was performed.

RESULTS

3862 coronary segments and 2220 cardiac structures were evaluated by two readers in 222 CT scans. Most patients (97.2%) had chest CT for oncologic evaluation. The median pitch was 2.34 (IQR 2.05, 2.65) in high pitch and 0.8 (IQR 0.8, 0.8) in low pitch scans (p < 0.001). High pitch CT showed higher image visualization scores for all cardiovascular structures compared with conventional pitch scans (p < 0.0001). Coronary arteries were visualized in 9 coronary segments per exam in high pitch scans versus 2 segments for conventional pitch (p < 0.0001). Radiation exposure was lower in the high pitch group compared with the conventional pitch group (median CTDIvol 10.83 vs. 12.36 mGy and DLP 790 vs. 827 mGycm respectively, p < 0.01 for both) with comparable image noise (p = 0.43).

CONCLUSION

Myocardial structure and coronary arteries are frequently visualized on non-gated 3rd generation chest CT. These results raise the question of whether the heart and coronary arteries should be routinely interpreted on routine chest CT that is otherwise obtained for non-cardiac indications.