Diagnostic Accuracy of Noninvasive 64-row Computed Tomographic Coronary Angiography (CCTA) Compared with Myocardial Perfusion Imaging (MPI): The PICTURE Study, A Prospective Multicenter Trial

The effectiveness of coronary computed tomography angiography and functional testing for the diagnosis of obstructive coronary artery disease: results from the individual patient data Collaborative Meta-Analysis of Cardiac CT (COME-CCT)

AIM

To determine the effectiveness of functional stress testing and computed tomography angiography (CTA) for diagnosis of obstructive coronary artery disease (CAD).

METHODS AND RESULTS

Two-thousand nine-hundred twenty symptomatic stable chest pain patients were included in the international Collaborative Meta-Analysis of Cardiac CT consortium to compare CTA with exercise electrocardiography (exercise-ECG) and single-photon emission computed tomography (SPECT) for diagnosis of CAD defined as ≥ 50% diameter stenosis by invasive coronary angiography (ICA) as reference standard. Generalised linear mixed models were used for calculating the diagnostic accuracy of each diagnostic test including non-diagnostic results as dependent variables in a logistic regression model with random intercepts and slopes. Covariates were the reference standard ICA, the type of diagnostic method, and their interactions. CTA showed significantly better diagnostic performance (p < 0.0001) with a sensitivity of 94.6% (95% CI 92.7-96) and a specificity of 76.3% (72.2-80) compared to exercise-ECG with 54.9% (47.9-61.7) and 60.9% (53.4-66.3), SPECT with 72.9% (65-79.6) and 44.9% (36.8-53.4), respectively. The positive predictive value of CTA was ≥ 50% in patients with a clinical pretest probability of 10% or more while this was the case for ECG and SPECT at pretest probabilities of ≥ 40 and 28%. CTA reliably excluded obstructive CAD with a post-test probability of below 15% in patients with a pretest probability of up to 74%.

CONCLUSION

In patients with stable chest pain, CTA is more effective than functional testing for the diagnosis as well as for reliable exclusion of obstructive CAD. CTA should become widely adopted in patients with intermediate pretest probability.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO Database for Systematic Reviews-CRD42012002780.

CRITICAL RELEVANCE STATEMENT

In symptomatic stable chest pain patients, coronary CTA is more effective than functional testing for diagnosis and reliable exclusion of obstructive CAD in intermediate pretest probability of CAD.

KEY POINTS

Coronary computed tomography angiography showed significantly better diagnostic performance (p < 0.0001) for diagnosis of coronary artery disease compared to exercise-ECG and SPECT. The positive predictive value of coronary computed tomography angiography was ≥ 50% in patients with a clinical pretest probability of at least 10%, for ECG ≥ 40%, and for SPECT 28%. Coronary computed tomography angiography reliably excluded obstructive coronary artery disease with a post-test probability of below 15% in patients with a pretest probability of up to 74%.

Coronary computed tomography angiography for clinical practice

Coronary artery disease (CAD) is a common condition caused by the accumulation of atherosclerotic plaques. It can be classified into stable CAD or acute coronary syndrome. Coronary computed tomography angiography (CCTA) has a high negative predictive value and is used as the first examination for diagnosing stable CAD, particularly in patients at intermediate-to-high risk. CCTA is also adopted for diagnosing acute coronary syndrome, particularly in patients at low-to-intermediate risk. Myocardial ischemia does not always co-exist with coronary artery stenosis, and the positive predictive value of CCTA for myocardial ischemia is limited. However, CCTA has overcome this limitation with recent technological advancements such as CT perfusion and CT-fractional flow reserve. In addition, CCTA can be used to assess coronary artery plaques. Thus, the indications for CCTA have expanded, leading to an increased demand for radiologists. The CAD reporting and data system (CAD-RADS) 2.0 was recently proposed for standardizing CCTA reporting. This RADS evaluates and categorizes patients based on coronary artery stenosis and the overall amount of coronary artery plaque and links this to patient management. In this review, we aimed to review the major trials and guidelines for CCTA to understand its clinical role. Furthermore, we aimed to introduce the CAD-RADS 2.0 including the assessment of coronary artery stenosis, plaque, and other key findings, and highlight the steps for CCTA reporting. Finally, we aimed to present recent research trends including the perivascular fat attenuation index, artificial intelligence, and the advancements in CT technology.

A novel hybrid machine learning model for auxiliary diagnosing myocardial ischemia

Introduction

Accurate identification of the myocardial texture features of fat around the coronary artery on coronary computed tomography angiography (CCTA) images are crucial to improve clinical diagnostic efficiency of myocardial ischemia (MI). However, current coronary CT examination is difficult to recognize and segment the MI characteristics accurately during earlier period of inflammation.

Materials and methods

We proposed a random forest model to automatically segment myocardium and extract peripheral fat features. This hybrid machine learning (HML) model is integrated by CCTA images and clinical data. A total of 1,316 radiomics features were extracted from CCTA images. To further obtain the features that contribute the most to the diagnostic model, dimensionality reduction was applied to filter features to three: LNS, GFE, and WLGM. Moreover, statistical hypothesis tests were applied to improve the ability of discriminating and screening clinical features between the ischemic and non-ischemic groups.

Results

By comparing the accuracy, recall, specificity and AUC of the three models, it can be found that HML had the best performance, with the value of 0.848, 0.762, 0.704 and 0.729.

Conclusion

In sum, this study demonstrates that ML-based radiomics model showed good predictive value in MI, and offer an enhanced tool for predicting prognosis with greater accuracy.

Subtraction Improves the Accuracy of Coronary CT Angiography in Patients with Severe Calcifications in Identifying Moderate and Severe Stenosis: A Multicenter Study

RATIONALE AND OBJECTIVES

To investigate the diagnostic accuracy of subtraction coronary computed tomographic angiography (CCTAsub) in identifying ≥ 50% and ≥ 70% coronary stenosis in patients with different degrees of calcification.

MATERIALS AND METHODS

In this study, 180 patients with coronary calcified plaques who underwent both coronary CT angiography and invasive coronary angiography (ICA) were prospectively enrolled at five centers. Patients were divided into three groups according to the Agatston score: group A (low to moderate, < 400), group B (high, 400-999), and group C (very high, ≥ 1000). Diagnostic accuracies estimated by area under the receiver operating characteristic curve (AUC) were compared between conventional CCTA (CCTAcon) and CCTAsub, with ICA as a reference standard.

RESULTS

There were 86 patients in group A, 44 in group B, and 50 in group C. In identifying ≥ 70% coronary stenosis, subtraction improved the diagnostic accuracies on a per-segment basis in group B (AUC: 0.80 vs 0.92, p = 0.001) and group C (AUC: 0.75 vs 0.84, p = 0.001) after subtraction. When identifying ≥ 50% coronary stenosis, the per-segment AUC of CCTAsub in group B and C were significantly higher than that in CCTAcon (group B: 0.81 vs 0.92, p < 0.001; group C: 0.77 vs 0.88, p < 0.001). However, no improvement was observed in group A.

CONCLUSION

Subtraction achieved better diagnostic accuracy in patients with Agatston score ≥ 400, both in identifying ≥ 50% and ≥ 70% coronary stenosis, which was instructive for the application of subtraction in clinical practice.

Efficacy and Safety of Iodixanol in Computed Coronary Tomographic Angiography and Cardiac Catheterization

Iodixanol is an iso-osmolar non-ionic dimeric hydrophilic contrast agent with a higher viscosity than the monomeric agents. It is the only Food and Drug Administration (FDA)-approved iso-osmolar agent in the United States, and it is the only contrast agent with an FDA-approved indication for use in cardiac computed tomographic angiography (CCTA), to assist in the diagnostic evaluation of patients with suspected coronary artery disease. In clinical studies, it has been noted to have fewer side effects and similar image quality when compared to low-osmolar contrast media. This can be attributed to the pharmacological properties of iodixanol. These contrast agents are used for coronary computed tomography angiography and cardiac catheterization. In this article, the use, tolerability, and efficacy of iodixanol are reviewed, specifically evaluating the use of CCTA and coronary angiography, including outcome studies, randomized trials, and comparisons to other contrast agents.

Effects of renin-angiotensin-aldosterone-system inhibitors on coronary atherosclerotic plaques: The PARADIGM registry

BACKGROUND AND AIMS

Inhibition of Renin-Angiotensin-Aldosterone-System (RAAS) has been hypothesized to improve endothelial function and reduce plaque inflammation, however, their impact on the progression of coronary atherosclerosis is unclear. We aim to study the effects of RAAS inhibitor on plaque progression and composition assessed by serial coronary CT angiography (CCTA).

METHODS

We performed a prospective, multinational study consisting of a registry of patients without history of CAD, who underwent serial CCTAs. Patients using RAAS inhibitors were propensity matched to RAAS inhibitor naïve patients based on clinical and CCTA characteristics at baseline. Atherosclerotic plaques in CCTAs were quantitatively analyzed for percent atheroma volume (PAV) according to plaque composition. Interactions between RAAS inhibitor use and baseline PAV on plaque progression were assessed in the unmatched cohort using a multivariate linear regression model.

RESULTS

Of 1248 patients from the registry, 299 RAAS inhibitor taking patients were matched to 299 RAAS inhibitor naïve patients. Over a mean interval of 3.9 years, there was no significant difference in annual progression of total PAV between RAAS inhibitor naïve vs taking patients (0.75 vs 0.79%/year, p = 0.66). With interaction testing in the unmatched cohort, however, RAAS inhibitor use was significantly associated with lower non-calcified plaque progression (Beta coefficient -0.100, adjusted p = 0.038) with higher levels of baseline PAV.

CONCLUSIONS

The use of RAAS inhibitors over a period of nearly 4 years did not significantly impact on total atherosclerotic plaque progression or various plaque components. However, interaction testing to assess the differential effect of RAAS inhibition based on baseline PAV suggested a significant decrease in progression of non-calcified plaque in patients with a higher burden of baseline atherosclerosis, which should be considered hypothesis generating.

Role of Cardiovascular Imaging in Risk Assessment: Recent Advances, Gaps in Evidence, and Future Directions

Optimal risk assessment for primary prevention remains highly challenging. Recent registries have highlighted major discrepancies between guidelines and daily practice. Although guidelines have improved over time and provide updated risk scores, they still fail to identify a significant proportion of at-risk individuals, who then miss out on effective prevention measures until their initial ischemic events. Cardiovascular imaging is progressively assuming an increasingly pivotal role, playing a crucial part in enhancing the meticulous categorization of individuals according to their risk profiles, thus enabling the customization of precise therapeutic strategies for patients with increased cardiovascular risks. For the most part, the current approach to patients with atherosclerotic cardiovascular disease (ASCVD) is homogeneous. However, data from registries (e.g., REACH, CORONOR) and randomized clinical trials (e.g., COMPASS, FOURIER, and ODYSSEY outcomes) highlight heterogeneity in the risks of recurrent ischemic events, which are especially higher in patients with poly-vascular disease and/or multivessel coronary disease. This indicates the need for a more individualized strategy and further research to improve definitions of individual residual risk, with a view of intensifying treatments in the subgroups with very high residual risk. In this narrative review, we discuss advances in cardiovascular imaging, its current place in the guidelines, the gaps in evidence, and perspectives for primary and secondary prevention to improve risk assessment and therapeutic strategies using cardiovascular imaging.

2022 use of coronary computed tomographic angiography for patients presenting with acute chest pain to the emergency department: An expert consensus document of the Society of cardiovascular computed tomography (SCCT): Endorsed by the American College of Radiology (ACR) and North American Society for cardiovascular Imaging (NASCI)

Coronary computed tomography angiography (CTA) improves the quality of care for patients presenting with acute chest pain (ACP) to the emergency department (ED), particularly in patients with low to intermediate likelihood of acute coronary syndrome (ACS). The Society of Cardiovascular Computed Tomography Guidelines Committee was formed to develop recommendations for acquiring, interpreting, and reporting of coronary CTA to ensure appropriate, safe, and efficient use of this modality. Because of the increasing use of coronary CTA testing for the evaluation of ACP patients, the Committee has been charged with the development of the present document to assist physicians and technologists. These recommendations were produced as an educational tool for practitioners evaluating acute chest pain patients in the ED, in the interest of developing systematic standards of practice for coronary CTA based on the best available data or broad expert consensus. Due to the highly variable nature of medical care, approaches to patient selection, preparation, protocol selection, interpretation or reporting that differs from these guidelines may represent an appropriate variation based on a legitimate assessment of an individual patient's needs.

Prediction of myocardial ischemia in coronary heart disease patients using a CCTA-Based radiomic nomogram

Objective

The present study aimed to predict myocardial ischemia in coronary heart disease (CHD) patients based on the radiologic features of coronary computed tomography angiography (CCTA) combined with clinical factors.

Methods

The imaging and clinical data of 110 patients who underwent CCTA scan before DSA or FFR examination in Changzhou Second People's Hospital, Nanjing Medical University (90 patients), and The First Affiliated Hospital of Soochow University (20 patients) from March 2018 to January 2022 were retrospectively analyzed. According to the digital subtraction angiography (DSA) and fractional flow reserve (FFR) results, all patients were assigned to myocardial ischemia (n = 58) and normal myocardial blood supply (n = 52) groups. All patients were further categorized into training (n = 64) and internal validation (n = 26) sets at a ratio of 7:3, and the patients from second site were used as external validation. Clinical indicators of patients were collected, the left ventricular myocardium were segmented from CCTA images using CQK software, and the radiomics features were extracted using pyradiomics software. Independent prediction models and combined prediction models were established. The predictive performance of the model was assessed by calibration curve analysis, receiver operating characteristic (ROC) curve and decision curve analysis.

Results

The combined model consisted of one important clinical factor and eight selected radiomic features. The area under the ROC curve (AUC) of radiomic model was 0.826 in training set, and 0.744 in the internal validation set. For the combined model, the AUCs were 0.873, 0.810, 0.800 in the training, internal validation, and external validation sets, respectively. The calibration curves demonstrated that the probability of myocardial ischemia predicted by the combined model was in good agreement with the observed values in both training and validation sets. The decision curve was within the threshold range of 0.1-1, and the clinical value of nomogram was higher than that of clinical model.

Conclusion

The radiomic characteristics of CCTA combined with clinical factors have a good clinical value in predicting myocardial ischemia in CHD patients.

Nomograms Based on the Albumin/Neutrophil-to-Lymphocyte Ratio Score for Predicting Coronary Artery Disease or Subclinical Coronary Artery Disease

Purpose

To develop and validate two nomograms incorporating the albumin/neutrophil-to-lymphocyte ratio score (ANS) for predicting the risk of coronary artery disease (CAD) or subclinical CAD.

Patients and Methods

Four hundred fifty patients with suspected CAD who underwent coronary computed tomographic angiography were consecutively enrolled between September 2015 and June 2017. Nomograms were established based on independent predictors of CAD or subclinical CAD.

Results

In total, 437 patients with suspected CAD who underwent coronary computed tomographic angiography were included. Male sex, age ≥65 years, smoking, hypertension, diabetes, dyslipidemia, ischemic stroke, and ANS were independent predictors of CAD and subclinical CAD. The areas under the curve of each nomogram were 0.799 (95% CI: 0.752-0.846) and 0.809 (95% CI: 0.762-0.856), respectively. The calibration curve and decision curve analysis showed good performance for the diagnostic nomograms. The prediction of CAD or subclinical CAD by the ANS was not modified by the independent predictors (all, p for interaction >0.05).

Conclusion

Our ANS-based nomograms can provide accurate and individualized risk predictions for patients with suspected CAD or subclinical CAD.

Pre-procedural planning of coronary revascularization by cardiac computed tomography: An expert consensus document of the Society of Cardiovascular Computed Tomography

Coronary CT angiography (CCTA) demonstrated high diagnostic accuracy for detecting coronary artery disease (CAD) and a key role in the management of patients with low-to-intermediate pretest likelihood of CAD. However, the clinical information provided by this noninvasive method is still regarded insufficient in patients with diffuse and complex CAD and for planning percutaneous coronary intervention (PCI) and surgical revascularization procedures. On the other hand, technology advancements have recently shown to improve CCTA diagnostic accuracy in patients with diffuse and calcific stenoses. Moreover, stress CT myocardial perfusion imaging (CT-MPI) and fractional flow reserve derived from CCTA (CT-FFR) have been introduced in clinical practice as new tools for evaluating the functional relevance of coronary stenoses, with the possibility to overcome the main CCTA drawback, i.e. anatomical assessment only. The potential value of CCTA to plan and guide interventional procedures lies in the wide range of information it can provide: a) detailed evaluation of plaque extension, volume and composition; b) prediction of procedural success of CTO PCI using scores derived from CCTA; c) identification of coronary lesions requiring additional techniques (e.g., atherectomy and lithotripsy) to improve stent implantation success by assessing calcium score and calcific plaque distribution; d) assessment of CCTA-derived Syntax Score and Syntax Score II, which allows to select the mode of revascularization (PCI or CABG) in patients with complex and multivessel CAD. The aim of this Consensus Document is to review and discuss the available data supporting the role of CCTA, CT-FFR and stress CT-MPI in the preprocedural and possibly intraprocedural planning and guidance of myocardial revascularization interventions.

Pre-procedural planning of coronary revascularization by cardiac computed tomography: An expert consensus document of the Society of Cardiovascular Computed Tomography

Coronary CT angiography (CCTA) demonstrated high diagnostic accuracy for detecting coronary artery disease (CAD) and a key role in the management of patients with low-to-intermediate pretest likelihood of CAD. However, the clinical information provided by this noninvasive method is still regarded insufficient in patients with diffuse and complex CAD and for planning percutaneous coronary intervention (PCI) and surgical revascularization procedures. On the other hand, technology advancements have recently shown to improve CCTA diagnostic accuracy in patients with diffuse and calcific stenoses. Moreover, stress CT myocardial perfusion imaging (CT-MPI) and fractional flow reserve derived from CCTA (CT-FFR) have been introduced in clinical practice as new tools for evaluating the functional relevance of coronary stenoses, with the possibility to overcome the main CCTA drawback, i.e. anatomical assessment only. The potential value of CCTA to plan and guide interventional procedures lies in the wide range of information it can provide: a) detailed evaluation of plaque extension, volume and composition; b) prediction of procedural success of CTO PCI using scores derived from CCTA; c) identification of coronary lesions requiring additional techniques (e.g., atherectomy and lithotripsy) to improve stent implantation success by assessing calcium score and calcific plaque distribution; d) assessment of CCTA-derived Syntax Score and Syntax Score II, which allows to select the mode of revascularization (PCI or CABG) in patients with complex and multivessel CAD. The aim of this Consensus Document is to review and discuss the available data supporting the role of CCTA, CT-FFR and stress CT-MPI in the preprocedural and possibly intraprocedural planning and guidance of myocardial revascularization interventions.

Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT

BACKGROUND

Stress-only myocardial perfusion imaging (MPI) markedly reduces radiation dose, scanning time, and cost. We developed an automated clinical algorithm to safely cancel unnecessary rest imaging with high sensitivity for obstructive coronary artery disease (CAD).

METHODS AND RESULTS

Patients without known CAD undergoing both MPI and invasive coronary angiography from REFINE SPECT were studied. A machine learning score (MLS) for prediction of obstructive CAD was generated using stress-only MPI and pre-test clinical variables. An MLS threshold with a pre-defined sensitivity of 95% was applied to the automated patient selection algorithm. Obstructive CAD was present in 1309/2079 (63%) patients. MLS had higher area under the receiver operator characteristic curve (AUC) for prediction of CAD than reader diagnosis and TPD (0.84 vs 0.70 vs 0.78, P < .01). An MLS threshold of 0.29 had superior sensitivity than reader diagnosis and TPD for obstructive CAD (95% vs 87% vs 87%, P < .01) and high-risk CAD, defined as stenosis of the left main, proximal left anterior descending, or triple-vessel CAD (sensitivity 96% vs 89% vs 90%, P < .01).

CONCLUSIONS

The MLS is highly sensitive for prediction of both obstructive and high-risk CAD from stress-only MPI and can be applied to a stress-first protocol for automatic cancellation of unnecessary rest imaging.

The Role of Cardiac Computed Tomography in Heart Failure

PURPOSE OF REVIEW

Cardiac computed tomography (CT) is becoming a more widely applied tool in the diagnosis and management of a variety of cardiovascular conditions, including heart failure. The aim of this narrative review is to examine the role of cardiac CT in patients with heart failure.

RECENT FINDINGS

Coronary computed tomographic angiography has robust diagnostic accuracy for ruling out coronary artery disease. These data are reflected in updated guidelines from major cardiology organizations. New roles for cardiac CT in myocardial imaging, perfusion scanning, and periprocedural planning, execution, and monitoring are being implemented. Cardiac CT is useful in ruling out coronary artery disease its diagnostic accuracy, accessibility, and safety. It is also intricately linked to invasive cardiac procedures that patients with heart failure routinely undergo.

Recent Advances in Coronary Computed Tomography Angiogram: The Ultimate Tool for Coronary Artery Disease

PURPOSE OF REVIEW

The emerging technologies in multidetector computed tomography scanners gave the ability to image coronary arteries in a single heartbeat, at a higher quality, and low radiation dose. Furthermore, incorporating artificial intelligence and machine learning into image processing and interpretation have extended the use for coronary computed tomography angiogram (CCTA) and its applications. In this review, we will explore the recent evidence and advances supporting CCTA to become the ultimate tool for coronary artery disease.

RECENT FINDINGS

Results from the EVINCI, ISCHEMIA, SCOT-HEART, and PROMISE showed that CCTA is better in patients' risk stratification and in detecting subclinical atherosclerosis, resulting in earlier interventions and lesser events. Additionally, CCTA gave us a closer look on atherosclerotic disease by identifying different type of plaque and their clinical significance. Furthermore, FFR_CT is a notable example of incorporating artificial intelligence into CCTA. This technology helped us to accurately and non-invasively identify flow limiting lesions, guiding revascularization. As a result of the recent evidence, CCTA have made its way into the chest pain guidelines all over the world. Moreover, CCTA have the potential to revolutionize our understanding and standards in screening, preventing, and managing heart disease.

Predicting Chronic Myocardial Ischemia Using CCTA-Based Radiomics Machine Learning Nomogram

BACKGROUND

Coronary computed tomography angiography (CCTA) is a well-established non-invasive diagnostic test for the assessment of coronary artery diseases (CAD). CCTA not only provides information on luminal stenosis but also permits non-invasive assessment and quantitative measurement of stenosis based on radiomics.

PURPOSE

This study is aimed to develop and validate a CT-based radiomics machine learning for predicting chronic myocardial ischemia (MIS).

METHODS

CCTA and SPECT-myocardial perfusion imaging (MPI) of 154 patients with CAD were retrospectively analyzed and 94 patients were diagnosed with MIS. The patients were randomly divided into two sets: training (n = 107) and test (n = 47). Features were extracted for each CCTA cross-sectional image to identify myocardial segments. Multivariate logistic regression was used to establish a radiomics signature after feature dimension reduction. Finally, the radiomics nomogram was built based on a predictive model of MIS which in turn was constructed by machine learning combined with the clinically related factors. We then validated the model using data from 49 CAD patients and included 18 MIS patients from another medical center. The receiver operating characteristic curve evaluated the diagnostic accuracy of the nomogram based on the training set and was validated by the test and validation set. Decision curve analysis (DCA) was used to validate the clinical practicability of the nomogram.

RESULTS

The accuracy of the nomogram for the prediction of MIS in the training, test and validation sets was 0.839, 0.832, and 0.816, respectively. The diagnosis accuracy of the nomogram, signature, and vascular stenosis were 0.824, 0.736 and 0.708, respectively. A significant difference in the number of patients with MIS between the high and low-risk groups was identified based on the nomogram (P < .05). The DCA curve demonstrated that the nomogram was clinically feasible.

CONCLUSION

The radiomics nomogram constructed based on the image of CCTA act as a non-invasive tool for predicting MIS that helps to identify high-risk patients with coronary artery disease.

The diagnostic accuracy of coronary computed tomography angiography in patients with and without previous coronary interventions

BACKGROUND

Invasive coronary angiography (ICA) is the gold standard for imaging coronary arteries and the severity of coronary artery disease (CAD). Coronary computed tomography angiography (CCTA) has undergone remarkable progress in the diagnosis of CAD.

OBJECTIVES

To evaluate the effect of prior vs no previous coronary interventions on the diagnostic accuracy of CCTA as an alternative to ICA to improve health outcomes for patients with suspected CAD.

METHODS

A prospective cohort study was carried out among patients suspected of CAD and for evaluation of grafts and stents to investigate recurrent ischemic symptoms. 120 patients imaged by CCTA were then referred to ICA, which is considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of CCTA were assessed relative to ICA.

RESULTS

Based on a per-patient analysis, the comparison with ICA reveals variations in sensitivity, specificity, PPV, NPV and accuracy of CCTA. In patients without any previous coronary interventions, the sensitivity was 97.8%, and specificity was 95.6%. The PPV and NPV were 97.8% and 95.5%, respectively. Regarding patients with coronary artery bypass grafts (CABG), the sensitivity was 95% and specificity 100%. The PPV and NPV were 100% and 90.9%, respectively. Regarding patients with prior percutaneous coronary intervention (PCI), the results were a sensitivity of 84.6%, specificity of 77.8%, PPV of 84.6% and NPV of 77.8%.

CONCLUSION

CCTA is a powerful diagnostic tool, especially for the evaluation of the major coronary arteries and evaluation of patients with prior CABG. ICA is recommended for evaluation of patients with an intracoronary stent.

Exploring value of CT coronary imaging combined with machine-learning methods to predict myocardial ischemia

PURPOSE

To establish a machine-learning (ML) model based on coronary computed tomography angiography (CTA) images for evaluating myocardial ischemia in patients diagnosed with coronary atherosclerosis.

METHODS

This retrospective analysis includes CTA images acquired from 110 patients. Among them, 58 have myocardial ischemia and 52 have normal myocardial blood supply. The patients are divided into training and test datasets with a ratio 7 : 3. Deep learning model-based CQK software is used to automatically segment myocardium on CTA images and extract texture features. Then, seven ML models are constructed to classify between myocardial ischemia and normal myocardial blood supply cases. Predictive performance and stability of the classifiers are determined by receiver operating characteristic curve with cross validation. The optimal ML model is then validated using an independent test dataset.

RESULTS

Accuracy and areas under ROC curves (AUC) obtained from the support vector machine with extreme gradient boosting linear method are 0.821 and 0.777, respectively, while accuracy and AUC achieved by the neural network (NN) method are 0.818 and 0.757, respectively. The naive Bayes model yields the highest sensitivity (0.942), and the random forest model yields the highest specificity (0.85). The k-nearest neighbors model yields the lowest accuracy (0.74). Additionally, NN model demonstrates the lowest relative standard deviations (0.16 for accuracy and 0.08 for AUC) indicating the high stability of this model, and its AUC applying to the independent test dataset is 0.72.

CONCLUSION

The NN model demonstrates the best performance in predicting myocardial ischemia using radiomics features computed from CTA images, which suggests that this ML model has promising potential in guiding clinical decision-making.

2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

This clinical practice guideline for the evaluation and diagnosis of chest pain provides recommendations and algorithms for clinicians to assess and diagnose chest pain in adult patients.

METHODS

A comprehensive literature search was conducted from November 11, 2017, to May 1, 2020, encompassing randomized and nonrandomized trials, observational studies, registries, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Collaboration, Agency for Healthcare Research and Quality reports, and other relevant databases. Additional relevant studies, published through April 2021, were also considered.

STRUCTURE

Chest pain is a frequent cause for emergency department visits in the United States. The "2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain" provides recommendations based on contemporary evidence on the assessment and evaluation of chest pain. This guideline presents an evidence-based approach to risk stratification and the diagnostic workup for the evaluation of chest pain. Cost-value considerations in diagnostic testing have been incorporated, and shared decision-making with patients is recommended.

2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

This clinical practice guideline for the evaluation and diagnosis of chest pain provides recommendations and algorithms for clinicians to assess and diagnose chest pain in adult patients.

METHODS

A comprehensive literature search was conducted from November 11, 2017, to May 1, 2020, encompassing randomized and nonrandomized trials, observational studies, registries, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Collaboration, Agency for Healthcare Research and Quality reports, and other relevant databases. Additional relevant studies, published through April 2021, were also considered.

STRUCTURE

Chest pain is a frequent cause for emergency department visits in the United States. The "2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain" provides recommendations based on contemporary evidence on the assessment and evaluation of chest pain. This guideline presents an evidence-based approach to risk stratification and the diagnostic workup for the evaluation of chest pain. Cost-value considerations in diagnostic testing have been incorporated, and shared decision-making with patients is recommended.

2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

This clinical practice guideline for the evaluation and diagnosis of chest pain provides recommendations and algorithms for clinicians to assess and diagnose chest pain in adult patients.

METHODS

A comprehensive literature search was conducted from November 11, 2017, to May 1, 2020, encompassing randomized and nonrandomized trials, observational studies, registries, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Collaboration, Agency for Healthcare Research and Quality reports, and other relevant databases. Additional relevant studies, published through April 2021, were also considered. Structure: Chest pain is a frequent cause for emergency department visits in the United States. The "2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain" provides recommendations based on contemporary evidence on the assessment and evaluation of chest pain. This guideline presents an evidence-based approach to risk stratification and the diagnostic workup for the evaluation of chest pain. Cost-value considerations in diagnostic testing have been incorporated, and shared decision-making with patients is recommended.

Nomograms Based on the Advanced Lung Cancer Inflammation Index for the Prediction of Coronary Artery Disease and Calcification

Aim

To develop and validate 3 nomograms incorporating the advanced lung cancer inflammation index (ALI) that can aid in predicting the risk of coronary artery disease (CAD) and coronary artery calcification (CAC).

Methods

The study enrolled 562 consecutive patients with suspected CAD who underwent coronary computed tomographic angiography between September 2015 and June 2017. Independent risk factors for CAD, CAC, and CAD with CAC were identified via univariate and multivariate analysis, and nomograms were established based on the independent predictors identified. The area under the curve (AUC), calibration curve, and decision curve analysis were used to evaluate the nomograms. Correlations between ALI and other clinical indicators were examined via Spearman correlation analysis.

Results

In total, 549 patients with suspected CAD who underwent coronary computed tomographic angiography were included. Male sex, hypertension, diabetes, dyslipidemia, ischemic stroke, and ALI were independent predictors of both CAD and CAC. Male sex, hypertension, diabetes, dyslipidemia, and ALI were also identified as independent predictors of CAD with CAC. The AUC values for the nomograms developed using these risk factors were 0.739 (95% confidence interval [CI], 0.693-0.785), 0.728 (95% CI, 0.684-0.772), and 0.717 (95% CI 0.673-0.761), respectively. ALI was negatively correlated with neutrophil-to-lymphocyte ratio and CAC score and positively correlated with serum albumin levels and body mass index (all P < .05).

Conclusions

ALI is an independent predictor of CAD, CAC, and CAD with CAC. Our ALI-based nomograms can provide accurate and individualized risk predictions for patients with suspected CAD.

Validation of Coronary Artery Disease Reporting and Data System (CAD-RADS) and Application of Coronary Artery Calcium Data and Reporting System (CAC-DRS) as New Standardized Tools in the Management of Coronary Artery Disease Patients

Background and Objectives

The coronary artery disease reporting and data system (CAD-RADS) is intended to standardize the reporting of CCTA and the subsequent management guidelines of CAD. The present study was conducted to investigate the validation of CAD-RADS and the application of coronary calcium grading in CAD management.

Patients and Methods

The current study is a single-center prospective study that involved 177 participants with chest pain who were submitted to coronary CT angiography (CCTA). Two reviewers independently assessed CCTA results and gave each patient a CAD-RADS category. The reference standard for determining the clinical utility of CAD-RADS was invasive coronary angiography (ICA). The inter-reviewer agreement (IRA) was tested using the intra-class correlation (ICC).

Results

The study enrolled 111 cases with non-significant CAD and 66 cases with significant CAD based on ICA findings. According to the reviewer, the CAD-RADS had a sensitivity, specificity, and accuracy of 90.9 to 100%, 89.2 to 94.6%, and 93.16 to 93.2%, respectively, for predicting severe CAD. The IRA for CAD-RADS categories was excellent (ICC = 0.960). The best cut-off value for predicting severe CAD was CAD-RADS > 3. Significant relation between Ca and severe CAD (p<0.001) was detected.

Conclusion

The current study provides a good understanding of CAD-RADS as a standard tool with high diagnostic accuracy.

Coronary Computed Tomographic Angiography for Complete Assessment of Coronary Artery Disease: JACC State-of-the-Art Review

Coronary computed tomography angiography (CTA) has shown great technological improvements over the last 2 decades. High accuracy of CTA in detecting significant coronary stenosis has promoted CTA as a substitute for conventional invasive coronary angiography in patients with suspected coronary artery disease. In patients with coronary stenosis, CTA-derived physiological assessment is surrogate for intracoronary pressure and velocity wires, and renders possible decision-making about revascularization solely based on computed tomography. Computed tomography coronary anatomy with functionality assessment could potentially become a first line in diagnosis. Noninvasive imaging assessment of plaque burden and morphology is becoming a valuable substitute for intravascular imaging. Recently, wall shear stress and perivascular inflammation have been introduced. These assessments could support risk management for both primary and secondary cardiovascular prevention. Anatomy, functionality, and plaque composition by CTA tend to replace invasive assessment. Complete CTA assessment could provide a 1-stop-shop for diagnosis, risk management, and decision-making on treatment.

Coronary Computed Tomography Angiography for Assesment of Stable Coronary Artery Disease – a Cost-effectiveness Perspective

Patients with chest pain presenting to the emergency room are currently investigated using either invasive coronary angiography (ICA) or noninvasive coronary computed tomography angiography (CCTA). ICA remains an expensive diagnostic tool and exposes patients to a high risk of periprocedural complication. Besides the currently available expansive economic evidence, there is still an important lingering issue: to establish, from the healthcare provider’s point of view, which is the most cost-effective investigation tool for the detection of significant coronary artery disease. The aim of this article is to present the latest developments in the field of imaging tools for the detection of coronary atherosclerosis in patients with chest pain, from the perspective of a cost-effectiveness analysis.

The usefulness of cardiac CT integrated with FFRCT for planning myocardial revascularization in complex coronary artery disease: a lesson from SYNTAX studies

After two decades of clinical use, during which coronary CT angiography (CCTA) was considered an appropriate method for the non-invasive assessment of patients with suspected stable coronary artery disease (CAD) and low-to-intermediate pretest likelihood of CAD, a growing body of literature is showing that CCTA may have also a clinical role in patients with high pretest likelihood of CAD, known CAD and complex and diffuse CAD. Particularly, the SYNTAX studies demonstrated the usefulness of CCTA in the field of non-invasive assessment of these patients and planning of interventional and surgical coronary procedures, thanks to its ability to combine, in a single method, precise stenosis quantification, accurate plaque characterization, functional assessment and selection of the revascularization modality for any individual patient and of the vessels that need to be revascularized. Of note, the SYNTAX III Revolution trial showed, in patients with three-vessel CAD, that treatment decision-making between PCI and CABG based on CCTA only has an almost perfect agreement with the treatment decision derived from invasive coronary angiography (ICA). Moreover, the SYNTAX Score II demonstrated a high degree of correlation between the two diagnostic strategies, suggesting the potential feasibility of a treatment decision-making based solely on non-invasive imaging and clinical information. New research prospects have opened up for the future to demonstrate the true feasibility and safety of this innovative approach in the clinical arena.

Coronary computed tomography angiography versus invasive coronary angiography: medical staff perceptions and diagnostic interest in Gaza-Palestine

BACKGROUND

Invasive coronary angiography (ICA) and coronary computed tomography angiography (CCTA) are used in the diagnosis of coronary artery disease (CAD). The medical benefits, as well as the ethical and logistical implications, should be explored, particularly in the scarcity of medical resources. We explore the perception of medical staff toward the interest of CCTA and ICA in diagnosis CAD to maximize the utility of both procedures.

METHODS

A triangulated observational, analytical prospective cohort study carried out among patients suspected with CAD who underwent CCTA and ICA. The quantitative part included 381 patients (250 underwent ICA and 131 underwent CCTA). The qualitative part included a purposive sample of two radiologists, three cardiologists, and two medical imaging specialists.

RESULTS

Low diagnostic yield of the ICA through 31.3% and 39.7% diagnosed without CAD and non-significant CAD, respectively. Risk factors such as the family history of heart disease, obesity, high cholesterol, and diabetes were with high frequency in the patients with significant CAD. The sensitivity, specificity, PPV, and NPV of CCTA technique was 94.74%, 94.23%, 92.31%, and 96.08% respectively. Cardiologist's perceptions focused on radiation concerns and difficulties for convincing patients to perform the CCTA procedure. Radiologists and medical imaging specialists focused on complete cooperation from the cardiologist to better preparation of patients to perform optimal CCTA procedures.

CONCLUSION

Efficient diagnostic benefits of CCTA and overuse of ICA for stable CAD are documented. Clear diagnostic strategy with medical, ethical, and logistical issues should be considered when selecting the CCTA or ICA for diagnosis CAD.

Machine learning insight into the role of imaging and clinical variables for the prediction of obstructive coronary artery disease and revascularization: An exploratory analysis of the CONSERVE study

BACKGROUND

Machine learning (ML) is able to extract patterns and develop algorithms to construct data-driven models. We use ML models to gain insight into the relative importance of variables to predict obstructive coronary artery disease (CAD) using the Coronary Computed Tomographic Angiography for Selective Cardiac Catheterization (CONSERVE) study, as well as to compare prediction of obstructive CAD to the CAD consortium clinical score (CAD2). We further perform ML analysis to gain insight into the role of imaging and clinical variables for revascularization.

METHODS

For prediction of obstructive CAD, the entire ICA arm of the study, comprising 719 patients was used. For revascularization, 1,028 patients were randomized to invasive coronary angiography (ICA) or coronary computed tomographic angiography (CCTA). Data was randomly split into 80% training 20% test sets for building and validation. Models used extreme gradient boosting (XGBoost).

RESULTS

Mean age was 60.6 ± 11.5 years and 64.3% were female. For the prediction of obstructive CAD, the AUC was significantly higher for ML at 0.779 (95% CI: 0.672-0.886) than for CAD2 (0.696 [95% CI: 0.594-0.798]) (P = 0.01). BMI, age, and angina severity were the most important variables. For revascularization, the model obtained an overall area under the receiver-operation curve (AUC) of 0.958 (95% CI = 0.933-0.983). Performance did not differ whether the imaging parameters used were from ICA (AUC 0.947, 95% CI = 0.903-0.990) or CCTA (AUC 0.941, 95% CI = 0.895-0.988) (P = 0.90). The ML model obtained sensitivity and specificity of 89.2% and 92.9%, respectively. Number of vessels with ≥70% stenosis, maximum segment stenosis severity (SSS) and body mass index (BMI) were the most important variables. Exclusion of imaging variables resulted in performance deterioration, with an AUC of 0.705 (95% CI 0.614-0.795) (P <0.0001).

CONCLUSIONS

For obstructive CAD, the ML model outperformed CAD2. BMI is an important variable, although currently not included in most scores. In this ML model, imaging variables were most associated with revascularization. Imaging modality did not influence model performance. Removal of imaging variables reduced model performance.

Effects of Deep Learning Reconstruction Technique in High-Resolution Non-contrast Magnetic Resonance Coronary Angiography at a 3-Tesla Machine

Purpose:

To evaluate the effects of deep learning reconstruction (DLR) in qualitative and quantitative image quality of non-contrast magnetic resonance coronary angiography (MRCA).

Methods:

Ten healthy volunteers underwent conventional MRCA (C-MRCA) and high-resolution (HR) MRCA on a 3T magnetic resonance imaging with a voxel size of 1.8 × 1.1 × 1.7 mm3 and 1.8 × 0.6 × 1.0 mm3, respectively, for C-MRCA and HR-MRCA. High-resolution magnetic resonance coronary angiography was also reconstructed with the DLR technique (DLR-HR-MRCA). We compared the contrast-to-noise ratio (CNR) and visual evaluation scores for vessel sharpness and traceability of proximal and distal coronary vessels on a 4-point scale among 3 image series.

Results:

The vascular CNR value on the C-MRCA and the DLR-HR-MRCA was significantly higher than that on the HR-MRCA in the proximal and distal coronary arteries (13.9 ± 6.4, 11.3 ± 4.4, and 7.8 ± 2.6 for C-MRCA, DLR-HR-MRCA, and HR-MRCA, P < .05, respectively). Mean visual evaluation scores for the vessel sharpness and traceability of proximal and distal coronary vessels were significantly higher on the HR-DLR-MRCA than the C-MRCA ( P < .05, respectively).

Conclusion:

Deep learning reconstruction significantly improved the CNR of coronary arteries on HR-MRCA, resulting in both higher visual image quality and better vessel traceability compared with C-MRCA.

The validity and applicability of CAD-RADS in the management of patients with coronary artery disease

BACKGROUND

The coronary artery disease reporting and data system (CAD-RADS) is designed for a uniform standardization of coronary computed tomography angiography (CCTA) reporting and further management recommendations of coronary artery disease (CAD). This study aimed to assess clinical validity, applicability, and reproducibility of CAD-RADS in the management of patients with CAD.

METHODS AND RESULTS

A single-center prospective study included 287 patients with clinically suspected or operated CAD who underwent CCTA. Four reviewers evaluated the CCTA images independently and assigned a CAD-RADS category to each patient. The invasive coronary angiography (ICA) was used as the reference standard for calculating diagnostic performance of CAD-RADS for categorizing the degree of coronary artery stenosis. The intra-class correlation (ICC) was used to test the inter-reviewer agreement (IRA). Reporting was provided to referring consultants according to the CAD-RADS. Based on ICA results, we have 156 patients with non-significant CAD and 131 patients with significant CAD. On a patient-based analysis, regarding those patients classified as CAD-RADS 4 and CAD-RADS 5 for predicting significant CAD, the CAD-RADS had a sensitivity, specificity, and an accuracy of 100%, 96.8 to 98.7%, and 98.3 to 99.3%, respectively, depending on the reviewer. There was an excellent IRA for CAD-RADS categories (ICC = 0.9862). The best cutoff value for predicting significant CAD was > CAD-RADS 3. Eighty-seven percentage of referring consultants considered CAD-RADS reporting system to be "quite helpful" or "completely helpful" for clinical decision-making in CAD.

CONCLUSION

CAD-RADS is valuable for improving CCTA structural reports and facilitating decision-making with high diagnostic accuracy and high reproducibility.

Effect of a calcium deblooming algorithm on accuracy of coronary computed tomography angiography

BACKGROUND

Coronary artery calcification is a significant contributor to reduced accuracy of coronary computed tomographic angiography (CTA) in the assessment of coronary artery disease severity. The aim of the current study is to assess the impact of a prototype calcium deblooming algorithm on the diagnostic accuracy of CTA.

METHODS

40 patients referred for invasive catheter angiography underwent CTA and invasive catheter angiography. The CTA were reconstructed using a standard soft tissue kernel (CTA_STAND) and a deblooming algorithm (CTA_DEBLOOM). CTA studies were read with and without the deblooming algorithm blinded to the invasive coronary angiogram findings. Sensitivity, specificity, accuracy, positive predictive value and negative predictive value for the detection of stenosis ≥50% or ≥70% were evaluated using quantitative coronary angiography as the reference standard. Image quality was assessed using a 5-point scale, and the presence of image artifact recorded.

RESULTS

All studies were diagnostic with 548 segments available for evaluation. Image score was 3.64 ± 0.72 with CTA_DEBLOOM, versus 3.56 ± 0.72 with CTA_STAND (p = 0.38). CTA_DEBLOOM had significantly less calcium blooming artifact than CTA_STAND (12.5% vs. 47.5%, p = 0.001). Based on a 50% stenosis threshold for defining significant disease, the Sensitivity/Specificity/PPV/NPV/Accuracy were 65.9/84.9/27.6/96.6/83.4 for CTA_DEBLOOM and 75.0/81.9/26.6/97.4/81.4 for CTA_STAND using a ≥50% threshold. CTA_DEBLOOM specificity was significantly higher than CTA_STAND (84.9% vs. 81.5%, p = 0.03), with no difference between the algorithms in sensitivity (p = 0.22), or accuracy (p = 0.15). These results remained unchanged when a stenosis threshold of ≥70% was used. Interobserver agreement was fair with both techniques (CTA_DEBLOOM k = 0.38, CTA_STAND k = 0.37).

CONCLUSION

In this proof of concept study, coronary calcification deblooming using a prototype post-processing algorithm is feasible and reduces calcium blooming with an improvement of the specificity of the CTA exam.

Effects of obesity on noninvasive test results in patients with suspected cardiac ischemia: Insights from the PROMISE trial

BACKGROUND

Obesity is a risk factor for coronary artery disease (CAD), but adiposity may mimic symptoms of CAD and reduce the accuracy of diagnostic testing.

METHODS

Patients from the PROMISE trial (n = 8889) were classified according to body mass index (BMI). We assessed relationships between BMI, physician's preference of functional test, test positivity, and results of invasive coronary angiography (Cath) using logistic regression models.

RESULTS

Nearly half (48%) of the patients had BMI ≥ 30 kg/m², and 20% had BMI ≥ 35. Providers were more likely to prefer nuclear myocardial perfusion imaging (MPI) over other functional tests as BMI increased. The rate of test positivity with coronary computed tomographic angiography (CTA) was not different (10% vs. 12%) in patients with BMI ≥35 vs. < 35. The same was true for stress echocardiogram and stress electrocardiogram (positivity 8-13%, P > 0.8 for both). In contrast, MPI was significantly more likely to be positive in those with BMI ≥35 vs. <35 (18% vs. 13%; P = 0.001). The likelihood of obstructive CAD at Cath did not differ with BMI ≥35 vs. <35 in patients having CTA (52% vs. 59%, P = 0.22), but among MPI patients, Cath positivity was only 29% with BMI ≥35 vs. 48% with BMI <35 (P = 0.005). Radiation exposure increased with higher BMI in both MPI and CTA groups.

CONCLUSIONS

Increasing levels of obesity adversely affect the diagnostic yield of MPI more than CTA. The degree of obesity should be considered when choosing evaluation strategies for patients with chest pain.

CLINICAL TRIAL REGISTRATION

PROMISE ClinicalTrials.gov number, NCT01174550.

Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks

Excellent image quality is a primary prerequisite for diagnostic non-invasive coronary CT angiography. Artifacts due to cardiac motion may interfere with detection and diagnosis of coronary artery disease and render subsequent treatment decisions more difficult. We propose deep-learning-based measures for coronary motion artifact recognition and quantification in order to assess the diagnostic reliability and image quality of coronary CT angiography images. More specifically, the application, steering and evaluation of motion compensation algorithms can be triggered by these measures. A Coronary Motion Forward Artifact model for CT data (CoMoFACT) is developed and applied to clinical cases with excellent image quality to introduce motion artifacts using simulated motion vector fields. The data required for supervised learning is generated by the CoMoFACT from 17 prospectively ECG-triggered clinical cases with controlled motion levels on a scale of 0-10. Convolutional neural networks achieve an accuracy of 93.3% ± 1.8% for the classification task of separating motion-free from motion-perturbed coronary cross-sectional image patches. The target motion level is predicted by a corresponding regression network with a mean absolute error of 1.12 ± 0.07. Transferability and generalization capabilities are demonstrated by motion artifact measurements on eight additional CCTA cases with real motion artifacts.

Coronary CT Angiography: Reversal of Earlier Utilization Trends

PURPOSE

To assess recent trends in utilization of coronary CT angiography (CCTA), based upon place of service and provider specialty.

MATERIALS AND METHODS

The nationwide Medicare Part B master files for 2006 through 2016 were the data source. Current Procedural Terminology, version 4 codes for CCTA were selected. The files provided procedure volume for each code. Utilization rates per 100,000 Medicare fee-for-service enrollees were then calculated. Medicare's place-of-service codes were used to identify CCTAs performed in private offices, hospital outpatient departments (HOPDs), emergency departments (EDs), and inpatient settings. Physician specialty codes were used to identify CCTAs interpreted by radiologists, cardiologists, and all other physicians as a group. Medicare practice share was defined as the percent of total Medicare utilization that was billed by each specialty.

RESULTS

The total utilization rate of CCTA in the Medicare population rose sharply from 2006 to 2007, peaking at 210.3 per 100,000 enrollees in 2007. Radiologists' CCTA practice share in 2007 was 32%, compared with 60% for cardiologists. The overall utilization rate then declined to a nadir of 107.1 per 100,000 enrollees in 2013, but subsequently increased to 131.0 by 2016. By that year, radiologists' share of CCTA practice had risen to 58%, compared with 38% for cardiologists. HOPD utilization increased sharply since 2010, primarily among radiologists. In EDs and inpatient settings, greater utilization has also occurred recently, primarily among radiologists. By contrast, private office utilization has dropped sharply since 2007.

CONCLUSION

After years of declining utilization, the utilization rate of CCTA is now increasing, predominantly among radiologists.

ECG-gated CT angiography of the thoracic aorta: the importance of evaluating the coronary arteries

AIM

To evaluate the feasibility of coronary artery disease (CAD) evaluation using electrocardiogram-gated computed tomography CT of the thoracic aorta.

MATERIALS AND METHODS

A total of 477 patients, who underwent CT angiography of the thoracic aorta, were included retrospectively. Dose-length products (DLP) were recorded. Two blinded readers graded image quality of the coronary arteries on a three-point scale. Coronary artery stenosis has only been reported if considered significant, i.e., ≥50%. The type of plaque responsible for the stenosis was considered. The normal distribution of the data was assessed using Shapiro-Wilk and Anderson-Darling tests. Results were expressed as means and standard deviations and percentages. Inter-reader agreements were analysed by calculating the intraclass correlation coefficient, and by using Cohen kappa statistics.

RESULTS

The mean DLP was 566±90.4 mGy∙cm, corresponding to an effective dose of 9.6±1.5 mSv. Five point three percent of asymptomatic patients were positive for CAD with stenosis ≥50%. All patients with coronary stenosis presented with a soft plaque. Two anomalous coronary origins were found. The inter-reader agreement was excellent in defining both the quality of the examination and the degree of coronary stenosis (k=0.85).

CONCLUSION

The opportunity to prove the presence of CAD in asymptomatic patients during a ECG-gated CT of the thoracic aorta can have an extremely important clinical impact, promoting the best therapeutic pathway for the patient. Therefore, coronary arteries should always be analysed carefully and reported in ECG-gated CT angiography of the thoracic aorta.

Diagnostic yield and accuracy of coronary CT angiography after abnormal nuclear myocardial perfusion imaging

We aimed to determine the diagnostic yield and accuracy of coronary CT angiography (CCTA) in patients referred for invasive coronary angiography (ICA) based on clinical concern for coronary artery disease (CAD) and an abnormal nuclear stress myocardial perfusion imaging (MPI) study. We enrolled 100 patients (84 male, mean age 59.6 ± 8.9 years) with an abnormal MPI study and subsequent referral for ICA. Each patient underwent CCTA prior to ICA. We analyzed the prevalence of potentially obstructive CAD (≥50% stenosis) on CCTA and calculated the diagnostic accuracy of ≥50% stenosis on CCTA for the detection of clinically significant CAD on ICA (defined as any ≥70% stenosis or ≥50% left main stenosis). On CCTA, 54 patients had at least one ≥50% stenosis. With ICA, 45 patients demonstrated clinically significant CAD. A positive CCTA had 100% sensitivity and 84% specificity with a 100% negative predictive value and 83% positive predictive value for clinically significant CAD on a per patient basis in MPI positive symptomatic patients. In conclusion, almost half (48%) of patients with suspected CAD and an abnormal MPI study demonstrate no obstructive CAD on CCTA.

Myocardial Assessment with Cardiac CT: Ischemic Heart Disease and Beyond

PURPOSE OF REVIEW

The aim of this review is to highlight recent advancements, current trends, and the expanding role for cardiac CT (CCT) in the evaluation of ischemic heart disease, nonischemic cardiomyopathies, and some specific congenital myocardial disease states.

RECENT FINDINGS

CCT is a highly versatile imaging modality for the assessment of numerous cardiovascular disease states. Coronary CT angiography (CCTA) is now a well-established first-line imaging modality for the exclusion of significant coronary artery disease (CAD); however, CCTA has modest positive predictive value and specificity for diagnosing obstructive CAD in addition to limited capability to evaluate myocardial tissue characteristics.

SUMMARY

CTP, when combined with CCTA, presents the potential for full functional and anatomic assessment with a single modality. CCT is a useful adjunct in select patients to both TTE and CMR in the evaluation of ventricular volumes and systolic function. Newer applications, such as dynamic CTP and DECT, are promising diagnostic tools offering the possibility of more quantitative assessment of ischemia. The superior spatial resolution and volumetric acquisition of CCT has an important role in the diagnosis of other nonischemic causes of cardiomyopathies.

Prognostic Value of Coronary Artery Calcium in the PROMISE Study (Prospective Multicenter Imaging Study for Evaluation of Chest Pain)

BACKGROUND

Coronary artery calcium (CAC) is an established predictor of future major adverse atherosclerotic cardiovascular events in asymptomatic individuals. However, limited data exist as to how CAC compares with functional testing (FT) in estimating prognosis in symptomatic patients.

METHODS

In the PROMISE trial (Prospective Multicenter Imaging Study for Evaluation of Chest Pain), patients with stable chest pain (or dyspnea) and intermediate pretest probability for obstructive coronary artery disease were randomized to FT (exercise electrocardiography, nuclear stress, or stress echocardiography) or anatomic testing. We evaluated those who underwent CAC testing as part of the anatomic evaluation (n=4209) and compared that with results of FT (n=4602). We stratified CAC and FT results as normal or mildly, moderately, or severely abnormal (for CAC: 0, 1-99 Agatston score [AS], 100-400 AS, and >400 AS, respectively; for FT: normal, mild=late positive treadmill, moderate=early positive treadmill or single-vessel ischemia, and severe=large ischemic region abnormality). The primary end point was all-cause death, myocardial infarction, or unstable angina hospitalization over a median follow-up of 26.1 months. Cox regression models were used to calculate hazard ratios (HRs) and C statistics to determine predictive and discriminatory values.

RESULTS

Overall, the distribution of normal or mildly, moderately, or severely abnormal test results was significantly different between FT and CAC (FT: normal, n=3588 [78.0%]; mild, n=432 [9.4%]; moderate, n=217 [4.7%]; severe, n=365 [7.9%]; CAC: normal, n=1457 [34.6%]; mild, n=1340 [31.8%]; moderate, n=772 [18.3%]; severe, n=640 [15.2%]; P<0.0001). Moderate and severe abnormalities in both arms robustly predicted events (moderate: CAC: HR, 3.14; 95% confidence interval, 1.81-5.44; and FT: HR, 2.65; 95% confidence interval, 1.46-4.83; severe: CAC: HR, 3.56; 95% confidence interval, 1.99-6.36; and FT: HR, 3.88; 95% confidence interval, 2.58-5.85). In the CAC arm, the majority of events (n=112 of 133, 84%) occurred in patients with any positive CAC test (score >0), whereas fewer than half of events occurred in patients with mildly, moderately, or severely abnormal FT (n=57 of 132, 43%; P<0.001). In contrast, any abnormality on FT was significantly more specific for predicting events (78.6% for FT versus 35.2% for CAC; P<0.001). Overall discriminatory ability in predicting the primary end point of mortality, nonfatal myocardial infarction, and unstable angina hospitalization was similar and fair for both CAC and FT (C statistic, 0.67 versus 0.64). Coronary computed tomographic angiography provided significantly better prognostic information compared with FT and CAC testing (C index, 0.72).

CONCLUSIONS

Among stable outpatients presenting with suspected coronary artery disease, most patients experiencing clinical events have measurable CAC at baseline, and fewer than half have any abnormalities on FT. However, an abnormal FT was more specific for cardiovascular events, leading to overall similarly modest discriminatory abilities of both tests.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov. Unique identifier: NCT01174550.

Leukemic Ischemia: A Case of Myocardial Infarction Secondary to Leukemic Cardiac Involvement

We report a case of a 39-year-old male who presented to the emergency department with acute chest pain while being in remission from T-cell acute lymphoblastic leukemia (T-ALL). Cardiac markers were elevated and EKG revealed ischemic changes compatible with acute myocardial ischemia. Coronary computed tomography angiography (CCTA) showed calcium-free coronary arteries and soft tissue myocardial infiltration suggestive of cardiac leukemia. A bone marrow biopsy confirmed recurrence of T-ALL, and patient was successfully treated with chemotherapy. We discuss the prospective diagnosis of myopericardial leukemic involvement and the role of CCTA in diagnosis and perform a literature review.

Stress testing and non-invasive coronary angiography in patients with suspected coronary artery disease: time for a new paradigm

Diagnosis and management of coronary artery disease represents major challenges to our health care system, affecting millions of patients each year. Until recently, the diagnosis of coronary artery disease was possible only through cardiac catheterization and invasive coronary angiography. To avoid the risks of an invasive procedure, stress testing is often employed for an initial assessment of patients with suspected coronary artery disease, serving as a gatekeeper for cardiac catheterization. With the emergence of non-invasive coronary angiography, the question arises if such a strategy is still sensible, particularly, in view of only a modest agreement between stress testing results and the presence of coronary artery disease established by cardiac catheterization. Much data in support of the diagnostic accuracy and prognostic value of non-invasive coronary angiography by computed tomography have emerged within the last few years. These data challenge the role of stress testing as the initial imaging modality in patients with suspected coronary artery disease. This article reviews the clinical utility, limitations, as well as the hazards of stress testing compared with non-invasive coronary artery imaging by computed tomography. Finally, the implications of this review are discussed in relation to clinical practice.