Incremental Prognostic Value of Cardiac Computed Tomography in Coronary Artery Disease Using CONFIRM

Deep Learning-Based Automated Labeling of Coronary Segments for Structured Reporting of Coronary Computed Tomography Angiography in Accordance With Society of Cardiovascular Computed Tomography Guidelines

PURPOSE

To evaluate a novel deep learning (DL)-based automated coronary labeling approach for structured reporting of coronary artery disease according to the guidelines of the Society of Cardiovascular Computed Tomography (CT) on coronary CT angiography (CCTA).

PATIENTS AND METHODS

A retrospective cohort of 104 patients (60.3 ± 10.7 y, 61% males) who had undergone prospectively electrocardiogram-synchronized CCTA were included. Coronary centerlines were automatically extracted, labeled, and validated by 2 expert readers according to Society of Cardiovascular CT guidelines. The DL algorithm was trained on 706 radiologist-annotated cases for the task of automatically labeling coronary artery centerlines. The architecture leverages tree-structured long short-term memory recurrent neural networks to capture the full topological information of the coronary trees by using a two-step approach: a bottom-up encoding step, followed by a top-down decoding step. The first module encodes each sub-tree into fixed-sized vector representations. The decoding module then selectively attends to the aggregated global context to perform the local assignation of labels. To assess the performance of the software, percentage overlap was calculated between the labels of the algorithm and the expert readers.

RESULTS

A total number of 1491 segments were identified. The artificial intelligence-based software approach yielded an average overlap of 94.4% compared with the expert readers' labels ranging from 87.1% for the posterior descending artery of the right coronary artery to 100% for the proximal segment of the right coronary artery. The average computational time was 0.5 seconds per case. The interreader overlap was 96.6%.

CONCLUSIONS

The presented fully automated DL-based coronary artery labeling algorithm provides fast and precise labeling of the coronary artery segments bearing the potential to improve automated structured reporting for CCTA.

Incremental prognostic value of downstream positron emission tomography perfusion imaging after coronary computed tomography angiography: a study using machine learning

AIMS

To evaluate the incremental value of positron emission tomography (PET) myocardial perfusion imaging (MPI) over coronary computed tomography angiography (CCTA) in predicting short- and long-term outcome using machine learning (ML) approaches.

METHODS AND RESULTS

A total of 2411 patients with clinically suspected coronary artery disease (CAD) underwent CCTA, out of whom 891 patients were admitted to downstream PET MPI for haemodynamic evaluation of obstructive coronary stenosis. Two sets of Extreme Gradient Boosting (XGBoost) ML models were trained, one with all the clinical and imaging variables (including PET) and the other with only clinical and CCTA-based variables. Difference in the performance of the two sets was analysed by means of area under the receiver operating characteristic curve (AUC). After the removal of incomplete data entries, 2284 patients remained for further analysis. During the 8-year follow-up, 210 adverse events occurred including 59 myocardial infarctions, 35 unstable angina pectoris, and 116 deaths. The PET MPI data improved the outcome prediction over CCTA during the first 4 years of the observation time and the highest AUC was at the observation time of Year 1 (0.82, 95% confidence interval 0.804-0.827). After that, there was no significant incremental prognostic value by PET MPI.

CONCLUSION

PET MPI variables improve the prediction of adverse events beyond CCTA imaging alone for the first 4 years of follow-up. This illustrates the complementary nature of anatomic and functional information in predicting the outcome of patients with suspected CAD.

Prognostic Value of Machine Learning-based Time-to-Event Analysis Using Coronary CT Angiography in Patients with Suspected Coronary Artery Disease

Purpose

To assess the long-term prognostic value of a machine learning (ML) approach in time-to-event analyses incorporating coronary CT angiography (CCTA)-derived and clinical parameters in patients with suspected coronary artery disease.

Materials and Methods

The retrospective analysis included patients with suspected coronary artery disease who underwent CCTA between October 2004 and December 2017. Major adverse cardiovascular events were defined as the composite of all-cause death, myocardial infarction, unstable angina, or late revascularization (>90 days after index scan). Clinical and CCTA-derived parameters were assessed as predictors of major adverse cardiovascular events and incorporated into two models: a Cox proportional hazards model with recursive feature elimination and an ML model based on random survival forests. Both models were trained and validated by employing repeated nested cross-validation. Harrell concordance index (C-index) was used to assess the predictive power.

Results

A total of 5457 patients (mean age, 61 years ± 11 [SD]; 3648 male patients) were evaluated. The predictive power of the ML model (C-index, 0.74; 95% CI: 0.71, 0.76) was significantly higher than the Cox model (C-index, 0.71; 95% CI: 0.68, 0.74; P = .02). The ML model also outperformed the segment stenosis score (C-index, 0.69; 95% CI: 0.66, 0.72; P < .001), which was the best performing CCTA-derived parameter, and patient age (C-index, 0.66; 95% CI: 0.63, 0.69; P < .001), the best performing clinical parameter.

Conclusion

An ML model for time-to-event analysis based on random survival forests had higher performance in predicting major adverse cardiovascular events compared with established clinical or CCTA-derived metrics and a conventional Cox model.Keywords: Machine Learning, CT Angiography, Cardiac, Arteries, Heart, Arteriosclerosis, Coronary Artery DiseaseSupplemental material is available for this article.© RSNA, 2023.

Opportunities and Challenges of Computed Tomography Coronary Angiography in the Investigation of Chest Pain in the Emergency Department-A Narrative Review

Chest pain is one of the most common presentations to emergency departments. However, only 5.1% will be diagnosed with an acute coronary syndrome, representing considerable time and expense in the diagnosis and investigation of the patients eventually found not to be suffering from an acute coronary syndrome. PubMed and Medline databases were searched with variations of the terms "chest pain", "emergency department", "computed tomography coronary angiography". After review, 52 articles were included. Computed tomography coronary angiography (CTCA) is a class I endorsement for investigating chest pain in major international societal guidelines. CTCA offers excellent sensitivity and negative predictive value in identifying patients with coronary disease, with prognostic data impacting patient management. If CTCA is to be applied to all comers, it is pertinent to discuss the advantages and potential pitfalls if use in the Australian system is to be increased.

Deep learning image reconstruction algorithm: impact on image quality in coronary computed tomography angiography

PURPOSE

To perform a comprehensive intraindividual objective and subjective image quality evaluation of coronary CT angiography (CCTA) reconstructed with deep learning image reconstruction (DLIR) and to assess correlation with routinely applied hybrid iterative reconstruction algorithm (ASiR-V).

MATERIAL AND METHODS

Fifty-one patients (29 males) undergoing clinically indicated CCTA from April to December 2021 were prospectively enrolled. Fourteen datasets were reconstructed for each patient: three DLIR strength levels (DLIR_L, DLIR_M, and DLIR_H), ASiR-V from 10% to 100% in 10%-increment, and filtered back-projection (FBP). Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) determined objective image quality. Subjective image quality was assessed with a 4-point Likert scale. Concordance between reconstruction algorithms was assessed by Pearson correlation coefficient.

RESULTS

DLIR algorithm did not impact vascular attenuation (P ≥ 0.374). DLIR_H showed the lowest noise, comparable with ASiR-V 100% (P = 1) and significantly lower than other reconstructions (P ≤ 0.021). DLIR_H achieved the highest objective quality, with SNR and CNR comparable to ASiR-V 100% (P = 0.139 and 0.075, respectively). DLIR_M obtained comparable objective image quality with ASiR-V 80% and 90% (P ≥ 0.281), while achieved the highest subjective image quality (4, IQR: 4-4; P ≤ 0.001). DLIR and ASiR-V datasets returned a very strong correlation in the assessment of CAD (r = 0.874, P = 0.001).

CONCLUSION

DLIR_M significantly improves CCTA image quality and has very strong correlation with routinely applied ASiR-V 50% dataset in the diagnosis of CAD.

Coronary stenosis is a risk marker for impaired cardiac function on cardiopulmonary exercise test

Background

Cardiac function varies in different ways in ischemic heart disease (IHD). We aimed to evaluate the characteristics of cardiac function on cardiopulmonary exercise test (CPET) in IHD with different coronary stenoses.

Methods

Totally 614 patients with IHD were divided into non-obstructive coronary artery disease (NOCAD) (stenosis < 50%), obstructive coronary artery disease (OCAD) (stenosis 50-90%) and severe OCAD ( stenosis > 90%) according to the coronary angiography. And 101 healthy volunteers as controls. All participants performed CPET to assess cardiac function by oxygen uptake (VO₂), estimated cardiac output (CO), and heart rate (HR).

Results

Generally, the values of VO₂, CO, and HR in IHD were significantly lower than in healthy volunteers. Among 289 NOCAD, 132 OCAD, and 193 severe OCAD, significantly decreased values of VO₂, CO, HR were observed (VO₂ peak: 16.01 ± 4.11 vs. 15.66 ± 4.14 vs. 13.33 ± 3.4 mL/min/kg; CO: 6.96 ± 2.34 vs. 6.87 ± 2.37 vs. 6.05 ± 1.79 L/min; HR: 126.44 ± 20.53 vs. 115.15 ± 18.78 vs. 109.07 ± 16.23 bpm, P < 0.05). NOCAD had significantly lower VO₂ at anaerobic threshold (-1.35, 95%CI -2.16 - -0.54) and VO₂ peak (-2.05, 95%CI -3.18 - -0.93) compared with healthy volunteers after adjustment. All IHD patients were associated with low stroke volume and inefficient gas exchange (P < 0.05).

Conclusion

IHD with increasing atherosclerotic burdens were associated with impaired cardiac output and chronotropic response on CPET. NOCAD should be given more early prevention and rigorous follow-up.

Association of MMP9 with adverse features of plaque progression and residual inflammatory risk in patients with chronic coronary syndrome (CCS)

BACKGROUND AND AIMS

MMP-9 is a predictor of atherosclerotic plaque instability and adverse cardiovascular events, but longitudinal data on the association between MMP9 and coronary disease progression are lacking. This study is aimed at investigating whether MMP9 is associated with atherosclerotic plaque progression and the related molecular basis in stable patients with chronic coronary syndrome (CCS).

METHODS

MMP9 serum levels were measured in 157 CCS patients (58 ± 8 years of age; 66% male) undergoing coronary computed tomography angiography at baseline and after a follow up period of 6.5 ± 1.1 years to assess progression of Total, Fibrous, Fibro-fatty, Necrotic Core, and Dense Calcium plaque volumes (PV). Gene expression analysis was evaluated in whole blood using a transcriptomic approach by RNA-seq.

RESULTS

At multivariate analysis, serum MMP9 was associated with annual change of Total and Necrotic Core PV (Coefficient 3.205, SE 1.321, P = 0.017; 1.449, SE 0.690, P = 0.038, respectively), while MMP9 gene expression with Necrotic Core PV (Coefficient 70.559, SE 32.629, P = 0.034), independently from traditional cardiovascular risk factors, medications, and presence of obstructive CAD. After transcriptomic analysis, MMP9 expression was linked to expression of genes involved in the innate immunity.

CONCLUSIONS

Among CCS patients, MMP9 is an independent predictive marker of progression of adverse coronary plaques, possibly reflecting the activity of inflammatory pathways conditioning adverse plaque phenotypes. Thus, blood MMP9 might be used for the identification of patients with residual risk even with optimal management of classical cardiovascular risk factors who may derive the greatest benefit from targeted anti-inflammatory drugs.

Association between circulating oxidized OxLDL/LDL-C ratio and the severity of coronary atherosclerosis, along with other emerging biomarkers of cardiovascular disease in patients with type 2 diabetes

AIMS

The aim of this study was to evaluate the association between circulating oxLDL/LDL-C ratio and the severity of coronary atherosclerosis, along with other emerging biomarkers of cardiovascular disease (CVD) in patients with type 2 diabetes.

METHODS

We recruited 152 patients with type 2 diabetes for our study. ELISA measured the plasma levels of oxLDL and other biomarkers. The severity of coronary lesions was evaluated using Gensini scores, which were calculated based on results of coronary computed tomographic angiography (CCTA). All patients were allocated into four groups according to CCTA findings and Gensini score: normal group (score = 0), mild coronary atherosclerosis group (0 < scores ≤ 3), moderate coronary atherosclerosis group (3.01 ≤ scores ≤ 32.67) and severe coronary atherosclerosis group (32.68 ≤ scores ≤ 180). Association between the oxLDL/LDL-C ratio and the severity of coronary atherosclerosis were evaluated using logistic regression models.

RESULTS

Multivariate logistic regression analysis showed that the oxLDL/LDL-C ratio was positively associated with severity of coronary atherosclerosis (OR 2.03, 95% CI 1.31-3.14, p < 0.01). Interleukin 33 (IL33) correlated positively with oxLDL/LDL-C ratio (r = 0.274, p < 0.01). However, vascular cell adhesion molecular-1 (VCAM-1) had similar trends with oxLDL/LDL-C ratio in these 4 groups.

CONCLUSIONS

OxLDL/LDL-C ratio is considered as a potential biomarker in patients with diabetes for early recognition and intervention of severe coronary atherosclerosis, and will be more effective if tested IL33 and VCAM-1 at the same time.

Impact of machine-learning-based coronary computed tomography angiography-derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

OBJECTIVES

To evaluate feasibility and diagnostic performance of coronary CT angiography (CCTA)-derived fractional flow reserve (CT-FFR) for detection of significant coronary artery disease (CAD) and decision-making in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR) to potentially avoid additional pre-TAVR invasive coronary angiography (ICA).

METHODS

Consecutive patients with severe AS (n = 95, 78.6 ± 8.8 years, 53% female) undergoing pre-procedural TAVR-CT followed by ICA with quantitative coronary angiography were retrospectively analyzed. CCTA datasets were evaluated using CAD Reporting and Data System (CAD-RADS) classification. CT-FFR measurements were computed using an on-site machine-learning algorithm. A combined algorithm was developed for decision-making to determine if ICA is needed based on pre-TAVR CCTA: [1] all patients with CAD-RADS ≥ 4 are referred for ICA; [2] patients with CAD-RADS 2 and 3 are evaluated utilizing CT-FFR and sent to ICA if CT-FFR ≤ 0.80; [3] patients with CAD-RADS < 2 or CAD-RADS 2-3 and normal CT-FFR are not referred for ICA.

RESULTS

Twelve patients (13%) had significant CAD (≥ 70% stenosis) on ICA and were treated with PCI. Twenty-eight patients (30%) showed CT-FFR ≤ 0.80 and 24 (86%) of those were reported to have a maximum stenosis ≥ 50% during ICA. Using the proposed algorithm, significant CAD could be identified with a sensitivity, specificity, and positive and negative predictive value of 100%, 78%, 40%, and 100%, respectively, potentially decreasing the number of necessary ICAs by 65 (68%).

CONCLUSION

Combination of CT-FFR and CAD-RADS is able to identify significant CAD pre-TAVR and bears potential to significantly reduce the number of needed ICAs.

KEY POINTS

• Coronary CT angiography-derived fractional flow reserve (CT-FFR) using machine learning together with the CAD Reporting and Data System (CAD-RADS) classification safely identifies significant coronary artery disease based on quantitative coronary angiography in patients prior to transcatheter aortic valve replacement. • The combination of CT-FFR and CAD-RADS enables decision-making and bears the potential to significantly reduce the number of needed invasive coronary angiographies.

Longitudinal Quantitative Assessment of Coronary Atherosclerotic Plaque Burden Related to Serum Hemoglobin Levels

Background

Despite a potential role of hemoglobin in atherosclerosis, data on coronary plaque volume changes (PVC) related to serum hemoglobin levels are limited.

Objectives

The authors sought to evaluate coronary atherosclerotic plaque burden changes related to serum hemoglobin levels using serial coronary computed tomographic angiography (CCTA).

Methods

A total of 830 subjects (age 61 ± 10 years, 51.9% male) who underwent serial CCTA were analyzed. The median interscan period was 3.2 (IQR: 2.5-4.4) years. Quantitative assessment of coronary plaques was performed at both scans. All participants were stratified into 4 groups based on the quartile of baseline hemoglobin levels. Annualized total PVC (mm³/year) was defined as total PVC divided by the interscan period.

Results

Baseline total plaque volume (mm³) was not different among all groups (group I [lowest]: 34.1 [IQR: 0.0-127.4] vs group II: 28.8 [IQR: 0.0-123.0] vs group III: 49.9 [IQR: 5.6-135.0] vs group IV [highest]: 34.3 [IQR: 0.0-130.7]; P = 0.235). During follow-up, serum hemoglobin level changes (Δ hemoglobin; per 1 g/dL) was related to annualized total PVC (β = −0.114) in overall participants (P < 0.05). After adjusting for age, sex, traditional risk factors, baseline hemoglobin and creatinine levels, baseline total plaque volume, and the use of aspirin, beta-blocker, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, and statin, Δ hemoglobin significantly affected annualized total PVC in only the composite of groups I and II (β = −2.401; P = 0.004).

Conclusions

Serial CCTA findings suggest that Δ hemoglobin has an independent effect on coronary atherosclerosis. This effect might be influenced by baseline hemoglobin levels. (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging [PARADIGM]; NCT02803411)

Integrating Coronary Plaque Information from CCTA by ML Predicts MACE in Patients with Suspected CAD

Conventional prognostic risk analysis in patients undergoing noninvasive imaging is based upon a limited selection of clinical and imaging findings, whereas machine learning (ML) algorithms include a greater number and complexity of variables. Therefore, this paper aimed to explore the predictive value of integrating coronary plaque information from coronary computed tomographic angiography (CCTA) with ML to predict major adverse cardiovascular events (MACEs) in patients with suspected coronary artery disease (CAD). Patients who underwent CCTA due to suspected coronary artery disease with a 30-month follow-up for MACEs were included. We collected demographic characteristics, cardiovascular risk factors, and information on coronary plaques by analyzing CCTA information (plaque length, plaque composition and coronary artery stenosis of 18 coronary artery segments, coronary dominance, myocardial bridge (MB), and patients with vulnerable plaque) and follow-up information (cardiac death, nonfatal myocardial infarction and unstable angina requiring hospitalization). An ML algorithm was used for survival analysis (CoxBoost). This analysis showed that chest symptoms, the stenosis severity of the proximal anterior descending branch, and the stenosis severity of the middle right coronary artery were among the top three variables in the ML model. After the 22nd month of follow-up, in the testing dataset, ML showed the largest C-index and AUC compared with Cox regression, SIS, SIS score + clinical factors, and clinical factors. The DCA of all the models showed that the net benefit of the ML model was the highest when the treatment threshold probability was between 1% and 9%. Integrating coronary plaque information from CCTA based on ML technology provides a feasible and superior method to assess prognosis in patients with suspected coronary artery disease over an approximately three-year period.

Cardiovascular risk stratification by coronary computed tomography angiography imaging: current state-of-the-art

Current cardiovascular risk stratification by use of clinical risk score systems or plasma biomarkers is good but less than satisfactory in identifying patients at residual risk for coronary events. Recent clinical evidence puts now further emphasis on the role of coronary anatomy assessment by coronary computed tomography angiography (CCTA) for the management of patients with stable ischaemic heart disease. Available computed tomography (CT) technology allows the quantification of plaque burden, identification of high-risk plaques, or the functional assessment of coronary lesions for ischaemia detection and revascularization for refractory angina symptoms. The current CT armamentum is also further enhanced by perivascular Fat Attenuation Index (FAI), a non-invasive metric of coronary inflammation, which allows for the first time the direct quantification of the residual vascular inflammatory burden. Machine learning and radiomic features' extraction and spectral CT for tissue characterization are also expected to maximize the diagnostic and prognostic yield of CCTA. The combination of anatomical, functional, and biological information on coronary circulation by CCTA offers a unique toolkit for the risk stratification of patients, and patient selection for targeted aggressive prevention strategies. We hereby provide a review of the current state-of-the art in the field and discuss how integrating the full capacities of CCTA into clinical care pathways opens new opportunities for the tailored management of coronary artery disease.

Beyond Coronary CT Angiography: CT Fractional Flow Reserve and Perfusion

심장 전산화단층촬영은 비약적인 기술발전과 다양한 연구 결과를 바탕으로 심혈관위험 계층화와 치료 결정을 위한 관상동맥 질환의 진단과 예후 평가성능이 입증되었다. 전산화단층촬영 관상동맥조영술은 폐쇄성 관상동맥 질환에 대한 음성 예측도가 높아서 침습적 혈관조영술의 빈도를 줄일 수 있는 관상동맥 질환 관련 검사의 관문으로 부상했지만, 진단특이도가 상대적으로 낮다. 하지만 심장 전산화단층촬영을 이용한 분획혈류예비력과 심근관류를 분석하여 관상동맥 질환의 혈역학적 유의성을 확인하는 기능적 평가를 통해 그 한계를 극복할 수 있다. 최근에는 이를 보다 객관적이고 재현 가능하도록 인공지능을 접목하는 연구들이 활발히 진행되고 있다. 본 종설에서는 심장 전산화단층촬영의 기능적 영상화 기법들에 대해 알아보고자 한다.

Coronary computed tomography angiography in patients with stable coronary artery disease

The treatment of coronary artery disease (CAD), which is defined by stable anatomical atherosclerotic and functional alterations of epicardial vessels or microcirculation, focuses on managing intermittent angina symptoms and preventing major adverse cardiovascular events with optimal medical therapy. When patients with known CAD present with angina and no acute coronary syndrome, they have historically been evaluated with a variety of noninvasive stress tests that utilize electrocardiography, radionuclide scintigraphy, echocardiography, or magnetic resonance imaging for determining the presence and extent of inducible myocardial ischemia. Patient event-free survival, however, is largely driven by the coronary atherosclerotic disease burden, which is not directly assessed by functional testing. Direct evaluation of coronary atherosclerotic disease by coronary computed tomography angiography (coronary CTA) has emerged as the first line noninvasive imaging modality as it improves diagnostic accuracy and positively influences clinical management. Compared to functional assessment of CAD, coronary CTA-guided management results in improved patient outcomes by facilitating prevention of myocardial infarction. Other strengths of coronary CTA include detailed atherosclerotic plaque characterization and the ability to assess functional significance of specific lesions, which may further improve risk assessment and prognosis and lead to more appropriate referrals for additional testing, such as invasive coronary angiography.

Understanding the predictive value and methods of risk assessment based on coronary computed tomographic angiography in populations with coronary artery disease: a review

Risk assessment in coronary artery disease plays an essential role in the early identification of high-risk patients. However, conventional invasive imaging procedures all require long intraprocedural times and high costs. The rapid development of coronary computed tomographic angiography (CCTA) and related image processing technology has facilitated the formulation of noninvasive approaches to perform comprehensive evaluations. Evidence has shown that CCTA has outstanding performance in identifying the degree of stenosis, plaque features, and functional reserve. Moreover, advancements in radiomics and machine learning allow more comprehensive interpretations of CCTA images. This paper reviews conventional as well as novel diagnostic and risk assessment tools based on CCTA.

Increased long-term mortality in women with high left ventricular ejection fraction: data from the CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) long-term registry

AIMS

There are significant sex-specific differences in left ventricular ejection fraction (LVEF), with a higher LVEF being observed in women. We sought to assess the clinical relevance of an increased LVEF in women and men.

METHODS AND RESULTS

A total of 4632 patients from the CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry (44.8% women; mean age 58.7 ± 13.2 years in men and 59.5 ± 13.3 years in women, P = 0.05), in whom LVEF was measured by cardiac computed tomography, were categorized according to LVEF (low <55%, normal 55-65%, and high >65%). The prevalence of high LVEF was similar in both sexes (33.5% in women and 32.5% in men, P = 0.46). After 6 years of follow-up, no difference in mortality was observed in patients with high LVEF in the overall cohort (P = 0.41). When data were stratified by sex, women with high LVEF died more often from any cause as compared to women with normal LVEF (8.6% vs. 7.1%, log rank P = 0.032), while an opposite trend was observed in men (5.8% vs. 6.8% in normal LVEF, log rank P = 0.89). Accordingly, a first order interaction term of male sex and high LVEF was significant (hazard ratios 0.63, 95% confidence intervals 0.41-0.98, P = 0.043) in a Cox regression model of all-cause mortality adjusted for age, cardiovascular risk factors, and severity of coronary artery disease (CAD).

CONCLUSION

Increased LVEF is highly prevalent in patients referred for evaluation of CAD and is associated with an increased risk of death in women, but not in men. Differentiating between normal and hyperdynamic left ventricles might improve risk stratification in women with CAD.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT01443637.

Higher prevalence of incidental findings identified upon coronary calcium score assessment in type 2 and type 3 diabetes versus type 1 diabetes

Aim

Noninvasive assessment of infraclinic coronary atherosclerosis by coronary artery calcium score (CAC) measurement leads to the identification of incidental findings. The aim of this study was to determine the prevalence of incidental findings following systematic CAC assessment in diabetic patients with high cardiovascular risk, to identify the determinants, and to assess the midterm consequences of these findings in patient care.

Methods

732 consecutive asymptomatic patients (187 type 1 diabetes (TD1), 482 type 2 diabetes (TD2) and 63 type 3 diabetes (TD3)) aged 60.6±0.7 years who had a CAC assessment by Multiple Detector Computed Tomography between 2015 and 2017 were systematically included. Clinical and biological data were collected from medical electronic files.

Results

117/732 diabetic patients (16.0%) had incidental findings of which 105 (14.3%) were unknown. Incidental findings were more frequent in TD3 (23.8%) and TD2 (17.0%) than in TD1 (10.7%) (p = 0.05). 76 diabetic patients (10.4%) had lung abnormalities, mainly pulmonary nodules (31 patients, 4.2%). The other incidental finding were pericardial (1.5%), vascular (1.2%), thymic (0.7%) and digestive diseases (0.5%). 42.6% of patients with incidental findings had an additional TDM and 56.8% a specialized medical advice. In 10 patients (9.3% of incidental findings), the identification of incidental finding led to a specific treatment of the underlying disease. In multivariate analysis, microalbuminuria, type of diabetes (TD2/TD3 vs TD1) and smoking were significantly associated with incidental findings (p = 0.003; p = 0.026; p = 0.050 respectively).

Conclusions

Incidental findings are not rare in diabetic patients upon CAC assessment. A fraction of them are accessible to specific treatment. These findings raise the question if a systematic low dose chest TDM should be conducted in TD2 or TD3 patients and in any diabetic smokers by enlarging the window used for CAC assessment.

Coronary CT angiography: a guide to examination, interpretation, and clinical indications

INTRODUCTION

The introduction of Cardiac Computed Tomography (CCT) has changed the paradigm in the field of diagnostic cardiovascular medicine. CCT is the primary tool in the assessment of suspected Coronary Artery Disease (CAD) and should be followed by functional assessment when needed to stratify disease and to plan potential interventional or surgical therapy.

AREAS COVERED

We provided the current state of the knowledge on the main aspects of technique of examination, image interpretation and clinical indications. We have focused our attention on the basic routine applications and activities.

EXPERT OPINION

The primary role of CCT in suspected CAD will progressively become the standard approach. In general, any situation in which anatomy of the heart and thoracic vessels/structures is mandatory must be approached using CT first, whenever possible. The quantity and quality of information that can be provided by CCT is big and the operators should learn how to deal with this information. On the other hand, CCT is only apparently a straightforward and simple examination. It is actually the most complex diagnostic procedure that can be performed on CT and requires highly skilled operators and state-of-art-technology.

Cardiovascular Disease in Type 1 Diabetes Mellitus: Epidemiology and Management of Cardiovascular Risk

Cardiovascular disease (CVD) is a major cause of mortality in type 1 diabetes mellitus (T1DM) patients, and cardiovascular risk (CVR) remains high even in T1DM patients with good metabolic control. The underlying mechanisms remain poorly understood and known risk factors seem to operate differently in T1DM and type 2 diabetes mellitus (T2DM) patients. However, evidence of cardiovascular risk assessment and management in T1DM patients often is extrapolated from studies on T2DM patients or the general population. In this review, we examine the existing literature about the prevalence of clinical and subclinical CVD, as well as current knowledge about potential risk factors involved in the development and progression of atherosclerosis in T1DM patients. We also discuss current approaches to the stratification and therapeutic management of CVR in T1DM patients. Chronic hyperglycemia plays an important role, but it is likely that other potential factors are involved in increased atherosclerosis and CVD in T1DM patients. Evidence on the estimation of 10-year and lifetime risk of CVD, as well as the efficiency and age at which current cardiovascular medications should be initiated in young T1DM patients, is very limited and clearly insufficient to establish evidence-based therapeutic approaches to CVD management.

Society of Cardiovascular Computed Tomography / North American Society of Cardiovascular Imaging - Expert Consensus Document on Coronary CT Imaging of Atherosclerotic Plaque

Coronary computed tomographic angiography (CCTA) provides a wealth of clinically meaningful information beyond anatomic stenosis alone, including the presence or absence of nonobstructive atherosclerosis and high-risk plaque features as precursors for incident coronary events. There is, however, no uniform agreement on how to identify and quantify these features or their use in evidence-based clinical decision-making. This statement from the Society of Cardiovascular Computed Tomography and North American Society of Cardiovascular Imaging addresses this gap and provides a comprehensive review of the available evidence on imaging of coronary atherosclerosis. In this statement, we provide standardized definitions for high-risk plaque (HRP) features and distill the evidence on the effectiveness of risk stratification into usable practice points. This statement outlines how this information should be communicated to referring physicians and patients by identifying critical elements to include in a structured CCTA report - the presence and severity of atherosclerotic plaque (descriptive statements, CAD-RADS™ categories), the segment involvement score, HRP features (e.g., low attenuation plaque, positive remodeling), and the coronary artery calcium score (when performed). Rigorous documentation of atherosclerosis on CCTA provides a vital opportunity to make recommendations for preventive care and to initiate and guide an effective care strategy for at-risk patients.

Coronary CT Angiography Guided Medical Therapy in Subclinical Atherosclerosis

The goals of primary prevention in coronary atherosclerosis are to avoid sudden cardiac death, myocardial infarction or the need for revascularization procedures. Successful prevention will rely on accurate identification, effective therapy and monitoring of those at risk. Identification and potential monitoring can be achieved using cardiac computed tomography (CT). Cardiac CT can determine coronary artery calcification (CAC), a useful surrogate of coronary atherosclerosis burden. Cardiac CT can also assess coronary CT angiography (CCTA). CCTA can identify arterial lumen narrowing and highlight mural atherosclerosis hitherto hidden from other anatomical approaches. Herein we consider the role of CCTA and CAC-scoring in subclinical atherosclerosis. We explore the use of these modalities in screening and discuss data that has used CCTA for guiding primary prevention. We examine therapeutic trials using CCTA to determine the effects of plaque-modifying therapies. Finally, we address the role of CCTA and CAC to guide therapy as defined in current primary prevention documents. CCTA has emerged as an essential tool in the detection and management of clinical coronary artery disease. To date, its role in subclinical atherosclerosis is less well defined, yet with modern CT scanners and continued pharmacotherapy development, CCTA is likely to achieve a more prominent place in the primary prevention of coronary atherosclerosis.

Coronary atherosclerosis as the main endpoint of non-invasive imaging in cardiology: a narrative review

The change of paradigm determined by the introduction of cardiac computed tomography (CCT) in the field of cardiovascular medicine has allowed new evidence to emerge. These evidences point towards a major role, probably the most important one in terms of prognostic impact, in the detection, characterization and quantification of atherosclerosis as the main driver and endpoint for the management of coronary artery disease (CAD). Extensive literature has been published in the last decade with large numbers and patients' populations, investigating several aspects and correlations between atherosclerotic plaque features and risk factors; also, the relationship between plaque features, both with qualitative and quantitative approaches, and cardiovascular events has been investigated. More recent studies have also pointed out the relationship between the knowledge and classification of sub-clinical atherosclerosis and the induced modification of medical therapy (both aggressiveness and compliance) that is most likely able to increase the effect of anti-atherosclerotic drugs, hence significantly improving prognosis. Non-invasive assessment of CAD by means of CCT is becoming the primary tool for management and also the most important parameter for the comprehension of natural history of CAD and how the therapies we adopt are affecting plaque burden as a whole. In this review we will address the modern concepts of CAD driven understanding and management of cardiovascular disease.

Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis

Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA analysis can be time consuming, often requiring advanced postprocessing techniques. In consideration of the most recent ESC guidelines on CAD management, which will likely increase CCTA volume over the next years, new tools are necessary to shorten reporting time and improve the accuracy for the detection of ischemia-inducing coronary lesions. The application of artificial intelligence (AI) may provide a helpful tool in CCTA, improving the evaluation and quantification of coronary stenosis, plaque characterization, and assessment of myocardial ischemia. Furthermore, in comparison with existing risk scores, machine-learning algorithms can better predict the outcome utilizing both imaging findings and clinical parameters. Medical AI is moving from the research field to daily clinical practice, and with the increasing number of CCTA examinations, AI will be extensively utilized in cardiac imaging. This review is aimed at illustrating the state of the art in AI-based CCTA applications and future clinical scenarios.

Cost-effectiveness Analysis of Anatomic vs Functional Index Testing in Patients With Low-Risk Stable Chest Pain

IMPORTANCE

Both noninvasive anatomic and functional testing strategies are now routinely used as initial workup in patients with low-risk stable chest pain (SCP).

OBJECTIVE

To determine whether anatomic approaches (ie, coronary computed tomography angiography [CTA] and coronary CTA supplemented with noninvasive fractional flow reserve [FFRCT], performed in patients with 30% to 69% stenosis) are cost-effective compared with functional testing for the assessment of low-risk SCP.

DESIGN, SETTING, AND PARTICIPANTS

This cost-effectiveness analysis used an individual-based Markov microsimulation model for low-risk SCP. The model was developed using patient data from the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial. The model was validated by comparing model outcomes with outcomes observed in the PROMISE trial for anatomic (coronary CTA) and functional (stress testing) strategies, including diagnostic test results, referral to invasive coronary angiography (ICA), coronary revascularization, incident major adverse cardiovascular event (MACE), and costs during 60 days and 2 years. The validated model was used to determine whether anatomic approaches are cost-effective over a lifetime compared with functional testing.

EXPOSURE

Choice of index test for evaluation of low-risk SCP.

MAIN OUTCOMES AND MEASURES

Downstream ICA and coronary revascularization, MACE (death, nonfatal myocardial infarction), cost, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) of competing strategies.

RESULTS

The model cohort included 10 003 individual patients (median [interquartile range] age, 60.0 [54.4-65.9] years; 5270 [52.7%] women; 7693 [77.4%] White individuals), who entered the model 100 times. The Markov model accurately estimated the test assignment, results of anatomic and functional index testing, referral to ICA, revascularization, MACE, and costs at 60 days and 2 years compared with observed data in PROMISE (eg, coronary CTA: ICA, 12.2% [95% CI, 10.9%-13.5%] vs 12.3% [95% CI, 12.2%-12.4%]; revascularization, 6.2% [95% CI, 5.5%-6.9%] vs 6.4% [95% CI, 6.3%-6.5%]; functional strategy: ICA, 8.1% [95% CI, 7.4%-8.9%] vs 8.2% [95% CI, 8.1%-8.3%]; revascularization, 3.2% [95% CI, 2.7%-3.7%] vs 3.3% [95% CI, 3.2%-3.4%]; 2-year MACE rates: coronary CTA, 2.1% [95% CI, 1.7%-2.5%] vs 2.3% [95% CI, 2.2%-2.4%]; functional strategy, 2.2% [95% CI, 1.8%-2.6%] vs 2.4% [95% CI, 2.3%-2.4%]). Anatomic approaches led to higher ICA and revascularization rates at 60 days, 2 years, and 5 years compared with functional testing but were more effective in patient selection for ICA (eg, 60-day revascularization-to-ICA ratio, CTA: 53.7% [95% CI, 53.3%-54.0%]; CTA with FFRCT: 59.5% [95% CI, 59.2%-59.8%]; functional testing: 40.7% [95% CI, 40.4%-50.0%]). Over a lifetime, anatomic approaches gained an additional 6 months in perfect health compared with functional testing (CTA, 25.16 [95% CI, 25.14-25.19] QALYs; CTA with FFRCT, 25.14 [95% CI, 25.12-25.17] QALYs; functional testing, 24.68 [95% CI, 24.66-24.70] QALYs). Anatomic strategies were less costly and more effective; thus, CTA with FFRCT dominated and CTA alone was cost-effective (ICERs ranged from $1912/QALY for women and $3,559/QALY for men) compared with functional testing. In probabilistic sensitivity analyses, anatomic approaches were cost-effective in more than 65% of scenarios, assuming a willingness-to-pay threshold of $100 000/QALY.

CONCLUSIONS AND RELEVANCE

The results of this study suggest that anatomic strategies may present a more favorable initial diagnostic option in the evaluation of low-risk SCP compared with functional testing.

Guideline-Based Statin Eligibility, Coronary Artery Stenosis and Cardiovascular Events in Patients with Stable Chest Pain: A Secondary Analysis of the PROMISE Randomized Clinical Trial

Background: Recommendations for preventive statin treatment in patients with stable chest pain may be difficult as symptoms can be unspecific. It is unclear if coronary CT angiography (CTA)-detected coronary artery disease (CAD) can optimize statin prescription. Methods: In stable chest pain patients randomized to CTA in the PROMISE trial, statin eligibility was defined per 2018 American College of Cardiology/American Heart Association (ACC/AHA) guidelines. Primary outcome was a composite of death, myocardial infarction or unstable angina over 26 months median follow-up. Hazard ratios (HR) of non-obstructive (1–69% stenosis) and obstructive (≥70% stenosis) CAD for events were determined using Cox proportional hazard models. Calculated HR were then incorporated into the ACC/AHA pooled cohort equation (PCE) to revised ASCVD risk and assess re-classification of statin eligibility. Results: Among 3986 patients (60.5 ± 8.2 years; 51% female), 72.9% (2904/3986) were statin eligible. Event rates in statin-eligible vs. ineligible patients were 3.3% vs. 2.3% (HR = 1.4 (95% CI 0.9–2.2), p = 0.142). Although the proportion of statin-eligible patients increased with CAD severity, 54% without CAD were statin eligible. Incorporating information on CAD into PCE reclassified 12.7% of patients (1.3% towards statin, 11.4% towards no statin). Similar results were found in stratified analysis of statin naïve patients (reclassification of 13.9%, 1.0% towards statin, and 12.9% towards no statin). As a result, revised ASCVD risk improved model discrimination in all patients (c-statistic: 0.59 (95 %CI 0.55–0.62) vs. 0.52 (95 %CI 0.49–0.56); p 0.001), while reducing statin use by 10.1% (62.7% vs. 72.9% statin eligible, p 0.001). Conclusion: In stable chest pain patients, integration of CAD into guideline recommendations was associated with greater accuracy to reclassify those at increased risk for incident events and a more efficient use of statins.

Prognostic value of coronary computed tomography angiography in patients with prior percutaneous coronary intervention

OBJECTIVE

We sought to determine the prognostic value of coronary computed tomography angiography (CCTA) in patients with a history of percutaneous coronary intervention (PCI).

BACKGROUND

Although the prognostic value of CCTA has been well studied, its incremental value in patients with previous PCI has not been robustly investigated.

METHODS

Consecutive patients with previous PCI were prospectively enrolled and CCTA images were evaluated for coronary artery disease (CAD) severity. Patients were followed for major adverse cardiovascular events (MACE) which was a composite of cardiac death and non-fatal myocardial infarction. All-cause death was assessed as a secondary endpoint.

RESULTS

A total of 501 patients were analyzed with a mean follow-up time of 59.5 ± 32.0 months and 52 patients (10.4%) experienced MACE. Multivariable Cox regression analysis showed that CAD severity was a predictor of MACE with 0, 1, 2, and 3 vessel disease having annual rates of 1.3%, 2.2%, 2.2%, and 5.3%, respectively. All-cause death was similar in all categories of CAD.

CONCLUSIONS

In patients with previous PCI, CAD severity as measured with CCTA has independent and incremental prognostic value.

Artificial intelligence in cardiac radiology

Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role of AI to support cardiac radiologist in their day-to-day tasks, assisting in segmentation, quantification, and reporting tasks. In addition, AI algorithms can be also utilized to optimize image reconstruction and image quality. Since these algorithms will play an important role in the field of cardiac radiology, it is increasingly important for radiologists to be familiar with the potential applications of AI. The main focus of this article is to provide an overview of cardiac-related AI applications for CT and MRI studies, as well as non-imaging-based applications for reporting and image optimization.

Atherogenic index of plasma and the risk of advanced subclinical coronary artery disease beyond traditional risk factors: An observational cohort study

BACKGROUND

Atherogenic lipoprotein profile of plasma is an important risk factor for atherosclerosis. The atherogenic index of plasma (AIP) has been suggested as a novel marker for atherosclerosis.

HYPOTHESIS

AIP is a useful marker of advanced subclinical coronary artery disease (CAD) in subjects without overt renal dysfunction.

METHODS

A total of 6928 subjects with estimated glomerular filtration rate > 60 mL/minutes/1.73 m² evaluated by coronary computed tomography angiography (CCTA) for health check-up were included. The relation of AIP to advanced CAD (heavy coronary calcification, defined as coronary artery calcium score [CACS] >100 or obstructive coronary plaque [OCP], defined as plaque with >50% stenosis) was evaluated.

RESULTS

All participants were stratified into four groups based on AIP quartiles. The prevalence of CACS >100 (group I [lowest] 4.7% vs group II 7.0% vs group III 8.8% vs group IV 10.0%) and OCP (group I 3.7% vs group II 6.4% vs group III 8.8% vs group IV 10.9%) (all P < .001) increased with elevating AIP quartiles. Higher AIP (per 0.1 unit increase) was associated with an increased risk of CACS >100 (odds ratio [OR] 1.057, 95% confidence interval (CI) 1.010 to 1.106, P = .017; relative risk (RR) 1.048, 95% CI 1.009-1.089, and P = .015) and OCP (OR 1.079, 95% CI 1.033-1.127, P = .001; RR 1.069, 95% CI 1.031-1.108, P < .001) after adjusting for age > 60 years, male sex, hypertension, diabetes mellitus, dyslipidaemia, obesity, and proteinuria.

CONCLUSION

AIP is independently associated with advanced subclinical CAD beyond traditional risk factors.

Quantitative assessment of coronary plaque volume change related to triglyceride glucose index: The Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging (PARADIGM) registry

Background

The association between triglyceride glucose (TyG) index and coronary atherosclerotic change remains unclear. We aimed to evaluate the association between TyG index and coronary plaque progression (PP) using serial coronary computed tomography angiography (CCTA).

Methods

A total of 1143 subjects (aged 60.7 ± 9.3 years, 54.6% male) who underwent serial CCTA with available data on TyG index and diabetic status were analyzed from The Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging (PARADIGM) registry. PP was defined as plaque volume (PV) (mm³) at follow-up minus PV at index > 0. Annual change of PV (mm³/year) was defined as PV change divided by inter-scan period. Rapid PP was defined as the progression of percent atheroma volume (PV divided by vessel volume multiplied by 100) ≥ 1.0%/year.

Results

The median inter-scan period was 3.2 (range 2.6–4.4) years. All participants were stratified into three groups based on TyG index tertiles. The overall incidence of PP was 77.3%. Baseline total PV (group I [lowest]: 30.8 (0.0–117.7), group II: 47.2 (6.2–160.4), and group III [highest]: 57.5 (8.4–154.3); P < 0.001) and the annual change of total PV (group I: 5.7 (0.0–20.2), group II: 7.6 (0.5–23.5), and group III: 9.4 (1.4–27.7); P = 0.010) were different among all groups. The risk of PP (odds ratio [OR] 1.648; 95% confidence interval [CI] 1.167–2.327; P = 0.005) and rapid PP (OR 1.777; 95% CI 1.288–2.451; P < 0.001) was increased in group III compared to that in group I. TyG index had a positive and significant association with an increased risk of PP and rapid PP after adjusting for confounding factors.

Conclusion

TyG index is an independent predictive marker for the progression of coronary atherosclerosis.

Clinical registration ClinicalTrials.gov NCT02803411

Long-Term Prognostic Role of Computed Tomography Coronary Angiography for Stable Angina

Purpose of review

Chest pain is a common presentation, and there are a wide variety of ways in which it can be investigated and treated. There is growing interest in whether the way we reach a diagnosis of angina can affect the long-term prognosis. In addition to its unparalleled negative predictive value, computed tomography coronary angiography (CCTA) gives anatomical information on the extent and severity of coronary artery disease. This article discusses recent research into the ability of CCTA to predict and improve long-term prognosis for patients with stable angina.

Recent findings

Results from retrospective studies, randomised controlled trials and meta-analyses all suggest that initial investigation with computed tomography coronary angiography confers a prognostic benefit. In addition, the most recent studies have shown that the assessment of plaque burden and plaque constituents is predictive of long-term outcomes.

Summary

Management of stable chest pain should be guided by a CCTA-based approach. Future research should focus on whether incorporating plaque analysis strategies into clinical practice confers additional benefit.

Plasma lipids in patients with inflammatory bowel disease : Observations on the associations between lipid indices and coronary flow reserve

BACKGROUND AND AIMS

Patients with inflammatory bowel disease (IBD) are at increased risk for coronary artery disease (CAD), even after adjusting for traditional risk factors for atherosclerosis. While inflammation is widely regarded as the pathophysiologic link between IBD and CAD, the exact mechanisms are largely unknown. This study was conducted to investigate the association of lipid parameters and indices with coronary flow reserve and markers of inflammation in IBD patients.

METHODS

A total of 73 patients with IBD and 26 healthy controls were enrolled. Patients in the IBD arm were either in remission or had mild disease activity. Lipid parameters, C‑reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were analyzed using standard laboratory techniques. Coronary flow reserve (CFR) was measured using two-dimensional echocardiography.

RESULTS

Both CRP and ESR were higher and CFR was significantly lower in IBD patients, but there were no differences in terms of lipid parameters or indices; however, patients with IBD and a CFR <2.0 had significantly higher triglyceride (TG) level (155.0 (80.0) mg/dl vs. 108.0 (68.0) mg/dl, p < 0.001) and there was a strong trend towards lower high-density lipoprotein (HDL) cholesterol (40.0 (8.5) mg/dl vs. 45.0 (10.0) mg/dl, p = 0.05) level in the latter group when compared to patients with a CFR ≥2.0. The atherogenic index of plasma (AIP), measured as log(TG/HDL-C) had the best predictive value for CFR in IBD group and was an independent predictor of CFR after multivariate adjustment for confounders (unstandardized coefficient: -0.75, 95% CI: (-1.13)-(-0.37)), β = -0.41, p = <0.001).

CONCLUSION

The atherogenic index of plasma is a marker for reduced CFR in IBD patients and could be useful to screen those at risk for early atherogenesis and CAD.

The impact of iterative reconstruction algorithms on machine learning-based coronary CT angiography-derived fractional flow reserve (CT-FFRML) values

To evaluate the impact of an iterative reconstruction (IR) algorithm (advanced modeled iterative reconstruction, ADMIRE) on machine learning-based coronary computed tomography angiography-derived fractional flow reserve (CT-FFR_ML) measurements compared with filtered back projection (FBP). 170 plaque-containing vessels in 107 patients were included. CT-FFR_ML values were measured and compared among 5 imaging reconstruction algorithms (FBP and ADMIRE at strength levels of 1, 2, 3 and 5). The plaques were classified as, 'calcified" or "noncalcified" and "≥ 50% stenosis" or "< 50% stenosis', a total of four subgroups by consensus. There were no significant differences of CT-FFR_ML values among the FBP and ADMIRE 1, 2, 3 and 5 groups wherever comparisons were done at the level of subgroups (P = 0.676, 0.414, 0.849, 0.873, respectively) or overall (P = 0.072). There were 20, 21, 19, 19 and 29 vessels with lesion-specific ischemia (CT-FFR_ML ≤ 0.80) in FBP and ADMIRE 1, 2, 3 and 5 datasets, respectively, but no statistical differences were found (P = 0.437). Compared with CT-FFR_ML value of FBP dataset, the CT-FFR_ML values of 9 (5.3%) vessels from 8 patients (7.5%) in ADMIRE5 dataset switched from above 0.8 to below or equal to 0.8. There were no significant differences of the CT-FFR_ML values among the FBP and IR image algorithms at different strength levels. However, high iterative strength level (ADMIRE 5) was not recommended, which might have an impact on diagnosis of lesion-specific ischemia, although changes only occurred in a modest number of subjects.

Long-term health outcomes and cost-effectiveness of coronary CT angiography in patients with suspicion for acute coronary syndrome

BACKGROUND

Randomized trials have shown favorable clinical outcomes for coronary CT angiography (CTA) in patients with suspected acute coronary syndrome (ACS). Our goal was to estimate the cost-effectiveness of coronary CTA as compared to alternative management strategies for ACP patients over lifetime.

METHODS

Markov microsimulation model was developed to compare cost-effectiveness of competitive strategies for ACP patients: 1) coronary CTA, 2) standard of care (SOC), 3) AHA/ACC Guidelines, and 4) expedited emergency department (ED) discharge protocol with outpatient testing. ROMICAT-II trial was used to populate the model with low to intermediate risk of ACS patient data, whereas diagnostic test-, treatment effect-, morbidity/mortality-, quality of life- and cost data were obtained from the literature. We predicted test utilization, costs, 1-, 3-, 10-year and over lifetime cardiovascular morbidity/mortality for each strategy. We determined quality adjusted life years (QALY) and incremental cost-effectiveness ratio. Observed outcomes in ROMICAT-II were used to validate the short-term model.

RESULTS

Estimated short-term outcomes accurately reflected observed outcomes in ROMICAT-II as coronary CTA was associated with higher costs ($4,490 vs. $2,513-$4,144) and revascularization rates (5.2% vs. 2.6%-3.7%) compared to alternative strategies. Over lifetime, coronary CTA dominated SOC and ACC/AHA Guidelines and was cost-effective compared to expedited ED protocol ($49,428/QALY). This was driven by lower cardiovascular mortality (coronary CTA vs. expedited discharge: 3-year: 1.04% vs. 1.10-1.17; 10-year: 5.06% vs. 5.21-5.36%; respectively).

CONCLUSION

Coronary CTA in patients with suspected ACS renders affordable long-term health benefits as compared to alternative strategies.

Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA

BACKGROUND AND AIMS

Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary computed tomography angiography (CCTA) in the correct Coronary Artery Disease Reporting and Data System (CAD-RADS) category.

METHODS

Two hundred eighty eight patients who underwent clinically indicated CCTA were included in this single-center retrospective study. The CCTAs were stratified by CAD-RADS scores by expert readers and considered as reference standard. A deep CNN was designed and tested on the CCTA dataset and compared to on-site reading. The deep CNN analyzed the diagnostic accuracy of the following three Models based on CAD-RADS classification: Model A (CAD-RADS 0 vs CAD-RADS 1-2 vs CAD-RADS 3,4,5), Model 1 (CAD-RADS 0 vs CAD-RADS>0), Model 2 (CAD-RADS 0-2 vs CAD-RADS 3-5). Time of analysis for both physicians and CNN were recorded.

RESULTS

Model A showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 47%, 74%, 77%, 46% and 60%, respectively. Model 1 showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 66%, 91%, 92%, 63%, 86%, respectively. Conversely, Model 2 demonstrated the following sensitivity, specificity, negative predictive value, positive predictive value and accuracy: 82%, 58%, 74%, 69%, 71%, respectively. Time of analysis was significantly lower using CNN as compared to on-site reading (530.5 ± 179.1 vs 104.3 ± 1.4 sec, p=0.01) CONCLUSIONS: Deep CNN yielded accurate automated classification of patients with CAD-RADS.

High HDL-C levels reduce the risk of obstructive coronary artery disease in asymptomatic diabetics who achieved optimal glycemic control

The benefit of a high level of high-density lipoprotein cholesterol (HDL-C) against coronary atherosclerosis risk after achieving optimal glycemic control (OGC) in diabetics remains uncertain. We aimed to evaluate the association between HDL-C and obstructive coronary artery disease (CAD) according to OGC status in diabetics. We analyzed 1,114 asymptomatic diabetics who underwent coronary computed tomographic angiography in a health examination. OGC was defined as hemoglobin A1C <7.0%. Obstructive CAD was defined as the presence of plaques with ≥50% stenosis. Patients with a high HDL-C level (≥40 mg/dL and ≥50 mg/dL in males and females, respectively) showed a lower prevalence of obstructive CAD than those with a low HDL-C level in the OGC group (8.9% vs. 14.4%; p = 0.046), but not in the non-OGC group (22.3% vs. 23.2%, p = 0.850). Multiple logistic regression models showed that the risk for obstructive CAD was lower in patients with a high HDL-C level than in those with a low HDL-C level in the OGC group (odds ratio: 0.584, 95% confidence interval: 0.343-0.995; p = 0.048), but not in the non-OGC group. In conclusion, it may be necessary to maintain a high HDL-C level to reduce the risk of obstructive CAD in asymptomatic diabetics after OGC is achieved.

Use of High-Risk Coronary Atherosclerotic Plaque Detection for Risk Stratification of Patients With Stable Chest Pain: A Secondary Analysis of the PROMISE Randomized Clinical Trial

Importance

Coronary computed tomographic angiography (coronary CTA) can characterize coronary artery disease, including high-risk plaque. A noninvasive method of identifying high-risk plaque before major adverse cardiovascular events (MACE) could provide practice-changing optimizations in coronary artery disease care.

Objective

To determine whether high-risk plaque detected by coronary CTA was associated with incident MACE independently of significant stenosis (SS) and cardiovascular risk factors.

Design, Setting, and Participants

This prespecified nested observational cohort study was part of the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial. All stable, symptomatic outpatients in this trial who required noninvasive cardiovascular testing and received coronary CTA were included and followed up for a median of 25 months.

Exposures

Core laboratory assessment of coronary CTA for SS and high-risk plaque (eg, positive remodeling, low computed tomographic attenuation, or napkin-ring sign).

Main Outcomes and Measures

The primary end point was an adjudicated composite of MACE (defined as death, myocardial infarction, or unstable angina).

Results

The study included 4415 patients, of whom 2296 (52%) were women, with a mean age of 60.5 years, a median atherosclerotic cardiovascular disease (ASCVD) risk score of 11, and a MACE rate of 3% (131 events). A total of 676 patients (15.3%) had high-risk plaques, and 276 (6.3%) had SS. The presence of high-risk plaque was associated with a higher MACE rate (6.4% vs 2.4%; hazard ratio, 2.73; 95% CI, 1.89-3.93). This association persisted after adjustment for ASCVD risk score and SS (adjusted hazard ratio [aHR], 1.72; 95% CI, 1.13-2.62). Adding high-risk plaque to the ASCVD risk score and SS assessment led to a significant continuous net reclassification improvement (0.34; 95% CI, 0.02-0.51). Presence of high-risk plaque increased MACE risk among patients with nonobstructive coronary artery disease relative to patients without high-risk plaque (aHR, 4.31 vs 2.64; 95% CI, 2.25-8.26 vs 1.49-4.69). There were no significant differences in MACE in patients with SS and high-risk plaque as opposed to those with SS but not high-risk plaque (aHR, 8.68 vs. 9.31; 95% CI, 4.25-17.73 vs 4.21-20.61). High-risk plaque was a stronger predictor of MACE in women (aHR, 2.41; 95% CI, 1.25-4.64) vs men (aHR, 1.40; 95% CI, 0.81-2.39) and younger patients (aHR, 2.33; 95% CI, 1.20-4.51) vs older ones (aHR, 1.36; 95% CI, 0.77-2.39).

Conclusions and Relevance

High-risk plaque found by coronary CTA was associated with a future MACE in a large US population of outpatients with stable chest pain. High-risk plaque may be an additional risk stratification tool, especially in patients with nonobstructive coronary artery disease, younger patients, and women. The importance of findings is limited by low absolute MACE rates and low positive predictive value of high-risk plaque.

Trial Registration

clinicaltrials.gov Indentifier: NCT01174550.

Association between insulin resistance, hyperglycemia, and coronary artery disease according to the presence of diabetes

This study evaluated the relationship of insulin resistance (IR) and glycemic control status to the presence and severity of coronary artery disease (CAD) according to diabetes. The relationship of IR parameters including homeostatic model assessment of IR (HOMA-IR), triglyceride-glucose (TyG) index, and triglyceride-to-high density lipoprotein cholesterol ratio (TG/HDL), and hemoglobin A1C (HbA1C) level to CAD and obstructive CAD was evaluated in 5,764 asymptomatic subjects who underwent coronary computed tomographic angiography. Non-diabetics (n = 4768) and diabetics (n = 996) were stratified into four groups based on the quartiles of HOMA-IR and the TyG index and were grouped based on the TG/HDL cut-offs of 3.5, respectively. CAD and obstructive CAD were defined as the presence of any plaques and plaques with ≥50% stenosis, respectively. The prevalence of CAD (59.0% vs. 39.0%) and obstructive CAD (15.0% vs. 6.6%) was higher in diabetic than in non-diabetic patients (p < 0.001, respectively). In non-diabetic patients, the adjusted odds ratio for both CAD and obstructive CAD significantly increased, but only with higher TyG index quartiles. Unlike non-diabetics, the adjusted odds ratio for obstructive CAD significantly increased in diabetic patients with a TG/HDL level ≥ 3.5. The HbA1C, rather than IR parameters, was independently associated with both CAD and obstructive CAD in diabetics. In conclusion, among IR parameters, TyG index was independently associated with the presence of CAD and obstructive CAD in non-diabetic patients. In contrast, the glycemic control status, rather than IR, was importantly related to both CAD and obstructive CAD in established diabetic patients.

Integration of CTA in the Diagnostic Workup of New Onset Chest Pain in Clinical Practice

Background

Recently, NICE guidelines recommend the use of computed tomographic angiography (CTA) as the first line of investigation for new onset chest pain. We sought to evaluate the impact of the integration of CTA in the diagnostic workup, as either a first- or second-line of investigation, in the clinical practice for patients presenting with new onset chest pain, with suspicion that it may be due to coronary artery disease (CAD).

Method and Results

From 2014 to 2016, 208 outpatients (mean age 63.8 ± 12.7, 37% female) with an unknown CAD diagnosis were evaluated. About half (n=106, 51%) received usual testing care plus CTA as a second-line investigation (group A), while the other half (n=102, 49%) received CTA as a first-line investigation (group B). Care decisions and test interpretations were made by the attending physician. Obstructive CAD (O-CAD) was defined as >50% stenosis in the principal branch. As determined by CTA, the rates of CAD in group A vs. group B were the following (P=0.001): 31.1% vs. 27.4% for normal/minimal CAD; 42.5% vs. 63.7% for no O-CAD; and 26.4% vs. 8.8% with O-CAD. Based on a diagnostic result of no O-CAD, invasive angiography was cancelled in 42.6% (n=45) of group A patients, and additional functional tests were cancelled for the same reason in 63.7% (n=65) of group B patients, without adverse events at median 3-year. The average diagnostic cost for patients in our study was lower in group B (206 vs. 324.42 euro; P<0.0001).

Conclusions

In clinical practice, CTA, as a first- or second-line investigation, most commonly detected no O-CAD in new onset chest pain patients, leading us to safely avoid unnecessary ICA or additional functional tests. The use of CTA as a first-line investigation also appears to be cost saving, but its cost-effectiveness remains to be demonstrated in larger studies.

High-density lipoprotein cholesterol and the risk of obstructive coronary artery disease beyond low-density lipoprotein cholesterol in non-diabetic individuals

AIMS

The relationship between high-density lipoprotein cholesterol and the severity of coronary artery disease beyond low-density lipoprotein cholesterol, the primary target of cholesterol-lowering therapy, remains uncertain. We evaluated the association between high-density lipoprotein cholesterol and obstructive coronary artery disease using parameters of any obstructive plaque, obstructive plaque in the left main coronary artery or proximal left anterior descending artery, and obstructive plaque in multi-vessels, according to low-density lipoprotein cholesterol levels.

METHODS AND RESULTS

We analyzed 5130 asymptomatic non-diabetics who underwent coronary computed tomography angiography for general health examination. Obstructive plaque was defined as a plaque with ≥50% luminal diameter stenosis. The participants were divided into three groups based on low-density lipoprotein cholesterol levels of ≤129, 130-159, and ≥160 mg/dl. The prevalence of any obstructive plaque (5.9% vs 6.4% vs 10.6%) and obstructive plaque in the left main coronary artery or proximal left anterior descending artery (2.1% vs 2.1% vs 4.3%) significantly increased with low-density lipoprotein cholesterol category (all p < 0.05). Compared with subjects with high-density lipoprotein cholesterol level ≥40 mg/dl, those with high-density lipoprotein cholesterol level <40 mg/dl had a significantly higher prevalence of any obstructive plaque (10.4% vs 5.1%), obstructive plaque in the left main coronary artery or proximal left anterior descending artery (3.6% vs 1.8%), and obstructive plaque in multi-vessels (4.3% vs 1.1%), only in the group with low-density lipoprotein cholesterol level ≤129 mg/dl (all p < 0.05). Multiple regression analysis showed that increased high-density lipoprotein cholesterol levels were associated with a reduced risk of all obstructive coronary artery disease parameters only in the group with low-density lipoprotein cholesterol level ≤129 mg/dl (all p < 0.05).

CONCLUSION

Increased high-density lipoprotein cholesterol levels were independently associated with a lower risk of obstructive coronary artery disease in asymptomatic non-diabetics with low low-density lipoprotein cholesterol levels.