Long-term prognostic impact of CT-Leaman score in patients with non-obstructive CAD: Results from the COronary CT Angiography EvaluatioN For Clinical Outcomes InteRnational Multicenter (CONFIRM) study

Type 2 diabetes mellitus aggravates coronary atherosclerosis in hypertensive individuals based on coronary CT angiography: a retrospective propensity score-based study

Background

The effect of type 2 diabetes mellitus (T2DM) on coronary atherosclerosis detected on coronary computed tomography angiography (CCTA) in hypertensive patients has attracted increasing attention. This study investigated the relationships of T2DM with coronary artery plaque characteristics and semiquantitative CCTA scores in hypertensive patients.

Materials and methods

In this single-center study, 1,700 hypertensive patients, including 850 T2DM [HT(T2DM+)] and 850 non-T2DM [HT(T2DM-)] individuals, were retrospectively analyzed after propensity matching. Plaque type, extent, coronary stenosis, segment involvement score (SIS), segment stenosis score (SSS), and CT-based Leaman score (CT-LeSc) based on CCTA were assessed and compared between the two groups.

Results

HT(T2DM+) patients had more coronary segments with calcified plaque (2.08 ± 2.20 vs. 1.40 ± 1.91), mixed plaque (2.90 ± 2.87 vs. 2.50 ± 2.66), nonobstructive stenosis (4.23 ± 2.44 vs. 3.62 ± 2.42), and obstructive stenosis (1.22 ± 2.18 vs. 0.78 ± 1.51), a lower proportion of 1-vessel disease (15.3% vs. 25.5%), a higher proportion of 3-vessel disease (59.6% vs. 46.7%), and higher SIS (5.5 ± 3.1 vs. 4.4 ± 3.0), SSS (10.3 ± 8.5 vs. 7.7 ± 7.1), and CT-LeSc (9.4 ± 5.6 vs. 7.9 ± 5.2) than HT(T2DM-) patients (all P-values <0.05). Multivariable analysis revealed that T2DM was an independent risk factor for calcified plaque [odds ratio (OR) = 2.213], obstructive coronary artery disease (CAD) (OR = 1.271), multivessel disease (OR = 1.838), SIS > 4 (OR = 1.910), SSS > 6 (OR = 1.718), and CT-LeSc > 5 (OR = 1.584) in hypertension population (all P-values <0.05).

Conclusion

T2DM was independently associated with the presence of calcified coronary artery plaque and increased the risk of obstructive CAD, multivessel disease, and CT-LeSc > 5 in hypertensive patients. More attention should be given to the assessment and management for coronary atherosclerosis in hypertensive patients with T2DM, as this population may have a higher risk of cardiovascular events.

Stenosis Detection and Quantification of Coronary Artery Using Machine Learning and Deep Learning

The aim of this review is to introduce some applications of artificial intelligence (AI) algorithms for the detection and quantification of coronary stenosis using computed tomography angiography (CTA). The realization of automatic/semi-automatic stenosis detection and quantification includes the following steps: vessel central axis extraction, vessel segmentation, stenosis detection, and quantification. Many new AI techniques, such as machine learning and deep learning, have been widely used in medical image segmentation and stenosis detection. This review also summarizes the recent progress regarding coronary stenosis detection and quantification, and discusses the development trends in this field. Through evaluation and comparison, researchers can better understand the research frontier in related fields, compare the advantages and disadvantages of various methods, and better optimize the new technologies. Machine learning and deep learning will promote the process of automatic detection and quantification of coronary artery stenosis. However, the machine learning and the deep learning methods need a large amount of data, so they also face some challenges because of the lack of professional image annotations (manually add labels by experts).

Clinical and cardiac CT characteristics of congenital coronary abnormalities occasionally detected in a middle-aged population: A long-term follow-up study

INTRODUCTION

Congenital coronary artery anomalies (CCAA) represent one of the most challenging conditions as their clinical presentation may range from sudden cardiac death to a complete subclinical form. The aim of the present study was to evaluate the diagnostic and prognostic role of cardiac CT (CCT) evaluation in patients with CCAA, focusing on anomalies of origin.

MATERIAL AND METHODS

The present is a retrospective analysis of a prospective clinical registry including a consecutive cohort of patients who underwent clinically indicated CCT from January 2007 to October 2015 for suspected but unknown coronary artery disease (CAD) and were diagnosed for having a congenital coronary abnormality compared to a control group matched for age, sex and segment stenosis score (SSS). Dedicated analysis of all CCT was performed for the present study and only coronary anomalies of origin were considered and included in the study. Two different composite end-points were identified for the present analysis: major cardiovascular events (MACE) and all-cause of death.

RESULTS

Among the 81 patients with CCAAs enrolled the most frequent anomaly was left main artery absence, which was identified in 41 individuals (50.6%). Forty-five subjects (55.5%) have an anomalous origin of the coronary artery from a different sinus of Valsalva and 45 subjects had also an anomalous course with the retro-aortic being the most common (32%). Eleven participants (13.6%) displayed also an intramural segment, while 10 (10.3%) had a slit-like ostial morphology. At multivariate analysis CT identification of ARCA, anomalous inter-arterial course and abnormal ostial morphology were significantly associated with MACE even when adjusted for age and SSS, without any differences in all-cause mortality between the two groups (6.2% vs 2.4% p ​= ​0.2478).

CONCLUSION

The result of the present study is that CCT can be successfully used to define the anatomy and features of CAA. It suggested that in middle-aged patients, the identification of high risk characteristics at CT may have a prognostic value in term of cardiovascular events occurrence at follow-up even if the rate of events strictly linked to CCAA is low.

Inter- and intra-observer reproducibility of CT-Leaman score by an independent core lab

To assess the reproducibility of CT-based Leaman score (CT-LeSc). CT-LeSc can non-invasively quantify total coronary atherosclerotic burden and is an independent long-term predictor of cardiac events. Its calculation however relies on the subjective assessment of lesions using coronary computed tomography angiography and therefore is subject to intra- and inter-observer variability. Inter-observer reproducibility was assessed by calculating the CT-LeSc in 50 patients randomly selected from the SYNTAX III REVOLUTION and ABSORB trials by two separate teams, each made up of two cardiologists, who reported results by consensus. For intra-observer reproducibility, the CT-LeSc was calculated in same 50 patients on two occasions eight weeks apart, by the same team of two cardiologists. The level of agreement was measured by the weighted kappa statistic, with intra- and inter-observer variability used to evaluate the CT-LeSc's reproducibility. The variables evaluated by weighted kappa statistics were total number of lesions; number of calcified lesions; number of non-calcified lesions; number of mixed lesions; number of obstructive lesions; number of non-obstructive lesions; and the total CT-LeSc in increments of ten and five. During assessment of inter-observer variability the mean ± standard deviation (SD) CT-LeSc calculated by the first and second team was 15.36 ± 5.57 versus 15.24 ± 5.16. The mean of the differences (precision) was 0.97, with a SD (accuracy) 1.17. The inter-observer variability was lowest for Leaman score in increments of five (weighted kappa 0.93), and highest for the total number of calcified lesions (weighted kappa 0.66). During assessment of intra-observer variability, the mean ± SD CT-LeSc were 16.61 ± 5.28 versus 16.82 ± 5.55. The mean ± SD of the differences was 1.28 ± 1.02. The intra-observer variability was the lowest for Leaman score in increments of five (weighted kappa 0.93), and the highest for the total number of lesions and calcified lesions (weighted kappa 0.65). CT-LeSc has substantial to near-perfect agreement for reproducibility.

Management strategies for heavily calcified coronary stenoses: an EAPCI clinical consensus statement in collaboration with the EURO4C-PCR group

Since the publication of the 2015 EAPCI consensus on rotational atherectomy, the number of percutaneous coronary interventions (PCI) performed in patients with severely calcified coronary artery disease has grown substantially. This has been prompted on one side by the clinical demand for the continuous increase in life expectancy, the sustained expansion of the primary PCI networks worldwide, and the routine performance of revascularization procedures in elderly patients; on the other side, the availability of new and dedicated technologies such as orbital atherectomy and intravascular lithotripsy, as well as the optimization of the rotational atherectomy system, has increased operators' confidence in attempting more challenging PCI. This current EAPCI clinical consensus statement prepared in collaboration with the EURO4C-PCR group describes the comprehensive management of patients with heavily calcified coronary stenoses, starting with how to use non-invasive and invasive imaging to assess calcium burden and inform procedural planning. Objective and practical guidance is provided on the selection of the optimal interventional tool and technique based on the specific calcium morphology and anatomic location. Finally, the specific clinical implications of treating these patients are considered, including the prevention and management of complications and the importance of adequate training and education.

Prognostic value of coronary CT angiography for the prediction of all-cause mortality and non-fatal myocardial infarction: a propensity score analysis

To explore the relationship between comprehensive assessment of coronary atherosclerosis by coronary CT angiography (CCTA) and all-cause mortality and non-fatal myocardial infarction in the Chinese population. Sixty-three patients from the prospective long-term study who experienced major adverse cardiovascular events (MACE) during the follow-up were included. No-MACE patients were 1:1 propensity-matched. Various qualitative and quantitative CCTA parameters, such as coronary artery calcium score (CACS), high-risk plaque, coronary artery disease (CAD) severity, number of obstructive vessels, segment involvement score (SIS), segment stenosis score (SSS), computed tomography-adapt Leaman score (CT-LeSc), and peri-coronary adipose tissue (PCAT) CT attenuation, were compared between both groups. Cox regression analysis was performed to determine the association between CCTA parameters and MACE. The MACE group had higher CACS, more high-risk plaques, more obstructive CAD, more obstructive vessels, higher PCAT CT attenuation, and higher coronary atherosclerotic burden (SIS: 5.76 ± 3.36 vs. 2.84 ± 3.07; SSS: 11.06 ± 8.41 vs. 3.94 ± 4.78; CT-LeSc: 11.25 ± 6.57 vs. 5.49 ± 5.82) than the control group (all p < 0.05). On multivariable analysis, hazard ratios were 1.058 for the SSS (p = 0.004), and 2.152 for the obstructive CAD. When the burden of coronary atherosclerosis was defined as the CT-LeSc, hazard ratios were 1.057 for the CT-LeSc (p = 0.036), and 2.272 for the obstructive CAD. The SSS, CT-LeSc, and presence of obstructive CAD were independently associated with the all-cause mortality and non-fatal myocardial infarction in the suspected CADs in the Chinese population.

Prognostic value of Toll-like receptor 4 on human monocyte subsets combined with computed tomography-adapted Leaman score assessing coronary artery disease

BACKGROUND

Upregulation of Toll-like receptor 4 (TLR-4) is associated with coronary plaque vulnerability assessed by coronary computed tomography angiography (CCTA). Computed tomography-adapted Leaman score (CT-LeSc) is an independent long-term predictor of cardiac events. The relationship between the TLR-4 expression of CD14 ++ CD16 + monocytes and future cardiac events is unknown. We investigated this relationship using CT-LeSc in patients with coronary artery disease (CAD).

METHODS

We analyzed 61 patients with CAD who underwent CCTA. Three monocyte subsets (CD14 ++ CD16 - , CD14 ++ CD16 + , and CD14 + CD16 + ) and the expression of TLR-4 were measured by flow cytometry. We divided the patients into two groups according to the best cutoff value of the TLR-4 expression on CD14 + CD16 + which could predict future cardiac events.

RESULTS

CT-LeSc was significantly greater in the high TLR-4 group than the low TLR-4 group [9.61 (6.70-13.67) vs. 6.34 (4.27-9.09), P  < 0.01]. The expression of TLR-4 on CD14 ++ CD16 + monocytes was significantly correlated with CT-LeSc ( R2  = 0.13, P  < 0.01). The expression of TLR-4 on CD14 ++ CD16 + monocytes was significantly higher in patients who had future cardiac events than in those who did not [6.8 (4.5-9.1) % vs. 4.2 (2.4-7.6) %, P  = 0.04]. High TLR-4 expression on CD14 ++ CD16 + monocytes was an independent predictor for future cardiac events ( P  = 0.01).

CONCLUSION

An increase in the TLR-4 expression on CD14 ++ CD16 + monocytes is related to the development of future cardiac events.

Prediction of outcome by 82Rb PET/CT in patients with ischemia and nonobstructive coronary arteries

BACKGROUND

The purpose of this study was to assess the prognostic value of cardiac 82Rb positron emission tomography (PET)/computed tomography (CT) imaging in patients with myocardial ischemia of nonobstructive coronary arteries (INOCA).

METHODS

We retrospectively evaluated 311 INOCA patients who underwent rest stress 82Rb PET/CT. Cardiac end points were cardiac death, myocardial infarction, or late coronary revascularization. A parametric survival model was also used to identify how the variables influenced time to event.

RESULTS

During a median follow-up of 37 months (range 6-108), 23 (7%) cardiac events occurred. In patients with events total perfusion defect (TPD) was higher and myocardial flow reserve (MFR) lower compared to those without events (both P < .001). At multivariable Cox analysis, increased TPD (i.e., ≥ 5%) and reduced MFR (i.e., < 2) were predictors of events (both P < .001). At Weibull survival analysis, the highest probability of cardiac events and risk acceleration were observed in patients with both increased TPD and reduced MFR. Annualized event rate was higher in patients with reduced MFR compared to those with preserved MFR (P < .001).

CONCLUSION

In patients with INOCA, the combined evaluation of myocardial perfusion and coronary vascular function by 82Rb PET/CT is able to identify those at higher risk of cardiac events.

Coronary Computed Tomography Angiography: Beyond Obstructive Coronary Artery Disease

Nowadays, coronary computed tomography angiography (CCTA) has a role of paramount importance in the diagnostic algorithm of ischemic heart disease (IHD), both in stable coronary artery disease (CAD) and acute chest pain. Alongside the quantification of obstructive coronary artery disease, the recent technologic developments in CCTA provide additional relevant information that can be considered as "novel markers" for risk stratification in different settings, including ischemic heart disease, atrial fibrillation, and myocardial inflammation. These markers include: (i) epicardial adipose tissue (EAT), associated with plaque development and the occurrence of arrhythmias; (ii) late iodine enhancement (LIE), which allows the identification of myocardial fibrosis; and (iii) plaque characterization, which provides data about plaque vulnerability. In the precision medicine era, these emerging markers should be integrated into CCTA evaluation to allow for the bespoke interventional and pharmacological management of each patient.

Computed tomographic angiography in coronary artery disease

Coronary computed tomographic angiography (CCTA) is becoming the first-line investigation for establishing the presence of coronary artery disease and, with fractional flow reserve (FFRCT), its haemodynamic significance. In patients without significant epicardial obstruction, its role is either to rule out atherosclerosis or to detect subclinical plaque that should be monitored for plaque progression/regression following prevention therapy and provide risk classification. Ischaemic non-obstructive coronary arteries are also expected to be assessed by non-invasive imaging, including CCTA. In patients with significant epicardial obstruction, CCTA can assist in planning revascularisation by determining the disease complexity, vessel size, lesion length and tissue composition of the atherosclerotic plaque, as well as the best fluoroscopic viewing angle; it may also help in selecting adjunctive percutaneous devices (e.g., rotational atherectomy) and in determining the best landing zone for stents or bypass grafts.

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.

Imaging subclinical coronary atherosclerosis to guide lipid management, are we there yet?

Atherosclerotic cardiovascular disease risk (ASCVD) is an ongoing epidemic, and lipid abnormalities are its primordial cause. Most individuals suffering a first ASCVD event are previously asymptomatic and often do not receive preventative therapies. The cornerstone of primary prevention has been the identification of individuals at risk through risk calculators based on clinical and laboratory traditional risk factors plus risk enhancers. However, it is well accepted that a clinical risk calculator misclassifies a significant proportion of individuals leading to the prescription of a lipid-lowering medication with very little yield or a missed opportunity for lipid-lowering agents with a potentially preventable event. The development of coronary artery calcium scoring (CAC) and CT coronary angiography (CCTA) provide complementary tools to directly visualize coronary plaque and other risk-modifying imaging components that can potentially provide individualized lipid management. Understanding patient selection for CAC or potentially CCTA and the risk implications of the different parameters provided, such as CAC score, coronary stenosis, plaque characteristics and burden, epicardial adipose tissue, and pericoronary adipose tissue, have grown more complex as technologies evolve. These parameters directly affect the shared decision with patients to start or withhold lipid-lowering therapies, to adjust statin intensity or LDL cholesterol goals. Emerging lipid lowering studies with non-invasive imaging as a guide to patient selection and treatment efficacy, plus the evolution of lipid lowering therapies from statins to a diverse armament of newer high-cost agents have pushed these two fields forward with a complex interaction. This review will discuss existing risk estimators, and non-invasive imaging techniques for subclinical coronary atherosclerosis, traditionally studied using CAC and more recently CCTA with qualitative and quantitative measurements. We will also explore the current data, gaps of knowledge and future directions on the use of these techniques in the risk-stratification and guidance of lipid management.

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.

Plaque assessment by coronary CT angiography may predict cardiac events in high risk and very high risk diabetic patients: A long-term follow-up study

BACKGROUND AND AIMS

The aim of the present study is to evaluate whether advanced coronary atherosclerosis analysis by CCTA may improve prognostic stratification among diabetic patients at high cardiovascular risk (CV risk).

METHODS AND RESULTS

The study population consisted of 265 consecutive diabetic patients at high CV risk who underwent CCTA for suspected CAD between January 2011 and December 2016. For every patients both traditional and advanced, qualitative and quantitative coronary plaque analysis were performed. The occurrence of cardiac death, ACS, and non-urgent revascularization were recorded at follow-up. Among the 265 patients enrolled, 21 were lost to follow-up, whereas 244 (92%) had a complete follow-up (mean 45 ± 22 months) and were classified at high (n = 67) or very high cardiovascular risk (n = 177), according to ESC Guidelines. A total of 63 events were recorded (3 Cardiac Death, 3 NSTEMI, 8 unstable angina, 36 late non-urgent revascularization and 13 non-cardiac death) in 57 different patients. Elevated fibro-fatty plaque volume was the only predictor of events over age, gender and traditional risk factor when ACS and MACE were considered as end-points [HR (95% CI) 6.01 (1.65-21.87), p = 0.006 and 3.46 (2.00-5.97); p < 0.001].

CONCLUSION

The present study confirms the prognostic role of advance coronary atherosclerosis evaluation beyond risk factors and stenosis severity, even in diabetics. Despite the very high cardiovascular risk of study population, a not negligible portion (23%) of patients exhibited totally normal coronaries.

Quantitative assessment of atherosclerotic plaque, recent progress and current limitations

An important advantage of computed tomography coronary angiography (CCTA) is its ability to visualize the presence and severity of atherosclerotic plaque, rather than just assessing coronary artery stenoses. Until recently, assessment of plaque subtypes on CCTA relied on visual assessment of the extent of calcified/non-calcified plaque, or visually identifying high-risk plaque characteristics. Recent software developments facilitate the quantitative assessment of plaque volume or burden on CCTA, and the identification of subtypes of plaque based on their attenuation density. These techniques have shown promise in single and multicenter studies, demonstrating that the amount and type of plaque are associated with subsequent cardiac events. However, there are a number of limitations to the application of these techniques, including the limitations imposed by the spatial resolution of current CT scanners, challenges from variations between reconstruction algorithms, and the additional time to perform these assessments. At present, these are a valuable research technique, but not yet part of routine clinical practice. Future advances that improve CT resolution, standardize acquisition techniques and reconstruction algorithms and automate image analysis will improve the clinical utility of these techniques. This review will discuss the technical aspects of quantitative plaque analysis and present pro and con arguments for the routine use of quantitative plaque analysis on CCTA.

Innovative Approaches to Assess Intermediate Cardiovascular Risk Subjects: A Review From Clinical to Metabolomics Strategies

Current risk stratification strategies for coronary artery disease (CAD) have low predictive value in asymptomatic subjects classified as intermediate cardiovascular risk. This is relevant because not all coronary events occur in individuals with traditional multiple risk factors. Most importantly, the first manifestation of the disease may be either sudden cardiac death or acute coronary syndrome, after rupture and thrombosis of an unstable non-obstructive atherosclerotic plaque, which was previously silent. The inaccurate stratification using the current models may ultimately subject the individual to excessive or insufficient preventive therapies. A breakthrough in the comprehension of the molecular mechanisms governing the atherosclerosis pathology has driven many researches toward the necessity for a better risk stratification. In this Review, we discuss how metabolomics screening integrated with traditional risk assessments becomes a powerful approach to improve non-invasive CAD subclinical diagnostics. In addition, this Review highlights the findings of metabolomics studies performed by two relevant analytical platforms in current use-mass spectrometry (MS) hyphenated to separation techniques and nuclear magnetic resonance spectroscopy (NMR) -and evaluates critically the challenges for further clinical implementation of metabolomics data. We also discuss the modern understanding of the pathophysiology of atherosclerosis and the limitations of traditional analytical methods. Our aim is to show how discriminant metabolites originated from metabolomics approaches may become promising candidate molecules to aid intermediate risk patient stratification for cardiovascular events and how these tools could successfully meet the demands to translate cardiovascular metabolic biomarkers into clinical settings.

Coronary plaque features on CTA can identify patients at increased risk of cardiovascular events

PURPOSE OF REVIEW

Multicenter studies showed that the characterization of coronary atherosclerosis by coronary computed tomography (CT) angiography (CCTA) provides independent and incremental prognostic value above and beyond traditional measures of coronary artery disease (CAD) and is able to identify patients at risk of future event. Aim of the present review is to expound the major imaging plaque features associated with increased risk of coronary event and to review the data supporting the usefulness of CCTA as tool for plaque assessment and for monitoring the changes in atherosclerotic burden.

RECENT FINDINGS

The evaluation of coronary atherosclerosis, including the measurement of imaging risk scores (e.g. CT-adapted Leaman score) was demonstrated as independent long-term predictor of acute coronary events. In particular, qualitative (remodelling index, low-attenuation plaque, napkin-ring sign, small spotty calcifications) and quantitative (plaque burden, total-, noncalcific- and fibrofatty plaque volume) plaque features were associated with increased risk. CCTA was also demonstrated to accurately quantify plaque volume vs. intravascular ultrasound and findings from PARADIGM and EVAPORATE studies supported the use of CCTA as noninvasive tool to follow the effect of medication on plaque progression/regression. Finally, interesting relationship between plaque features, coronary physiology and biomarkers have been described.

SUMMARY

Latest guidelines on the management of patients with stable CAD recommended CCTA in Class I of evidence, particularly when 'information on atherosclerosis are desired', underlining the usefulness of CCTA to characterize and quantify the atherosclerotic burden.

Clinical Relevance of Coronary Computed Tomography Angiography Beyond Coronary Artery Stenosis

BACKGROUND

 The capabilities of coronary computed tomography angiography (CCTA) have advanced significantly in the past decade. Its capacity to detect stenotic coronary arteries safely and consistently has led to a marked decline in invasive diagnostic angiography. However, CCTA can do much more than identify coronary artery stenoses.

METHOD

 This review discusses applications of CCTA beyond coronary stenosis assessment, focusing in particular on the visual and quantitative analysis of atherosclerotic plaque.

RESULTS

 Established signs of visually assessed high-risk plaque on CT include positive remodeling, low-attenuation plaque, spotty calcification, and the napkin-ring sign, which correlate with the histological thin-cap fibroatheroma. Recently, quantification of plaque subtypes has further improved the assessment of coronary plaque on CT. Quantitatively assessed low-attenuation plaque, which correlates with the necrotic core of the thin-cap fibroatheroma, has demonstrated superiority over stenosis severity and coronary calcium score in predicting subsequent myocardial infarction. Current research aims to use radiomic and machine learning methods to further improve our understanding of high-risk atherosclerotic plaque subtypes identified on CCTA.

CONCLUSION

 Despite rapid technological advances in the field of coronary computed tomography angiography, there remains a significant lag in routine clinical practice where use is often limited to lumenography. We summarize some of the most promising techniques that significantly improve the diagnostic and prognostic potential of CCTA.

KEY POINTS

  · In addition to its ability to determine severity of luminal stenoses, CCTA provides important prognostic information by evaluating atherosclerotic plaque.. · Simple scoring systems such as the segment involved score or the CT-adapted Leaman score can provide more prognostic information on major adverse coronary events compared to traditional risk factors such as presence of hypertension or diabetes.. · CT signs of high-risk plaque, including positive remodeling, low-attenuation plaque, spotty calcification, and the napkin-ring sign, are significantly more likely to predict acute coronary syndromes.. · Quantitative plaque assessment can provide precise description of volume and burden of plaque subtypes and have been found to predict subsequent myocardial infarction better than cardiovascular risk scores, calcium scoring and severity of coronary artery stenoses.. · Machine learning techniques have the potential to automate risk stratification and enhance health economy, even though present clinical applications are limited. In this era of "big data" they are an exciting avenue for future research..

CITATION FORMAT

· Meah MN, Williams MC. Clinical Relevance of Coronary Computed Tomography Angiography Beyond Coronary Artery Stenosis. Fortschr Röntgenstr 2021; 193: 1162 - 1170.

Gamma-glutamyl transferase to albumin ratio can predict severity of coronary artery disease detected by coronary computed tomography angiography

OBJECTIVE

Gamma-glutamyl transferase (GGT) to albumin ratio (GAR) has been shown to be helpful to diagnose and determine the severity of coronary artery disease (CAD). Coronary computed tomography angiography (CCTA) is a guide recommended non-invasive test that provides information about the presence, severity, and morphology of coronary plaques. In this study, our main aim was to investigate the relationship between the presence, morphology, and severity of coronary plaques detected via CCTA and GAR in patients with low to moderate risk for undiagnosed CAD.

METHODS

Nine hundred and sixty six patients were included who underwent CCTA. The severity of CAD and plaque morphology were investigated. CT-adapted Leaman score (CT-LeSc) was calculated to determine the extent of the CAD. The study population was further evaluated in three groups according to tertiles of GAR.

RESULTS

Atherosclerotic plaques were more common in the male gender and older patients with conventional cardiovascular risk factors. GAR was significantly lower in patients with normal CCTA than in patients with a non-obstructive plaque or obstructive plaque on CCTA. Patients in upper GAR tertiles had a higher coronary calcium score (CACS) and CT-LeSc. GAR was one of the independent predictors to predict severe stenotic plaque and high CACS.

CONCLUSION

GAR can independently predict the presence, extent, and severity of CAD determined by CT-LeSc. We believe as a cheap, safe, and widely available tool, GAR would be useful in the diagnosis of CAD.

Comparative differences in the atherosclerotic disease burden between the epicardial coronary arteries: quantitative plaque analysis on coronary computed tomography angiography

AIMS

Anatomic series commonly report the extent and severity of coronary artery disease (CAD), regardless of location. The aim of this study was to evaluate differences in atherosclerotic plaque burden and composition across the major epicardial coronary arteries.

METHODS AND RESULTS

A total of 1271 patients (age 60 ± 9 years; 57% men) with suspected CAD prospectively underwent coronary computed tomography angiography (CCTA). Atherosclerotic plaque volume was quantified with categorization by composition (necrotic core, fibrofatty, fibrous, and calcified) based on Hounsfield Unit density. Per-vessel measures were compared using generalized estimating equation models. On CCTA, total plaque volume was lowest in the LCx (10.0 ± 29.4 mm3), followed by the RCA (32.8 ± 82.7 mm3; P < 0.001), and LAD (58.6 ± 83.3 mm3; P < 0.001), even when correcting for vessel length or volume. The prevalence of ≥2 high-risk plaque features, such as positive remodelling or spotty calcification, occurred less in the LCx (3.8%) when compared with the LAD (21.4%) or RCA (10.9%, P < 0.001). In the LCx, the most stenotic lesion was categorized as largely calcified more often than in the RCA and LAD (55.3% vs. 39.4% vs. 32.7%; P < 0.001). Median diameter stenosis was also lowest in the LCx (16.2%) and highest in the LAD (21.3%; P < 0.001) and located more distal along the LCx when compared with the RCA and LAD (P < 0.001).

CONCLUSION

Atherosclerotic plaque, irrespective of vessel volume, varied across the epicardial coronary arteries; with a significantly lower burden and different compositions in the LCx when compared with the LAD and RCA. These volumetric and compositional findings support a diverse milieu for atherosclerotic plaque development and may contribute to a varied acute coronary risk between the major epicardial coronary arteries.

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.

Percutaneous Coronary Revascularization: JACC Historical Breakthroughs in Perspective

Over the last 4 decades, percutaneous coronary intervention has evolved dramatically and is now an acceptable treatment option for patients with advanced coronary artery disease. However, trialists have struggled to establish the respective roles for percutaneous coronary intervention and coronary artery bypass graft surgery, especially in patients with multivessel disease and unprotected left-main stem coronary artery disease. Several pivotal trials and meta-analyses comparing these 2 revascularization strategies have enabled the relative merits of each technique to be established with regard to the type of ischemic syndrome, the coronary anatomy, and the patient's overall comorbidity. Precision medicine with individualized prognosis is emerging as an important method of selecting treatment. However, the never-ending advancement of technology, in conjunction with the emergence of novel pharmacological agents, will in the future continue to force us to reconsider the evolving question: "Which treatment strategy is better and for which patient?"

Clinical risk factors and atherosclerotic plaque extent to define risk for major events in patients without obstructive coronary artery disease: the long-term coronary computed tomography angiography CONFIRM registry

AIMS

In patients without obstructive coronary artery disease (CAD), we examined the prognostic value of risk factors and atherosclerotic extent.

METHODS AND RESULTS

Patients from the long-term CONFIRM registry without prior CAD and without obstructive (≥50%) stenosis were included. Within the groups of normal coronary computed tomography angiography (CCTA) (N = 1849) and non-obstructive CAD (N = 1698), the prognostic value of traditional clinical risk factors and atherosclerotic extent (segment involvement score, SIS) was assessed with Cox models. Major adverse cardiac events (MACE) were defined as all-cause mortality, non-fatal myocardial infarction, or late revascularization. In total, 3547 patients were included (age 57.9 ± 12.1 years, 57.8% male), experiencing 460 MACE during 5.4 years of follow-up. Age, body mass index, hypertension, and diabetes were the clinical variables associated with increased MACE risk, but the magnitude of risk was higher for CCTA defined atherosclerotic extent; adjusted hazard ratio (HR) for SIS >5 was 3.4 (95% confidence interval [CI] 2.3-4.9) while HR for diabetes and hypertension were 1.7 (95% CI 1.3-2.2) and 1.4 (95% CI 1.1-1.7), respectively. Exclusion of revascularization as endpoint did not modify the results. In normal CCTA, presence of ≥1 traditional risk factors did not worsen prognosis (log-rank P = 0.248), while it did in non-obstructive CAD (log-rank P = 0.025). Adjusted for SIS, hypertension and diabetes predicted MACE risk in non-obstructive CAD, while diabetes did not increase risk in absence of CAD (P-interaction = 0.004).

CONCLUSION

Among patients without obstructive CAD, the extent of CAD provides more prognostic information for MACE than traditional cardiovascular risk factors. An interaction was observed between risk factors and CAD burden, suggesting synergistic effects of both.

Potential Application of Cardiac Computed Tomography for Early Detection of Coronary Atherosclerosis: From Calcium Score to Advanced Atherosclerosis Analysis

In the present article, an overview of advanced analysis of coronary atherosclerosis by coronary computed tomography angiography (CCTA) is provided, focusing on the potential application of this technique in a primary prevention setting. Coronary artery calcium score (CACS) has a well-demonstrated prognostic value even in a primary prevention setting; however, fibro-fatty, high-risk coronary plaque may be missed by this tool. On the contrary, even if not recommended for primary prevention in the general population, CCTA may enable early high-risk atherosclerosis detection, and specific subgroups of patients may benefit from its application. However, further studies are needed to determine the possible use of CCTA in a primary prevention setting.

The revolution project: replacing coronary artery angiography with coronary computed tomography with functional evaluation

In the last two decades, several studies and widespread clinical use demonstrated that coronary computed tomography angiography (CCTA) is 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. Moreover, 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 disease. Particularly, the SYNTAX II trial demonstrated the feasibility of planning interventional and surgical coronary procedures with CCTA thanks to its ability to combine, in a single method, precise stenosis quantification, accurate plaque characterization, functional assessment with fractional flow reserve derived from standard acquired CCTA datasets, and selection of the revascularization modality for any individual patient and of the vessels that need to be revascularized. More recently, the SYNTAX III Revolution trial showed, in patients with three-vessel CAD with or without left main involvement, that treatment decision-making between percutaneous coronary intervention and coronary artery bypass grafting based on CCTA only has an almost perfect agreement with the treatment decision derived from invasive coronary angiography (ICA). The high degree of correlation between CCTA and ICA suggests the potential feasibility of 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.

Natural History of Adapted Leaman Score Assessing Coronary Artery Disease Progression by Computed Tomography Angiography: A 7-Year Follow-Up Report

BACKGROUND

Coronary computed tomographic angiography (CCTA) provides a non-invasive assessment of the coronary artery tree. Computed Tomography - adapted Leaman Score (CT-LeSc) has been shown to be an independent predictor of cardiac events in coronary artery disease (CAD) patients with a score greater than 5 (high).

PURPOSE

To investigate the relationship between CT-LeSc and the progression of CAD and to provide vessel- and segment-level CAD qualification and quantification at baseline and 7-year follow-up.

METHODS

Patients with multivessel CAD and CCTA assessments at baseline and follow-up were included. The CT-LeSc analysis was performed in a paired fashion. The patient-level scores and the differences between each phase were assessed by 2 analysts in an independent core laboratory.

RESULTS

This study analyzed 248 coronary segments from 17 patients with a mean follow-up interval of 7.5 ± 0.6 years. The mean CT-LeSc at baseline and follow-up were 14.6 ± 4.2 and 16.9 ± 1.5, respectively, with an absolute increase of 2.3 ± 1.8. The mean cumulative increase of new lesions was 0.2 ± 0.2 per year. Over time, 14.6% of the non-obstructive lesions became obstructive, and 15.0% of the non-calcified plaques became calcified. There were 29 new lesions found at follow-up, and out of these, 16 were obstructive and 19 were non-calcified.

CONCLUSION

In patients at high risk for cardiac events, as determined by CT-LeSc, there was an increase in CT-LeSc, obstructive lesions, and calcified plaques over the 7-year follow-up period. Most of the new lesions were obstructive and non-calcified. This is the first report showing long-term serial imaging CCTA changes in a high-risk population.

Reviewing imaging modalities for the assessment of plaque erosion

Plaque rupture followed by intracoronary thrombus formation is recognized as the most common pathophysiological mechanism in acute coronary syndromes (ACS). The second most common underlying substrate for ACS is plaque erosion whose hallmark is thrombus formation without cap disruption. Invasive and non-invasive methods have emerged as a promising tool for evaluation of plaque features that either predict or detect plaque erosion. Optical coherence tomography (OCT), high-definition intravascular ultrasound (IVUS), near-infrared spectroscopy (NIRS), and near-infrared autofluorescence (NIRF) have been used to study plaque erosion. The detection of plaque erosion in the clinical setting, mainly facilitated by OCT, has shed light upon the complex pathophysiology underlying ACS not related to plaque rupture. Coronary computed tomography angiography (CCTA), which is to date the most commonly used non-invasive technique for coronary plaque evaluation, may also have a role in the evaluation of patients predisposed to erosion. Also, computational models enabling quantification of endothelial shear stress may pave the way to new research in coronary plaque pathophysiology. This review focuses on the recent imaging techniques for the evaluation of plaque erosion including invasive and non-invasive assessment.

Prognostic value of cardiac CT

In the past decades, coronary computed tomography angiography (CCTA) has become a powerful tool in the management of coronary artery disease. The diagnostic and prognostic value of CCTA has been extensively demonstrated in both large observational studies and clinical trials among stable chest pain patients. The quantification of coronary artery calcium score (CACS) is a well-established predictor of cardiovascular morbidity and mortality in asymptomatic subjects. Besides CACS, the main strength of CCTA is the accurate assessment of the individual total atherosclerotic plaque burden, which holds important prognostic information. In addition, CCTA, by providing detailed information on coronary plaque morphology and composition with identification of specific high-risk plaque features, may further improve the risk stratification beyond the assessment of coronary stenosis. The development of new CCTA applications, such as stress myocardial CT perfusion and computational fluids dynamic applied to standard CCTA to derive CT-based fractional flow reserve (FFR) values have shown promising results to guide revascularization, potentially improving clinical outcomes in stable chest pain patients. In this review, starting from the role of CACS and moving beyond coronary stenosis, we evaluate the existing evidence of the prognostic effectiveness of the CCTA strategy in real-world clinical practice.

Improved long-term prognostic value of coronary CT angiography-derived plaque measures and clinical parameters on adverse cardiac outcome using machine learning

OBJECTIVES

To evaluate the long-term prognostic value of coronary CT angiography (cCTA)-derived plaque measures and clinical parameters on major adverse cardiac events (MACE) using machine learning (ML).

METHODS

Datasets of 361 patients (61.9 ± 10.3 years, 65% male) with suspected coronary artery disease (CAD) who underwent cCTA were retrospectively analyzed. MACE was recorded. cCTA-derived adverse plaque features and conventional CT risk scores together with cardiovascular risk factors were provided to a ML model to predict MACE. A boosted ensemble algorithm (RUSBoost) utilizing decision trees as weak learners with repeated nested cross-validation to train and validate the model was used. Performance of the ML model was calculated using the area under the curve (AUC).

RESULTS

MACE was observed in 31 patients (8.6%) after a median follow-up of 5.4 years. Discriminatory power was significantly higher for the ML model (AUC 0.96 [95%CI 0.93-0.98]) compared with conventional CT risk scores including Agatston calcium score (AUC 0.84 [95%CI 0.80-0.87]), segment involvement score (AUC 0.88 [95%CI 0.84-0.91]), and segment stenosis score (AUC 0.89 [95%CI 0.86-0.92], all p < 0.05). Similar results were shown for adverse plaque measures (AUCs 0.72-0.82, all p < 0.05) and clinical parameters including the Framingham risk score (AUCs 0.71-0.76, all p < 0.05). The ML model yielded significantly higher diagnostic performance compared with logistic regression analysis (AUC 0.96 vs. 0.92, p = 0.024).

CONCLUSION

Integration of a ML model improves the long-term prediction of MACE when compared with conventional CT risk scores, adverse plaque measures, and clinical information. ML algorithms may improve the integration of patient's information to enhance risk stratification.

KEY POINTS

• A machine learning (ML) model portends high discriminatory power to predict major adverse cardiac events (MACE). • ML-based risk stratification shows superior diagnostic performance for MACE prediction over coronary CT angiography (cCTA)-derived risk scores or clinical parameters alone. • A ML model outperforms conventional logistic regression analysis for the prediction of MACE.

Coronary atherosclerosis scoring with semiquantitative CCTA risk scores for prediction of major adverse cardiac events: Propensity score-based analysis of diabetic and non-diabetic patients

AIMS

We aimed to compare semiquantitative coronary computed tomography angiography (CCTA) risk scores - which score presence, extent, composition, stenosis and/or location of coronary artery disease (CAD) - and their prognostic value between patients with and without diabetes mellitus (DM). Risk scores derived from general chest-pain populations are often challenging to apply in DM patients, because of numerous confounders.

METHODS

Out of a combined cohort from the Leiden University Medical Center and the CONFIRM registry with 5-year follow-up data, we performed a secondary analysis in diabetic patients with suspected CAD who were clinically referred for CCTA. A total of 732 DM patients was 1:1 propensity-matched with 732 non-DM patients by age, sex and cardiovascular risk factors. A subset of 7 semiquantitative CCTA risk scores was compared between groups: 1) any stenosis ≥50%, 2) any stenosis ≥70%, 3) stenosis-severity component of the coronary artery disease-reporting and data system (CAD-RADS), 4) segment involvement score (SIS), 5) segment stenosis score (SSS), 6) CT-adapted Leaman score (CT-LeSc), and 7) Leiden CCTA risk score. Cox-regression analysis was performed to assess the association between the scores and the primary endpoint of all-cause death and non-fatal myocardial infarction. Also, area under the receiver-operating characteristics curves were compared to evaluate discriminatory ability.

RESULTS

A total of 1,464 DM and non-DM patients (mean age 58 ± 12 years, 40% women) underwent CCTA and 155 (11%) events were documented after median follow-up of 5.1 years. In DM patients, the 7 semiquantitative CCTA risk scores were significantly more prevalent or higher as compared to non-DM patients (p ≤ 0.022). All scores were independently associated with the primary endpoint in both patients with and without DM (p ≤ 0.020), with non-significant interaction between the scores and diabetes (interaction p ≥ 0.109). Discriminatory ability of the Leiden CCTA risk score in DM patients was significantly better than any stenosis ≥50% and ≥70% (p = 0.003 and p = 0.007, respectively), but comparable to the CAD-RADS, SIS, SSS and CT-LeSc that also focus on the extent of CAD (p ≥ 0.265).

CONCLUSION

Coronary atherosclerosis scoring with semiquantitative CCTA risk scores incorporating the total extent of CAD discriminate major adverse cardiac events well, and might be useful for risk stratification of patients with DM beyond the binary evaluation of obstructive stenosis alone.

Coronary Artery Disease Assessed by Computed Tomography-Based Leaman Score in Patients With Low-Risk Transcatheter Aortic Valve Implantation

We aimed to evaluate the burden of coronary artery disease (CAD) using the computed tomography (CT) Leaman score in low-risk transcatheter aortic valve implantation (TAVI) patients. The extent of CAD in low-risk patients with aortic stenosis who are candidates for TAVI has not been accurately quantified. The CT Leaman score was developed to quantify coronary CT angiography (CCTA) atherosclerotic burden and has been validated to evaluate the extent of CAD. CT Leaman score >5 has been associated with an increase in major adverse cardiac events over long-term follow-up. The study population included patients enrolled in the Low Risk TAVI trial who underwent CCTA before the procedure. For the CT Leaman score, we used 3 sets of weighting factors: (1) location of coronary plaques, (2) type of plaque, and (3) degree of stenosis. A total of 200 patients were enrolled in the Low Risk TAVI trial. Excluded were 31 patients who had no analyzable CCTA imaging. For the remaining 169 patients, the mean CT Leaman score was 6.27 ± 0.27, of whom 102 (60.4%) had CT Leaman score >5. Nearly all analyzed patients (97%) had coronary plaques. Furthermore, 33 patients (19.5%) had potentially obstructive coronary plaques (>50% stenosis by CCTA) in proximal segments. Most low-risk TAVI patients have significant CAD burden by CCTA. It should be a priority for future TAVI devices to guarantee unimpeded access to the coronary arteries for selective angiography and interventions.

Relationships between myocardial perfusion abnormalities and integrated indices of atherosclerotic burden: clinical impact of combined anatomic-functional evaluation

Aim to evaluate the relationships between functional and anatomical information obtained by myocardial perfusion imaging (MPI) and coronary computed tomography angiography (CCTA) in a series of consecutive patients at intermediate probability of coronary artery disease (CAD). Material and Methods — The study group comprised 139 patients (83 men, age of 61.6±7.5 years) who underwent CCTA and single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI). Based on CCTA results patients were divided into three groups: 1) with the absence of coronary atherosclerosis on CCTA; 2) with non-obstructive CAD (<50%); 3) with obstructive (≥50%) CAD. The Segment Involvement Score, Segment Stenosis Score (SSS) and CTA Risk Score were calculated as measures of global atherosclerosis burden. MPI studies were considered abnormal in the presence of SSS≥4. Results — Abnormal myocardial perfusion was detected in 60% of cases in group 1 and 2; in 75% of cases in group 3. The overall frequencies of normal and abnormal MPI studies differed significantly only in obstructive CAD patients and did not differ in group 1 and 2. There were no significant correlations between calcium score, atherosclerotic lesion length, positive remodelling index and MPI results in patients with non-obstructive as well as in patients with obstructive CAD. In group of patients with obstructive CAD Segment Stenosis Score correlated wekly with SSS (r=0.39, p=0.001) and SDS (r=0.28; p=0.012); the CTA Risk Score showed correlationes with SSS (r=0.38, p=0.002) and SDS (r=0.30, p=0.020). Conclusion — Myocardial perfusion abnormalities may develop even in the absence of critical coronary artery lesions. The extent of myocardial ischemia correlates with measures of global CAD burden only in patients with obstructive CAD.

Severe obstructive sleep apnea is associated with significant coronary artery plaque burden independent of traditional cardiovascular risk factors

Obstructive Sleep Apnea (OSA) is strongly associated with adverse cardiovascular events. In these patients, increased oxidative stress has been associated with accelerated coronary atherosclerosis. However, it is unclear if OSA is associated with significant coronary artery plaque burden. Our aim is to determine whether OSA and/or markers of hypoxemia are associated with coronary plaque burden (CPB). Patients who had coronary computed tomography angiography (CCTA) and a polysomnogram within 1 year of each other between 2011 and 2016 were analyzed. Apnea-Hypopnea Index (AHI) and hypoxemic burden (ODI3%, ODI4%, nadir SpO2, average spO₂ and time of spO₂ < 88%) were obtained from the polysomnogram. Total CPB was assessed using the prognostically validated CT-Leaman score (CT-LeSc). Significant CPB was defined as CT-LeSc ≥ 8.3. There were 119 patients with mean (± SD) age of 59 ± 12 years. Using logistical regression analysis; AHI, ODI4% and ODI3% were the only parameters associated with significant CPB. Severe OSA (AHI ≥ 30 events/h) was associated with significant CPB with adjusted OR of 3.21 (p = 0.010) independent of traditional cardiovascular risk factors. Mechanisms associated with apnea and hypopnea events (as measured by AHI, ODI3% and ODI4%), but not the severity of arterial desaturation (nadir SpO₂, burden of SpO₂ < 88%) were associated with significant CPB.

Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning

Background Coronary CT angiography contains prognostic information but the best method to extract these data remains unknown. Purpose To use machine learning to develop a model of vessel features to discriminate between patients with and without subsequent death or cardiovascular events. Performance was compared with that of conventional scores. Materials and Methods Coronary CT angiography was analyzed by radiologists into four features for each of 16 coronary segments. Four machine learning model types were explored. Five conventional vessel scores were computed for comparison including the Coronary Artery Disease Reporting and Data System (CAD-RADS) score. The National Death Index was retrospectively queried from January 2004 through December 2015. Outcomes were all-cause mortality, coronary heart disease deaths, and coronary deaths or nonfatal myocardial infarctions. Score performance was assessed by using area under the receiver operating characteristic curve (AUC). Results Between February 2004 and November 2009, 6892 patients (4452 men [mean age ± standard deviation, 51 years ± 11] and 2440 women [mean age, 57 years ± 12]) underwent coronary CT angiography (median follow-up, 9.0 years; interquartile range, 8.2-9.8 years). There were 380 deaths of all causes, 70 patients died of coronary artery disease, and 43 patients reported nonfatal myocardial infarctions. For all-cause mortality, the AUC was 0.77 (95% confidence interval: 0.76, 0.77) for machine learning (k-nearest neighbors) versus 0.72 (95% confidence interval: 0.72, 0.72) for CAD-RADS (P < .001). For coronary artery heart disease deaths, AUC was 0.85 (95% confidence interval: 0.84, 0.85) for machine learning versus 0.79 (95% confidence interval: 0.78, 0.80) for CAD-RADS (P < .001). When deciding whether to start statins, if the choice is made to tolerate treating 45 patients to be sure to include one patient who will later die of coronary disease, the use of the machine learning score ensures that 93% of patients with events will be administered the drug; if CAD-RADS is used, only 69% will be treated. Conclusion Compared with Coronary Artery Disease Reporting and Data System and other scores, machine learning methods better discriminated patients who subsequently experienced an adverse event from those who did not. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Schoepf and Tesche in this issue.

Clinical determinants of plasma cardiac biomarkers in patients with stable chest pain

OBJECTIVE

Troponin and B-type natriuretic peptide (BNP) concentrations are associated with cardiovascular risk in stable patients. Understanding their determinants and identifying modifiable clinical targets may improve outcomes. We aimed to establish clinical and cardiac determinants of these biomarkers.

METHODS

This was a prespecified substudy from the randomised Scottish Computed Tomography of the Heart trial, which enrolled patients 18-75 years with suspected stable angina between 2010 and 2014 (NCT01149590). We included patients from six centres in whom high-sensitivity troponin I and BNP were measured (Singulex Erenna). Patients with troponin >99th centile upper reference limit (10.2 ng/L) or BNP ≥400 ng/L were excluded to avoid inclusion of patients with myocardial injury or heart failure. Multivariable linear regression models were constructed with troponin and BNP as dependent variables.

RESULTS

In total, 885 patients were included; 881 (99%) and 847 (96%) had troponin and BNP concentrations above the limit of detection, respectively. Participants had a slight male preponderance (n=513; 56.1%), and the median age was 59.0 (IQR 51.0-65.0) years. The median troponin and BNP concentrations were 1.4 (IQR 0.90-2.1) ng/L and 29.1 (IQR 14.0-54.0) ng/L, respectively. Age and atherosclerotic burden were independent predictors of both biomarkers. Male sex, left ventricular mass and systolic blood pressure were independent predictors of increased troponin. In contrast, female sex and left ventricular volume were independent predictors of increased BNP.

CONCLUSIONS

Troponin and BNP are associated with coronary atherosclerosis but have important sex differences and distinct and contrasting associations with CT-determined left ventricular mass and volume.

CLINICAL TRIAL REGISTRATION

NCT01149590; Post-results.

Long-term prognostic value of coronary computed tomography angiography in chest pain patients

BACKGROUND

Coronary computed tomography angiography (CCTA) is increasingly used to detect coronary artery disease (CAD), but long-term follow-up studies are still scarce.

PURPOSE

To evaluate the prognostic value of CCTA in patients with suspected CAD.

MATERIAL AND METHODS

A total of 1205 consecutive CCTA patients with chest pain were classified as normal coronary arteries, non-obstructive CAD, or obstructive CAD. The primary outcome was major adverse cardiac event (MACE), defined as a composite outcome including cardiac death, myocardial infarction, unstable angina pectoris, or late revascularization (after >90 days).

RESULTS

Over 7.5 years follow-up (median = 3.1 years), Kaplan-Meier estimates demonstrated a MACE in 1.0%, 4.6%, and 20.7% in normal coronary arteries, non-obstructive CAD, and obstructive CAD, respectively. Log rank test for pairwise comparisons showed significant differences between non-obstructive CAD and normal coronary arteries ( P = 0.023) and between obstructive CAD and normal coronary arteries ( P < 0.001). In a multivariable analysis, adjusting for classical risk factors, non-obstructive CAD and obstructive CAD were independent predictors of MACE, with hazard ratios (HR) of 3.22 ( P = 0.041) and 25.18 ( P < 0.001), respectively.

CONCLUSION

Patients with normal coronary arteries have excellent long-term prognosis, but the risk for MACE increases with non-obstructive and obstructive CAD. Both non-obstructive and obstructive CAD are independently associated with future ischemic events.

Quantification of coronary atherosclerotic burden with coronary computed tomography angiography: adapted Leaman score in Croatian patients

The aim of the study was to quantify the total coronary atherosclerotic burden in patients with suspected coronary artery disease (CAD) defined by coronary computed tomography adapted Leaman score (CT-LeSc) and to estimate its cut-off level for high coronary atherosclerotic burden. We enrolled 434 consecutive patients referred to coronary computed tomography angiography, of which 261 patients fulfilled the study inclusion criteria. Demographic and clinical characteristics, as well as CAD risk factors were obtained. CAD pre-test probabilities were estimated by the Diamond-Forrester model and Morise score. The coronary atherosclerotic burden was estimated using CT-LeSc. As a cut-off for a high coronary atherosclerotic burden, we used 3rd tercile (Tc3) (CT-LeSc ≥ 5.52). We evaluated the association of clinical characteristics and risk factors with Tc3 in univariate and multivariate analysis. There were 60.9% males and 39.1% females, 81% of patients had above-normal weight, 68.2% hypertension, 54.0% dyslipidemia, 15.3% diabetes mellitus, 12.3% positive smoking history and 11.9% had a family history of CAD. According to the Diamond-Forrester model and Morise score the majority of patients had intermediate risk, 59.7 and 52.8%, followed by the high-risk group, 36.0 and 34.4%, respectively. Age, dyslipidemia, hypertension and pre-test risk scores in the univariate analysis significantly predicted Tc3. In the multivariate analysis, male sex (p = 0.004), dyslipidemia (p = 0.002) and coronary calcium score (< 0.001) were identified as predictors of Tc3. CT-LeSc quantified the total coronary atherosclerotic burden and showed an association of risk factors and pre-test probabilities with Tc3.