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

Predicting vulnerable carotid plaques by detecting wall shear stress based on ultrasonic vector flow imaging

OBJECTIVE

Carotid plaque vulnerability is a significant factor in the risk of cardiocerebrovascular events, with intraplaque neovascularization (IPN) being a crucial characteristic of plaque vulnerability. This study investigates the value of ultrasound vector flow imaging (V-flow) for measuring carotid plaque wall shear stress (WSS) in predicting the extent of IPN.

METHODS

We enrolled 140 patients into three groups: 53 in the plaque group (72 plaques), 23 in the stenosis group (27 plaques), and 64 in the control group. V-flow was used to measure WSS parameters, including the average WSS (WSS mean) and the maximum WSS (WSS max), across three plaque locations: mid-upstream, maximum thickness, and mid-downstream. Contrast-enhanced ultrasound examination was used in 76 patients to analyze IPN and its correlation with WSS parameters.

RESULTS

WSS max in the stenosis group was significantly higher than that in the control and plaque groups at the maximum thickness part (P < .05) and WSS mean in the stenosis group was significantly lower than that in the control group at the mid-upstream and mid-downstream segments (P < .05). WSS mean in the plaque group was significantly lower than that of the control group at all three locations (P < .05). Contrast-enhanced ultrasound examination revealed that plaques with neovascularization enhancement exhibited significantly higher WSS values (P < .05), with a positive correlation between WSS parameters and IPN enhancement grades, particularly WSS max at the thickest part (r = 0.508). Receiver operating characteristic curve analysis of WSS parameters for evaluating IPN showed that the efficacy of WSS max in evaluating IPN was better than that of WSS mean (P < .05), with an area under the curve of 0.7762 and 0.6973 (95% confidence intervals, 0.725-0.822 and 0.642-0.749, respectively). The cut-offs were 4.57 Pa and 1.12 Pa, sensitivities were 74.03% and 63.64%, and specificities were 75.00% and 68.18%.

CONCLUSIONS

V-flow effectively measures WSS in carotid plaques. WSS max provides a promising metric for assessing IPN, offering potential insights into plaque characteristics and showing some potential in predicting plaque vulnerability.

Atherosclerosis quantification and cardiovascular risk: the ISCHEMIA trial

BACKGROUND AND AIMS

The aim of this study was to determine the prognostic value of coronary computed tomography angiography (CCTA)-derived atherosclerotic plaque analysis in ISCHEMIA.

METHODS

Atherosclerosis imaging quantitative computed tomography (AI-QCT) was performed on all available baseline CCTAs to quantify plaque volume, composition, and distribution. Multivariable Cox regression was used to examine the association between baseline risk factors (age, sex, smoking, diabetes, hypertension, ejection fraction, prior coronary disease, estimated glomerular filtration rate, and statin use), number of diseased vessels, atherosclerotic plaque characteristics determined by AI-QCT, and a composite primary outcome of cardiovascular death or myocardial infarction over a median follow-up of 3.3 (interquartile range 2.2-4.4) years. The predictive value of plaque quantification over risk factors was compared in an area under the curve (AUC) analysis.

RESULTS

Analysable CCTA data were available from 3711 participants (mean age 64 years, 21% female, 79% multivessel coronary artery disease). Amongst the AI-QCT variables, total plaque volume was most strongly associated with the primary outcome (adjusted hazard ratio 1.56, 95% confidence interval 1.25-1.97 per interquartile range increase [559 mm3]; P = .001). The addition of AI-QCT plaque quantification and characterization to baseline risk factors improved the model's predictive value for the primary outcome at 6 months (AUC 0.688 vs. 0.637; P = .006), at 2 years (AUC 0.660 vs. 0.617; P = .003), and at 4 years of follow-up (AUC 0.654 vs. 0.608; P = .002). The findings were similar for the other reported outcomes.

CONCLUSIONS

In ISCHEMIA, total plaque volume was associated with cardiovascular death or myocardial infarction. In this highly diseased, high-risk population, enhanced assessment of atherosclerotic burden using AI-QCT-derived measures of plaque volume and composition modestly improved event prediction.

Cardiovascular risk and subclinical atherosclerosis in first-degree relatives of patients with premature cardiovascular disease

Background

Screening first-degree relatives (FDRs) of patients with premature coronary artery disease (CAD) is recommended but not routinely performed.

Objectives

To assess the diagnostic yield and impact on clinical management of a clinical and imaging-based screening program of FDRs delivered in the setting of routine clinical care.

Methods

We recruited FDRs of patients with premature CAD with no personal history of CAD and prospectively assessed for: 1) cardiovascular risk and presence of significant subclinical atherosclerosis (SA) defined as plaque on carotid ultrasound, stenosis >50% or extensive atherosclerosis on coronary computed tomography angiography, or coronary artery calcium scores >100 Agatston units or >75% percentile for age and sex; 2) utilization of preventive medications and lipid levels prior enrolment and after completion of the assessment.

Results

We assessed 132 FDRs (60.6% females), mean (SD) age 47(17) years old. Cardiovascular risk was high in 38.2%, moderate in 12.2%, and low in 49.6% of FDRs. SA was present in 34.1% of FDRs, including 12.5% in low, 51.9% in moderate, and 55.0% in high calculated risk groups. After assessment, LLT was initiated in 32.6% of FDRs and intensified in 16.0% leading to mean (SD) LDL-C decrease of 1.07(1.10) mmol/L in patients with high calculated risk or SA. LLT was recommended to all patients with high calculated risk, but those with SA were more likely to receive the medications from pharmacies (93.3% vs 60.0%, p = 0.006).

Conclusion

Screening the FDRs of patients with premature CAD is feasible, may have high diagnostic yield and impact risk factor management.

Rapid Plaque Progression Is Independently Associated With Hyperglycemia and Low HDL Cholesterol in Patients With Stable Coronary Artery Disease: A PARADIGM Study

BACKGROUND

We assessed whether combinations of cardiometabolic risk factors independently predict coronary plaque progression (PP) and major adverse cardiovascular events in patients with stable coronary artery disease.

METHODS

Patients with known or suspected stable coronary artery disease (60.9±9.3 years, 55.4% male) undergoing serial coronary computed tomography angiographies (≥2 years apart), with clinical characterization and follow-up (N=1200), were analyzed from the PARADIGM study (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging). Plaque volumes measured in coronary segments (≥2 mm in diameter) were summed to provide whole heart plaque volume (mm3) and percent atheroma volume (plaque volume/vessel volume×100; %) per patient at baseline and follow-up. Rapid PP was defined as a percent atheroma volume increase of ≥1.0%/y. Major adverse cardiovascular events included nonfatal myocardial infarction, death, and unplanned coronary revascularization.

RESULTS

In an interscan period of 3.2 years (interquartile range, 1.9), rapid PP occurred in 341 patients (28%). At multivariable analysis, the combination of cardiometabolic risk factors defined as metabolic syndrome predicted rapid PP (odds ratio, 1.51 [95% CI, 1.12-2.03]; P=0.007) together with older age, smoking habits, and baseline percent atheroma volume. Among single cardiometabolic variables, high fasting plasma glucose (diabetes or fasting plasma glucose >100 mg/dL) and low HDL-C (high-density lipoprotein cholesterol; <40 mg/dL in males and <50 mg/dL in females) were independently associated with rapid PP, in particular when combined (odds ratio, 2.37 [95% CI, 1.56-3.61]; P<0.001). In a follow-up of 8.23 years (interquartile range, 5.92-9.53), major adverse cardiovascular events occurred in 201 patients (17%). At multivariable Cox analysis, the combination of high fasting plasma glucose with high systemic blood pressure (treated hypertension or systemic blood pressure >130/85 mm Hg) was an independent predictor of events (hazard ratio, 1.79 [95% CI, 1.10-2.90]; P=0.018) together with family history, baseline percent atheroma volume, and rapid PP.

CONCLUSIONS

In patients with stable coronary artery disease, the combination of hyperglycemia with low HDL-C is associated with rapid PP independently of other risk factors, baseline plaque burden, and treatment. The combination of hyperglycemia with high systemic blood pressure independently predicts the worse outcome beyond PP.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02803411.

Triglyceride-glucose index is associated with myocardial ischemia and poor prognosis in patients with ischemia and no obstructive coronary artery disease

BACKGROUND

Ischemia and no obstructive coronary artery disease (INOCA) is increasingly recognized and associated with poor outcomes. The triglyceride-glucose (TyG) index is a reliable alternative measure of insulin resistance significantly linked to cardiovascular disease and adverse prognosis. We investigated the association between the TyG index and myocardial ischemia and the prognosis in INOCA patients.

METHODS

INOCA patients who underwent both coronary angiography and myocardial perfusion imaging (MPI) were included consecutively. All participants were divided into three groups according to TyG tertiles (T1, T2, and T3). Abnormal MPI for myocardial ischemia in individual coronary territories was defined as summed stress score (SSS) ≥ 4 and summed difference score (SDS) ≥ 2. SSS refers to the sum of all defects in the stress images, and SDS is the difference of the sum of all defects between the rest images and stress images. All patients were followed up for major adverse cardiac events (MACE).

RESULTS

Among 332 INOCA patients, 113 (34.0%) had abnormal MPI. Patients with higher TyG index had a higher rate of abnormal MPI (25.5% vs. 32.4% vs. 44.1%; p = 0.012). Multivariate logistic analysis showed that a high TyG index was significantly correlated with abnormal MPI in INOCA patients (OR, 1.901; 95% CI, 1.045-3.458; P = 0.035). During the median 35 months of follow-up, 83 (25%) MACE were recorded, and a higher incidence of MACE was observed in the T3 group (T3 vs. T2 vs. T1: 36.9% vs. 21.6% vs. 16.4%, respectively; p = 0.001). In multivariate Cox regression analysis, the T3 group was significantly associated with the risk of MACE compared to the T1 group (HR, 2.338; 95% CI 1.253-4.364, P = 0.008).

CONCLUSION

This study indicates for the first time that the TyG index is significantly associated with myocardial ischemia and poor prognosis among INOCA patients.

Innovations in cardiac computed tomography: Imaging in coronary artery disease

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool in the non-invasive evaluation of coronary artery disease (CAD). Recent advancements in imaging techniques, quantitative plaque assessment methods, assessment of coronary physiology, and perivascular coronary inflammation have propelled CCTA to the forefront of CAD management, enabling precise risk stratification, disease monitoring, and evaluation of treatment response. However, challenges persist, including the need for cardiovascular outcomes data for therapy modifications based on CCTA findings and the lack of standardized quantitative plaque assessment techniques to establish universal guidelines for treatment strategies. This review explores the current utilization of CCTA in clinical practice, highlighting its clinical impact and discussing challenges and opportunities for future development. By addressing these nuances, CCTA holds promise for revolutionizing coronary imaging and improving CAD management in the years to come. Ultimately, the goal is to provide precise risk stratification, optimize medical therapy, and improve cardiovascular outcomes while ensuring cost-effectiveness for healthcare systems.

Comparison of Coronary Artery Calcium and Quantitative Coronary Plaque in Predicting Obstructive Coronary Artery Disease: Subgroup Analysis of the CLARIFY Study

Background: Agatston coronary artery calcium (CAC) score is a strong predictor of mortality. However, the relationship between CAC and quantitative calcified plaque volume (CPV), which is measured on coronary computed tomography angiography (CCTA), is not well understood. Furthermore, there is limited evidence evaluating the difference between CAC versus CPV and CAC versus total plaque volume (TPV) in predicting obstructive coronary artery disease (CAD). Methods: This study included 147 subjects from the CLARIFY registry, a multicentered study of patients undergoing assessment using CCTA and CAC score as part of acute and stable chest pain evaluation. Automated software service (Cleerly.Inc, Denver, CO, USA) was used to evaluate the degree of vessel stenosis and plaque quantification on CCTA. CAC was measured using the standard Agatston method. Spearman correlation and receiver operating characteristic curve analysis was performed to evaluate the diagnostic ability of CAC, CPV and TPV in detecting obstructive CAD. Results: Results demonstrated a very strong positive correlation between CAC and CPV (r=0.76, p=0.0001) and strong correlation between CAC and TPV (r=0.72, p<0.001) at per-patient level analysis. At per-patient level analysis, the sensitivity of CAC (68%) is lower than CPV (77%) in predicting >50% stenosis, but negative predictive value is comparable. However, the sensitivity of TPV is higher compared with CAC in predicting >50% stenosis, and the negative predictive value of TPV is also higher. Conclusion: CPV and TPV are more sensitive in predicting the severity of obstructive CAD compared with the CAC score. However, the negative predictive value of CAC is comparable to CPV, but is lower than TPV. This study elucidates the relationship between CAC and quantitative plaque types, and especially emphasizes the differences between CAC and CPV which are two distinct plaque measurement techniques that are utilized in predicting obstructive CAD.

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.

Apolipoprotein B is associated with CT-angiographic progression beyond low-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol in patients with coronary artery disease

BACKGROUND

Accumulating evidence indicated that apolipoprotein B (apoB) was the principal lipid determinant of coronary artery disease (CAD). Nevertheless, the connection between apoB and angiographic progression of CAD remained undetermined.

METHODS

Five hundred and forty-four CAD patients with twice coronary computed tomography angiography experiences were enrolled. The Gensini scoring system was used to assess angiographic progression. Incident angiographic progression was defined as an annual change rate of the Gensini score of > 1 point. The predictive efficacy of baseline apoB levels for angiographic progression was assessed using a receiver operating characteristic (ROC) curve. For comparative purposes, patients were categorized into three groups according to their baseline apoB tertiles. Furthermore, discordance analyses defined by the median were performed to assess the superiority of apoB over lipoprotein cholesterol in predicting angiographic progression of CAD.

RESULTS

Angiographic progression was observed in 184 patients (33.8%) during a follow-up period of 2.2-year. The area under the ROC curve was 0.565 (0.522-0.607, P = 0.013). The incidence of angiographic progression was elevated with increasing apoB tertile after adjusting for confounding factors [odds ratio (OR) for the medium apoB tertile: 1.92, 95% confidence interval (CI): 1.15-3.19, P = 0.012; OR for the high apoB tertile: 2.05, 95%CI:1.17-3.60, P = 0.013]. Additionally, discordance analyses showed that the higher apoB group had a significantly higher risk of CAD progression in the fully adjusted model (all P < 0.05).

CONCLUSIONS

ApoB could be used as an accurate and comprehensive indicator of angiographic progression in patients with CAD.

Global trans-lesional computed tomography-derived fractional flow reserve gradient is associated with clinical outcomes in diabetic patients with non-obstructive coronary artery disease

BACKGROUND

Coronary computed tomography angiography (CCTA)-derived fractional flow reserve (CT-FFR) enables physiological assessment and risk stratification, which is of significance in diabetic patients with nonobstructive coronary artery disease (CAD). We aim to evaluate prognostic value of the global trans-lesional CT-FFR gradient (GΔCT-FFR), a novel metric, in patients with diabetes without flow-limiting stenosis.

METHODS

Patients with diabetes suspected of having CAD were prospectively enrolled. GΔCT-FFR was calculated as the sum of trans-lesional CT-FFR gradient in all epicardial vessels greater than 2 mm. Patients were stratified into low-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR < 0.20), high-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR ≥ 0.20), and flow-limiting group (CT-FFR ≤ 0.75). Discriminant ability for major adverse cardiovascular events (MACE) prediction was compared among 4 models [model 1: Framingham risk score; model 2: model 1 + Leiden score; model 3: model 2 + high-risk plaques (HRP); model 4: model 3 + GΔCT-FFR] to determine incremental prognostic value of GΔCT-FFR.

RESULTS

Of 1215 patients (60.1 ± 10.3 years, 53.7% male), 11.3% suffered from MACE after a median follow-up of 57.3 months. GΔCT-FFR (HR: 2.88, 95% CI 1.76-4.70, P < 0.001) remained independent risk factors of MACE in multivariable analysis. Compared with the low-gradient without flow-limiting group, the high-gradient without flow-limiting group (HR: 2.86, 95% CI 1.75-4.68, P < 0.001) was associated with higher risk of MACE. Among the 4 risk models, model 4, which included GΔCT-FFR, showed the highest C-statistics (C-statistics: 0.75, P = 0.002) as well as a significant net reclassification improvement (NRI) beyond model 3 (NRI: 0.605, P < 0.001).

CONCLUSIONS

In diabetic patients with non-obstructive CAD, GΔCT-FFR was associated with clinical outcomes at 5 year follow-up, which illuminates a novel and feasible approach to improved risk stratification for a global hemodynamic assessment of coronary artery in diabetic patients.

Association Between Major Adverse Cardiovascular Events and the Gensini Score or Coronary Artery Calcification Score in Hypertensive Patients Who Have Undergone Coronary Computed Tomography Angiography

Background

From the Fukuoka University Coronary Computed Tomography Angiography (FU-CCTA) registry, we present major adverse cardiovascular events (MACEs) in hypertensive patients who have undergone CCTA, and the association between MACEs and the Gensini score of coronary arteries or the coronary artery calcification (CAC) score.

Methods

Of the patients who underwent CCTA for coronary artery disease (CAD) screening at Fukuoka University Hospital, 318 hypertensive patients who had at least one cardiovascular risk factor or suspected CAD were enrolled. The patients were divided into two groups: MACEs and non-MACEs groups. The severity of atherosclerosis of coronary arteries was assessed by the Gensini score. The CAC score was also defined by computed tomography (CT) images at the time of CCTA. A primary endpoint was MACEs (all-cause death, ischemic stroke, acute myocardial infarction, coronary revascularization). The patients were followed for up to 5 years.

Results

The patients were 68 ± 10 years, and 50% were males. The percentages of smoking, dyslipidemia, diabetes, and chronic kidney disease were 39%, 70%, 26% and 37%, respectively. The %males, %smoking, CAC score and Gensini score in the MACEs group were significantly higher than those in the non-MACEs group. On the other hand, the differences in age, dyslipidemia, diabetes, or chronic kidney disease between the groups were not seen. A multivariate analysis was performed regarding the presence or absence of MACE by logistic regression analysis of the CAC score or Gensini score in addition to conventional risk factors as independent variables. A Cox regression analysis revealed significant relationships for both the CAC score (P = 0.043) and the Gensini score (P = 0.008).

Conclusions

The CAC score and the Gensini score could predict MACEs in hypertensive patients who have undergone CCTA.

A Coronary CT Angiography Radiomics Model to Identify Vulnerable Plaque and Predict Cardiovascular Events

Background A noninvasive coronary CT angiography (CCTA)-based radiomics technique may facilitate the identification of vulnerable plaques and patients at risk for future adverse events. Purpose To assess whether a CCTA-based radiomic signature (RS) of vulnerable plaques defined with intravascular US was associated with increased risk for future major adverse cardiac events (MACE). Materials and Methods In a retrospective study, an RS of vulnerable plaques was developed and validated using intravascular US as the reference standard. The RS development data set included patients first undergoing CCTA and then intravascular US within 3 months between June 2013 and December 2020 at one tertiary hospital. The development set was randomly assigned to training and validation sets at a 7:3 ratio. Diagnostic performance was assessed internally and externally from three tertiary hospitals using the area under the curve (AUC). The prognostic value of the RS for predicting MACE was evaluated in a prospective cohort with suspected coronary artery disease between April 2018 and March 2019. Multivariable Cox regression analysis was used to evaluate the RS and conventional anatomic plaque features (eg, segment involvement score) for predicting MACE. Results The RS development data set included 419 lesions from 225 patients (mean age, 64 years ± 10 [SD]; 68 men), while the prognostic cohort included 1020 lesions from 708 patients (mean age, 62 years ± 11; 498 men). Sixteen radiomic features, including two shape features and 14 textural features, were selected to build the RS. The RS yielded a moderate to good AUC in the training, validation, internal, and external test sets (AUC = 0.81, 0.75, 0.80, and 0.77, respectively). A high RS (≥1.07) was independently associated with MACE over a median 3-year follow-up (hazard ratio, 2.01; P = .005). Conclusion A coronary CT angiography-derived radiomic signature of coronary plaque enabled the detection of vulnerable plaques that were associated with increased risk for future adverse cardiac outcomes. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by De Cecco and van Assen in this issue.

The long-term prognostic value provided by Coronary CT angiography

BACKGROUND

Risk-stratification of patients has a major role in the prevention and treatment of cardiovascular disease. The aim was to find the most informative predictors of cardiovascular events in patients undergoing Coronary CT Angiography.

METHODS

We carried out a secondary analysis of a large registry dataset. The included population comprises adults aged 18 or older who underwent Coronary CT Angiography of 64-detector rows or greater. We clustered patients based on their characteristics and compared the risk for poor clinical outcomes between the two clusters.

RESULTS

There were two clusters of patients having different risks for all-cause death, myocardial infarction, and late revascularization [hazard ratios (95%CI) = 2.28 (2.02, 2.57), 1.63 (1.40, 1.89), and 2.46 (2.1, 2.88), all P < 0.001]. The severity of stenosis in the left main coronary artery adjusted for age and sex was the most significant predictor of the high-risk cluster [adjusted odds ratio (95%CI) = 3.35 (2.98, 3.77), P < 0.001]. The severity of stenosis in the first obtuse marginal branch of the left circumflex, distal left circumflex, distal left anterior descending, posterior descending, the first diagonal branch of the left anterior descending, and proximal right coronary artery were important as well (all adjusted odds ratios ≥ 2.52). Cluster profiling showed a higher performance for CT Angiography features (sensitivity = 97.4%, specificity = 85.7%, C-statistic = 98.7%) than calcium, Framingham, and Duke scores in identifying high-risk patients (C-statistic = 82.1, 77.0, and 88.2%, respectively).

CONCLUSION

Coronary CT Angiography can accurately risk-stratify patients concerning poor clinical outcomes.

Ischemia and no obstructive coronary arteries (INOCA): A narrative review

Myocardial ischemia with no obstructive coronary arteries (INOCA) is a chronic coronary syndrome condition that is increasingly being recognized as a substantial contributor to adverse cardiovascular mortality and outcomes, including myocardial infarction and heart failure with preserved ejection fraction (HFpEF). While INOCA occurs in both women and men, women are more likely to have the finding of INOCA and are more adversely impacted by angina, with recurrent hospitalizations and a lower quality of life with this condition. Abnormal epicardial coronary vascular function and coronary microvascular dysfunction (CMD) have been identified in a majority of INOCA patients on invasive coronary function testing. CMD can co-exist with obstructive epicardial coronary artery disease (CAD), diffuse non-obstructive epicardial CAD, and with coronary vasospasm. Epicardial vasospasm can also occur with normal coronary arteries that have no atherosclerotic plaque on intravascular imaging. While all predisposing factors are not clearly understood, cardiometabolic risk factors, and endothelium dependent and independent mechanisms that increase oxidative stress and inflammation are associated with microvascular injury, CMD and INOCA. Cardiac autonomic dysfunction has also been implicated in abnormal vasoreactivity and persistent symptoms. INOCA is under-recognized and under-diagnosed, partly due to the heterogenous patient populations and mechanisms. However, diagnostic testing methods are available to guide INOCA management. Treatment of INOCA is evolving, and focuses on cardiac risk factor control, improving ischemia, reducing atherosclerosis progression, and improving angina and quality of life. This review focuses on INOCA, relations to HFpEF, available diagnostics, current and investigational therapeutic strategies, and knowledge gaps in this condition.

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.

Comparison of conventional scoring systems to machine learning models for the prediction of major adverse cardiovascular events in patients undergoing coronary computed tomography angiography

BACKGROUND

The study aims to compare the prognostic performance of conventional scoring systems to a machine learning (ML) model on coronary computed tomography angiography (CCTA) to discriminate between the patients with and without major adverse cardiovascular events (MACEs) and to find the most important contributing factor of MACE.

MATERIALS AND METHODS

From November to December 2019, 500 of 1586 CCTA scans were included and analyzed, then six conventional scores were calculated for each participant, and seven ML models were designed. Our study endpoints were all-cause mortality, non-fatal myocardial infarction, late coronary revascularization, and hospitalization for unstable angina or heart failure. Score performance was assessed by area under the curve (AUC) analysis.

RESULTS

Of 500 patients (mean age: 60 ± 10; 53.8% male subjects) referred for CCTA, 416 patients have met inclusion criteria, 46 patients with early (<90 days) cardiac evaluation (due to the inability to clarify the reason for the assessment, deterioration of the symptoms vs. the CCTA result), and 38 patients because of missed follow-up were not enrolled in the final analysis. Forty-six patients (11.0%) developed MACE within 20.5 ± 7.9 months of follow-up. Compared to conventional scores, ML models showed better performance, except only one model which is eXtreme Gradient Boosting had lower performance than conventional scoring systems (AUC:0.824, 95% confidence interval (CI): 0.701-0.947). Between ML models, random forest, ensemble with generalized linear, and ensemble with naive Bayes were shown to have higher prognostic performance (AUC: 0.92, 95% CI: 0.85-0.99, AUC: 0.90, 95% CI: 0.81-0.98, and AUC: 0.89, 95% CI: 0.82-0.97), respectively. Coronary artery calcium score (CACS) had the highest correlation with MACE.

CONCLUSION

Compared to the conventional scoring system, ML models using CCTA scans show improved prognostic prediction for MACE. Anatomical features were more important than clinical characteristics.

Impact of lipid-lowering therapies on cardiovascular outcomes according to coronary artery calcium score. A systematic review and meta-analysis

INTRODUCTION AND OBJECTIVES

Coronary artery calcium (CAC) score improves the accuracy of risk stratification for atherosclerotic cardiovascular disease (ASCVD) events compared with traditional cardiovascular risk factors. We evaluated the interaction of coronary atherosclerotic burden as determined by the CAC score with the prognostic benefit of lipid-lowering therapies in the primary prevention setting.

METHODS

We reviewed the MEDLINE, EMBASE, and Cochrane databases for studies including individuals without a previous ASCVD event who underwent CAC score assessment and for whom lipid-lowering therapy status stratified by CAC values was available. The primary outcome was ASCVD. The pooled effect of lipid-lowering therapy on outcomes stratified by CAC groups (0, 1-100,> 100) was evaluated using a random effects model.

RESULTS

Five studies (1 randomized, 2 prospective cohort, 2 retrospective) were included encompassing 35 640 individuals (female 38.1%) with a median age of 62.2 [range, 49.6-68.9] years, low-density lipoprotein cholesterol level of 128 (114-146) mg/dL, and follow-up of 4.3 (2.3-11.1) years. ASCVD occurrence increased steadily across growing CAC strata, both in patients with and without lipid-lowering therapy. Comparing patients with (34.9%) and without (65.1%) treatment exposure, lipid-lowering therapy was associated with reduced occurrence of ASCVD in patients with CAC> 100 (OR, 0.70; 95%CI, 0.53-0.92), but not in patients with CAC 1-100 or CAC 0. Results were consistent when only adjusted data were pooled.

CONCLUSIONS

Among individuals without a previous ASCVD, a CAC score> 100 identifies individuals most likely to benefit from lipid-lowering therapy, while undetectable CAC suggests no treatment benefit.

Cardiac CT angiography in current practice: An American society for preventive cardiology clinical practice statement✰

In this clinical practice statement, we represent a summary of the current evidence and clinical applications of cardiac computed tomography (CT) in evaluation of coronary artery disease (CAD), from an expert panel organized by the American Society for Preventive Cardiology (ASPC), and appraises the current use and indications of cardiac CT in clinical practice. Cardiac CT is emerging as a front line non-invasive diagnostic test for CAD, with evidence supporting the clinical utility of cardiac CT in diagnosis and prevention. CCTA offers several advantages beyond other testing modalities, due to its ability to identify and characterize coronary stenosis severity and pathophysiological changes in coronary atherosclerosis and stenosis, aiding in early diagnosis, prognosis and management of CAD. This document further explores the emerging applications of CCTA based on functional assessment using CT derived fractional flow reserve, peri‑coronary inflammation and artificial intelligence (AI) that can provide personalized risk assessment and guide targeted treatment. We sought to provide an expert consensus based on the latest evidence and best available clinical practice guidelines regarding the role of CCTA as an essential tool in cardiovascular prevention - applicable to risk assessment and early diagnosis and management, noting potential areas for future investigation.

Current Progress of Studies of Coronary CT for Risk Prediction of Major Adverse Cardiovascular Event (MACE)

Cardiovascular disease is a serious threat to human health, and early risk prediction of major adverse cardiovascular event in people suspected of coronary heart disease can help guide prevention and clinical decisions. Coronary computed tomography (CT) is a useful imaging tool for evaluation of coronary heart disease, and its ability to reflect coronary atherosclerosis shows potential value for risk prediction. In recent years, various new techniques and studies of coronary CT have emerged for risk prediction of major adverse cardiovascular event in people suspected of coronary heart disease. We will review the background and current study advances of using coronary artery calcium score, coronary CT angiography, and artificial intelligence in this field.

Risk Stratification With the Use of Coronary Computed Tomographic Angiography in Patients With Nonobstructive Coronary Artery Disease

OBJECTIVES

The purpose of this study was to develop a risk prediction model for patients with nonobstructive CAD.

BACKGROUND

Among stable chest pain patients, most cardiovascular (CV) events occur in those with nonobstructive coronary artery disease (CAD). Thus, developing tailored risk prediction approaches in this group of patients, including CV risk factors and CAD characteristics, is needed.

METHODS

In PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) computed tomographic angiography patients, a core laboratory assessed prevalence of CAD (nonobstructive 1% to 49% left main or 1% to 69% stenosis any coronary artery), degree of stenosis (minimal: 1% to 29%; mild: 30% to 49%; or moderate: 50% to 69%), high-risk plaque (HRP) features (positive remodeling, low-attenuation plaque, and napkin-ring sign), segment involvement score (SIS), and coronary artery calcium (CAC). The primary end point was an adjudicated composite of unstable angina pectoris, nonfatal myocardial infarction, and death. Cox regression analysis determined independent predictors in nonobstructive CAD.

RESULTS

Of 2,890 patients (age 61.7 years, 46% women) with any CAD, 90.4% (n = 2,614) had nonobstructive CAD (mean age 61.6 yrs, 46% women, atherosclerotic cardiovascular disease [ASCVD] risk 16.2%). Composite events were independently predicted by ASCVD risk (hazard ratio [HR]: 1.03; p = 0.001), degree of stenosis (30% to 69%; HR: 1.91; p = 0.011), and presence of ≥2 HRP features (HR: 2.40; p = 0.008). Addition of ≥2 HRP features to: 1) ASCVD and CAC; 2) ASCVD and SIS; or 3) ASCVD and degree of stenosis resulted in a statistically significant improvement in model fit (p = 0.0036; p = 0.0176; and p = 0.0318; respectively). Patients with ASCVD ≥7.5%, any HRP, and mild/moderate stenosis had significantly higher event rates than those who did not meet those criteria (3.0% vs. 6.2%; p = 0.007).

CONCLUSIONS

Advanced coronary plaque features have incremental value over total plaque burden for the discrimination of clinical events in low-risk stable chest pain patients with nonobstructive CAD. This may be a first step to improve prevention in this cohort with the highest absolute risk for CV events.

The year 2020 in the European Heart Journal - Cardiovascular Imaging: part I

The European Heart Journal - Cardiovascular Imaging was launched in 2012 and has during these 9 years become one of the leading multimodality cardiovascular imaging journals. The journal is currently ranked as number 20 among all cardiovascular journals. Our journal is well established as one of the top cardiovascular journals and is the most important cardiovascular imaging journal in Europe. The most important studies published in our Journal in 2020 will be highlighted in two reports. Part I of the review will focus on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.

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.

Added prognostic value of plaque burden to computed tomography angiography and myocardial perfusion imaging

BACKGROUND AND AIMS

Cardiac computed tomographic angiography (CCTA) - derived measures of coronary artery disease (CAD) burden have been shown to independently predict incident cardiovascular events. We aimed to compare the added prognostic value of plaque burden to CCTA anatomic assessment and single photon emission computed tomography (SPECT) physiologic assessment in a cohort with high prevalence of risk factors undergoing both tests.

METHODS

Consecutive patients who underwent clinically indicated CCTA and SPECT myocardial imaging for suspected CAD were included. Stenosis severity and segment involvement score (SIS - number of segments with plaque irrespective of stenosis) were determined from CCTA, and presence of ischemia was determined from SPECT. Patients were followed for major adverse cardiovascular events (MACE, inclusive of all-cause death, non-fatal myocardial infarction, and percutaneous coronary intervention or coronary artery bypass grafting 90-days after imaging test.) RESULTS: A total of 956 patients were included (mean age 61.1 ± 14.2 years, 54% men, 89% hypertension, 81% diabetes, 84% dyslipidemia). Obstructive stenosis (left main ≥50%, all other coronary segments ≥70%) and ischemia were observed in a similar number of patients (14%). In multivariable Cox regression models, SIS significantly predicted outcomes and improved risk discrimination in models with CCTA obstructive stenosis (HR 1.15, p ≤ 0.001; Harrel's C 0.74, p = 0.008) and SPECT ischemia (HR 1.14, p < 0.001; Harrel's C 0.76, p = 0.019).

CONCLUSIONS

Our results suggest that in patients with suspected CAD and a high prevalence of risk-factors, plaque burden adds incremental prognostic value over established CCTA and SPECT measures to predict incident cardiovascular outcomes.

Impact of atherosclerotic extent on clinical outcome for diabetic patients with non-obstructive coronary artery disease

Background and aims

The prognostic impact of non-obstructive coronary artery disease (CAD) has long been underestimated due to its mild stenosis (<50% stenosis). We aim to investigate the prognostic value of atherosclerotic extent in DM patients with non-obstructive CAD.

Methods

The analysis was based on a single center cohort of DM patients referred for coronary computed tomography angiography (CCTA) due to suspect CAD in 2015-2017. Based on coronary stenosis combined with segment involvement score (SIS), the study population were divided into four groups: normal (0% stenosis), non-obstructive SIS<3, non-obstructive SIS≥3 and obstructive (≥50% stenosis). The intra-class correlation (ICC) was used to test the inter-and intra-reviewer agreement. Multivariate Cox model and Kaplan-Meier method were used to evaluate the effect size of atherosclerotic extent on the prognosis.

Results

In total, 1241 patients (age 60.2 ± 10.4 years, 54.1% male) were included, of which 50.2% were non-obstructive. During a median follow-up of 2.6 years, 131 MACEs (10.6%) were adjudicated, including 17 cardiovascular deaths, 28 non-fatal myocardial infarctions, 64 unstable anginas requiring hospitalization and 22 strokes. Incremental event rates could be observed across the four groups. After adjustment for age, gender, hyperlipidemia and presence of high-risk plaque, Hazard Ratio (HR) for non-obstructive SIS<3, non-obstructive SIS≥3 and the obstructive group was 1.84 (95%CI: 0.70-4.79), 3.71 (95%CI: 1.37-10.00) and 5.46 (95%CI: 2.18-13.69), respectively. Compared with non-obstructive SIS<3, non-obstructive SIS≥3 showed a significantly higher risk (HR:2.02 95%CI:1.11-3.68, p = 0.021). Similar results were demonstrated when Leiden risk score was used for sensitivity analysis.

Conclusion

In DM patients with non-obstructive CAD, atherosclerotic extent was associated with higher risk of major adverse cardiac events at long-term follow-up. Efforts should be made to determine risk stratification for the management of DM patients with non-obstructive CAD.

Impact of clinical and subclinical coronary artery disease as assessed by coronary artery calcium in COVID-19

BACKGROUND AND AIMS

The potential impact of coronary atherosclerosis, as detected by coronary artery calcium, on clinical outcomes in COVID-19 patients remains unsettled. We aimed to evaluate the prognostic impact of clinical and subclinical coronary artery disease (CAD), as assessed by coronary artery calcium score (CAC), in a large, unselected population of hospitalized COVID-19 patients undergoing non-gated chest computed tomography (CT) for clinical practice.

METHODS

SARS-CoV 2 positive patients from the multicenter (16 Italian hospitals), retrospective observational SCORE COVID-19 (calcium score for COVID-19 Risk Evaluation) registry were stratified in three groups: (a) "clinical CAD" (prior revascularization history), (b) "subclinical CAD" (CAC >0), (c) "No CAD" (CAC = 0). Primary endpoint was in-hospital mortality and the secondary endpoint was a composite of myocardial infarction and cerebrovascular accident (MI/CVA).

RESULTS

Amongst 1625 patients (male 67.2%, median age 69 [interquartile range 58-77] years), 31%, 57.8% and 11.1% had no, subclinical and clinical CAD, respectively. Increasing rates of in-hospital mortality (11.3% vs. 27.3% vs. 39.8%, p < 0.001) and MI/CVA events (2.3% vs. 3.8% vs. 11.9%, p < 0.001) were observed for patients with no CAD vs. subclinical CAD vs clinical CAD, respectively. The association with in-hospital mortality was independent of in-study outcome predictors (age, peripheral artery disease, active cancer, hemoglobin, C-reactive protein, LDH, aerated lung volume): subclinical CAD vs. No CAD: adjusted hazard ratio (adj-HR) 2.86 (95% confidence interval [CI] 1.14-7.17, p=0.025); clinical CAD vs. No CAD: adj-HR 3.74 (95% CI 1.21-11.60, p=0.022). Among patients with subclinical CAD, increasing CAC burden was associated with higher rates of in-hospital mortality (20.5% vs. 27.9% vs. 38.7% for patients with CAC score thresholds≤100, 101-400 and > 400, respectively, p < 0.001). The adj-HR per 50 points increase in CAC score 1.007 (95%CI 1.001-1.013, p=0.016). Cardiovascular risk factors were not independent predictors of in-hospital mortality when CAD presence and extent were taken into account.

CONCLUSIONS

The presence and extent of CAD are associated with in-hospital mortality and MI/CVA among hospitalized patients with COVID-19 disease and they appear to be a better prognostic gauge as compared to a clinical cardiovascular risk assessment.

CT ​EvaLuation ​by ​ARtificial ​Intelligence ​For ​Atherosclerosis, Stenosis and Vascular ​MorphologY ​(CLARIFY): ​A ​Multi-center, international study

BACKGROUND

Atherosclerosis evaluation by coronary computed tomography angiography (CCTA) is promising for coronary artery disease (CAD) risk stratification, but time consuming and requires high expertise. Artificial Intelligence (AI) applied to CCTA for comprehensive CAD assessment may overcome these limitations. We hypothesized AI aided analysis allows for rapid, accurate evaluation of vessel morphology and stenosis.

METHODS

This was a multi-site study of 232 patients undergoing CCTA. Studies were analyzed by FDA-cleared software service that performs AI-driven coronary artery segmentation and labeling, lumen and vessel wall determination, plaque quantification and characterization with comparison to ground truth of consensus by three L3 readers. CCTAs were analyzed for: % maximal diameter stenosis, plaque volume and composition, presence of high-risk plaque and Coronary Artery Disease Reporting & Data System (CAD-RADS) category.

RESULTS

AI performance was excellent for accuracy, sensitivity, specificity, positive predictive value and negative predictive value as follows: >70% stenosis: 99.7%, 90.9%, 99.8%, 93.3%, 99.9%, respectively; >50% stenosis: 94.8%, 80.0%, 97.0, 80.0%, 97.0%, respectively. Bland-Altman plots depict agreement between expert reader and AI determined maximal diameter stenosis for per-vessel (mean difference -0.8%; 95% CI 13.8% to -15.3%) and per-patient (mean difference -2.3%; 95% CI 15.8% to -20.4%). L3 and AI agreed within one CAD-RADS category in 228/232 (98.3%) exams per-patient and 923/924 (99.9%) vessels on a per-vessel basis. There was a wide range of atherosclerosis in the coronary artery territories assessed by AI when stratified by CAD-RADS distribution.

CONCLUSIONS

AI-aided approach to CCTA interpretation determines coronary stenosis and CAD-RADS category in close agreement with consensus of L3 expert readers. There was a wide range of atherosclerosis identified through AI.

Clinical Implications of Monogenic Versus Polygenic Hypercholesterolemia: Long-Term Response to Treatment, Coronary Atherosclerosis Burden, and Cardiovascular Events

Background

Familial hypercholesterolemia (FH) may arise from deleterious monogenic variants in FH‐causing genes as well as from a polygenic cause. We evaluated the relationships between monogenic FH and polygenic hypercholesterolemia in influencing the long‐term response to therapy and the risk of atherosclerosis.

Methods and Results

A cohort of 370 patients with clinically diagnosed FH were screened for monogenic mutations and a low‐density lipoprotein‐rising genetic risk score >0.69 to identify polygenic cause. Medical records were reviewed to estimate the response to lipid‐lowering therapies and the occurrence of major atherosclerotic cardiovascular events during a median follow‐up of 31.0 months. A subgroup of patients (n=119) also underwent coronary computed tomographic angiography for the evaluation of coronary artery calcium score and severity of coronary stenosis as compared with 135 controls. Two hundred nine (56.5%) patients with hypercholesterolemia were classified as monogenic (FH/M+), 89 (24.1%) as polygenic, and 72 (19.5%) genetically undefined (FH/M−). The response to lipid‐lowering therapy was poorest in monogenic, whereas it was comparable in patients with polygenic hypercholesterolemia and genetically undetermined. Mean coronary artery calcium score and the prevalence of coronary artery calcium >100 units were significantly higher in FH/M+ as compared with both FH/M− and controls. Finally, after adjustments for confounders, we observed a 5‐fold higher risk of incident major atherosclerotic cardiovascular events in FH/M+ (hazard ratio, 4.8; 95% CI, 1.06–21.36; P_adj=0.041).

Conclusions

Monogenic cause of FH is associated with lower response to conventional cholesterol‐lowering therapies as well as with increased burden of coronary atherosclerosis and risk of atherosclerotic‐related events. Genetic testing for hypercholesterolemia is helpful in providing important prognostic information.

Artificial Intelligence to Assist in Exclusion of Coronary Atherosclerosis During CCTA Evaluation of Chest Pain in the Emergency Department: Preparing an Application for Real-world Use

Coronary computed tomography angiography (CCTA) evaluation of chest pain patients in an emergency department (ED) is considered appropriate. While a "negative" CCTA interpretation supports direct patient discharge from an ED, labor-intensive analyses are required, with accuracy in jeopardy from distractions. We describe the development of an artificial intelligence (AI) algorithm and workflow for assisting qualified interpreting physicians in CCTA screening for total absence of coronary atherosclerosis. The two-phase approach consisted of (1) phase 1-development and preliminary testing of an algorithm for vessel-centerline extraction classification in a balanced study population (n = 500 with 50% disease prevalence) derived by retrospective random case selection, and (2) phase 2-simulated clinical Trialing of developed algorithm on a per-case (entire coronary artery tree) basis in a more "real-world" study population (n = 100 with 28% disease prevalence) from an ED chest pain series. This allowed pre-deployment evaluation of the AI-based CCTA screening application which provides vessel-by-vessel graphic display of algorithm inference results integrated into a clinically capable viewer. Algorithm performance evaluation used area under the receiver operating characteristic curve (AUC-ROC); confusion matrices reflected ground truth vs AI determinations. The vessel-based algorithm demonstrated strong performance with AUC-ROC = 0.96. In both phase 1 and phase 2, independent of disease prevalence differences, negative predictive values at the case level were very high at 95%. The rate of completion of the algorithm workflow process (96% with inference results in 55-80 s) in phase 2 depended on adequate image quality. There is potential for this AI application to assist in CCTA interpretation to help extricate atherosclerosis from chest pain presentations.

The evolving role of coronary CT angiography in Acute Coronary Syndromes

In the United States, non-obstructive coronary disease has been on the rise, and each year, nearly one million adults suffer myocardial infarction, 70% of which are non-ST-segment elevation myocardial infarction (NSTEMI). In addition, approximately 15% of patients suffering NSTEMI will have subsequent readmission for a recurrent acute coronary syndrome (ACS). While invasive angiography remains the standard of care in the diagnostic and therapeutic approach to these patients, these methods have limitations that include procedural complications, uncertain specificity in diagnosis of the culprit lesion in patients with multi-vessel coronary artery disease (CAD), and challenges in following coronary disease over time. The role of coronary computed tomography angiography (CCTA) for evaluating patients with both stable and acute chest pain has seen a paramount upshift in the last decade. This paper reviews the established role of CCTA for the rapid exclusion of obstructive plaque in troponin negative acute chest pain, while exploring opportunities to address challenges in the current approach to evaluating NSTEMI.

Segmentation and Classification of Heart Angiographic Images Using Machine Learning Techniques

Heart angiography is a test in which the concerned medical specialist identifies the abnormality in heart vessels. This type of diagnosis takes a lot of time by the concerned physician. In our proposed method, we segmented the interested regions of heart vessels and then classified. Segmentation and classification of heart angiography provides significant information for the physician as well as patient. Contradictorily, in the mention domain of heart angiography, the charge is prone to error, phase overwhelming, and thought-provoking task for the physician (heart specialist). An automatic segmentation and classification of heart blood vessels descriptions can improve the truthfulness and speed up the finding of heart illnesses. In this work, we recommend a computer-assisted conclusion arrangement for the localization of human heart blood vessels within heart angiographic imageries by using multiclass ensemble classification mechanism. In the proposed work, the heart blood vessels will be first segmented, and the various features according to accuracy have been extracted. Low-level features such as texture, statistical, and geometrical features were extracted in human heart blood vessels. At last, in the proposed framework, heart blood vessels have been categorized in their four respective classes including normal, block, narrow, and blood flow-reduced vessels. The proposed approach has achieved best result which provides very useful, easy, accurate, and time-saving environment to cardiologists for the diagnosis of heart-related diseases.

Prognostic Value of Atherosclerotic Extent in Diabetic Patients with Nonobstructive Coronary Artery Disease

METHODS AND RESULTS

813 DM patients (mean age 58.9 ± 9.9 years, 48.1% male) referred for CCTA due to suspected CAD in 2015-2017 were consecutively included. During a median follow-up of 31.77 months, 50 major adverse cardiovascular events (MACEs) (6.15%) were experienced, including 2 cardiovascular deaths, 14 nonfatal myocardial infarctions, 27 unstable anginas requiring hospitalization, and 7 strokes. Three groups were defined based on coronary stenosis combined with Leiden score as normal, nonobstructive Leiden < 5, and nonobstructive Leiden ≥ 5. Cox models were used to assess the prognosis of plaque burden within these groups. An incremental incidence of MACE rates was observed. After adjustment for age, gender, and presence of high-risk plaque, the group of Leiden ≥ 5 showed a higher risk than Leiden < 5 (HR: 1.88, 95% CI: 1.03-3.42, p = 0.039). Similar results were observed when segment involvement score (SIS) was used for sensitivity analysis.

CONCLUSION

Atherosclerotic extent was associated with the prognosis of DM patients with nonobstructive coronary artery disease, highlighting the importance of better risk stratification and management.

The Vulnerable Plaque: Recent Advances in Computed Tomography Imaging to Identify the Vulnerable Patient

PURPOSE OF REVIEW

This review aims to summarize the role of coronary computed tomography plaque analysis in identifying high-risk patients and plaques.

RECENT FINDINGS

In this review, we will describe the histopathological features of a vulnerable plaque as well as the coronary computed tomography characteristics including spotty calcification, low-attenuation fatty core, positive remodeling, and thin fibrous cap. We will also review several studies that assessed features of a vulnerable plaque on non-invasive imaging and evaluated them as risk predictors of future acute coronary events. Multiple recent studies suggested that coronary computed tomography angiography can accurately identify high-risk features of plaque that will predict future events.

Association of plaque calcification pattern and attenuation with instability features and coronary stenosis and calcification grade

BACKGROUND AND AIMS

Coronary computed tomography (CT) allows calculating coronary artery calcium score (CACS). However, other CT features might be more strongly related to plaque vulnerability and risk of future coronary events. This study investigated the association of plaque calcification pattern and attenuation with plaque instability features, coronary artery disease (CAD) grade and CACS.

METHODS

One-hundred patients with coronary stenosis associated with calcified plaques were considered for this analysis. CACS, CAD grade, calcification pattern and attenuation, features of plaque instability, and epicardial adipose tissue (EAT) thickness and attenuation were assessed with non-contrast and contrast-enhanced CT angiography.

RESULTS

Of 373 calcified plaques, 131 were responsible for the highest degree of coronary stenosis (1.31 ± 0.53 per patient). Participants were stratified according to the features of the highest-grade lesion(s) into patients with large (35%), spotty (52%) or mixed (13%) calcification pattern and tertiles of plaque calcification attenuation (using the mean value for multiple lesions). Patients with large calcification pattern or higher plaque calcification attenuation had higher stenosis and CACS grade (and EAT attenuation), but lower plaque instability score, whereas those with spotty calcification pattern or lower plaque calcification attenuation had lower stenosis and CACS grade (and EAT attenuation), but higher plaque instability score. Among the instability features, low attenuation and napkin-ring sign, but not positive remodeling, were associated with a spotty pattern and a lower calcification attenuation.

CONCLUSIONS

Both the pattern and attenuation of calcification should be considered, in addition to CACS, for risk stratification of heavily calcified high-risk patients with non-critical coronary stenosis.

The Quantification of Total Coronary Atheroma Burden – A Major Step Forward

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