Total coronary atherosclerotic plaque burden assessment by CT angiography for detecting obstructive coronary artery disease associated with myocardial perfusion abnormalities

Improved diagnostic accuracy of vessel-specific myocardial ischemia by coronary computed tomography angiography (CCTA)

BACKGROUND

Discrepancies between stenosis severity assessed at coronary computed tomography angiography (CCTA) and ischemia might depend on vessel type. Coronary plaque features are associated with ischemia. Thus, we evaluated the vessel-specific correlation of CCTA-derived diameter stenosis (DS) and invasive fractional flow reserve (FFR) and explored whether integrating morphological plaque features stratified by vessel might increase the predictive yield in identifying vessel-specific ischemia.

METHODS

Observational cohort study including patients undergoing CCTA for suspected coronary artery disease, with at least one vessel with DS ​≥ ​50 ​% at CCTA, undergoing invasive coronary angiography and FFR. Plaque analysis was performed using validated semi-automated software. Coronary vessels were stratified in left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA). Per vessel independent predictors of ischemia among CCTA-derived anatomical and morphologic plaque features were tested at univariable and multivariable logistic regression analysis. The best cut-off to predict ischemia was determined by Youden's index. Ischemia was defined by FFR≤0.80.

RESULTS

The study population consisted of 192 patients, of whom 224 vessels (61 ​% LAD, 19 ​% LCX, 20 ​% RCA) had lesions with DS ​≥ ​50 ​% interrogated by FFR. Despite similar DS, the rate of FFR≤0.80 was higher in the LAD compared to LCX and RCA (67.2 ​% vs 43.2 ​% and 44.2 ​%, respectively, p ​= ​0.018). A significant correlation between DS and FFR was observed only in LAD (p ​= ​0.003). At multivariable analysis stratified by vessel, the vessel-specific independent predictors of positive FFR were percent atheroma volume (threshold>17 ​%) for LAD, non-calcified plaque volume (threshold >130 ​mm3) for LCX, and lumen volume (threshold <844 ​mm3) for RCA. Integrating DS and vessel-specific morphological plaque features significantly increased the predictive yield for ischemia compared to DS alone (AUC ranging from 0.51 to 0.63 to 0.76-0.80).

CONCLUSIONS

Integrating DS and vessel-specific morphological plaque features significantly increased the predictive yield for vessel-specific ischemia compared to DS alone, potentially improving patients' referral to the catheterization laboratory.

Atherosclerosis evaluation and cardiovascular risk estimation using coronary computed tomography angiography

Clinical risk scores based on traditional risk factors of atherosclerosis correlate imprecisely to an individual's complex pathophysiological predisposition to atherosclerosis and provide limited accuracy for predicting major adverse cardiovascular events (MACE). Over the past two decades, computed tomography scanners and techniques for coronary computed tomography angiography (CCTA) analysis have substantially improved, enabling more precise atherosclerotic plaque quantification and characterization. The accuracy of CCTA for quantifying stenosis and atherosclerosis has been validated in numerous multicentre studies and has shown consistent incremental prognostic value for MACE over the clinical risk spectrum in different populations. Serial CCTA studies have advanced our understanding of vascular biology and atherosclerotic disease progression. The direct disease visualization of CCTA has the potential to be used synergistically with indirect markers of risk to significantly improve prevention of MACE, pending large-scale randomized evaluation.

Effects of a Tai Chi rehabilitation program implemented using a hybrid online and offline mode on oxidative stress and inflammatory responses in patients with coronary heart disease: a randomized controlled trial

Background

Coronary heart disease (CHD) is the leading cause of death in both developed and many developing countries. Exercise training is a fundamental component of cardiac rehabilitation programs for patients with CHD. This study aims to investigate the effects of a Tai Chi rehabilitation program, which is provided through a hybrid online and offline mode, on oxidative stress and inflammatory responses in patients with CHD.

Methods

A total of 34 patients with coronary heart disease were randomly assigned to two groups: an experiment group (n = 14, age 62.07 ± 9.076 years) and a control group (n = 20, age 61.90 ± 9.700 years). The experiment group underwent a 12-week Tai Chi cardiac rehabilitation program (TCCRP), while the control group followed a conventional exercise rehabilitation program (CERP) consisting of 1-h sessions, 3 times per week, for a total of 36 sessions. Participants were studied at baseline and post-intervention. The main assessments include the levels of Malondialdehyde (MDA), Superoxide dismutase (SOD), Tumor necrosis factor (TNF-α) and Interleukin-10 (IL - 10) in blood samples. Pearson correlation analysis was used, and the differences between the two groups were subsequently tested using two-way repeated ANOVA. Statistical significance was defined as a two-sided p-value of <0.05.

Results

The key finding of the study reveals that MDA was significantly reduced by 1.027 nmoL/mL. Additionally, the TCCRP showed significant improvements in SOD and IL-10, with values of 10.110 U/mL and 2.441 pg./mL, respectively. Notably, a significant positive correlation was found between SOD and IL-10 (r = 0.689, p = 0.006), while MDA showed a significant positive correlation with TNF-a (r = 0.542, p = 0.045). In contrast, the ECRP group only showed a significant improvement in SOD.

Conclusion

The study conducted a 12-week program on TCCRP, which utilized a hybrid online and offline model for individuals with coronary heart disease. The program showed promising results in alleviating oxidative stress and inflammation, possibly by regulating the balance between oxidative and antioxidative factors, as well as pro-inflammatory and anti-inflammatory factors.

Coronary artery disease grading by cardiac CT for predicting outcome in patients with stable angina

BACKGROUND

The coronary atheroma burden drives major adverse cardiovascular events (MACE) in patients with suspected coronary heart disease (CHD). However, a consensus on how to grade disease burden for effective risk stratification is lacking. The purpose of this study was to compare the effectiveness of common CHD grading tools to risk stratify symptomatic patients.

METHODS

We analyzed the 5-year outcome of 381 prospectively enrolled patients in the CORE320 international, multicenter study using baseline clinical and cardiac computer-tomography (CT) imaging characteristics, including coronary artery calcium score (CACS), percent atheroma volume, "high-risk" plaque, disease severity grading using the CAD-RADS, and two simplified CAD staging systems. We applied Cox proportional hazard models and area under the curve (AUC) analysis to predict MACE or hard MACE, defined as death, myocardial infarction, or stroke. Analyses were stratified by a history of CHD. Additional forward selection analysis was performed to evaluate incremental value of metrics.

RESULTS

Clinical characteristics were the strongest predictors of MACE in the overall cohort. In patients without history of CHD, CACS remained the only independent predictor of MACE yielding an AUC of 73 (CI 67-79) vs. 64 (CI 57-70) for clinical characteristics. Noncalcified plaque volume did not add prognostic value. Simple CHD grading schemes yielded similar risk stratification as the CAD-RADS classification. Forward selection analysis confirmed prominent role of CACS and revealed usefulness of functional testing in subgroup with known CHD.

CONCLUSION

In patients referred for invasive angiography, a history of CHD was the strongest predictor of MACE. In patients without history of CHD, a coronary calcium score yielded at least equal risk stratification vs. more complex CHD grading.

High-quality annotations for deep learning enabled plaque analysis in SCAPIS cardiac computed tomography angiography

Background

Plaque analysis with coronary computed tomography angiography (CCTA) is a promising tool to identify high risk of future coronary events. The analysis process is time-consuming, and requires highly trained readers. Deep learning models have proved to excel at similar tasks, however, training these models requires large sets of expert-annotated training data. The aims of this study were to generate a large, high-quality annotated CCTA dataset derived from Swedish CArdioPulmonary BioImage Study (SCAPIS), report the reproducibility of the annotation core lab and describe the plaque characteristics and their association with established risk factors.

Methods and results

The coronary artery tree was manually segmented using semi-automatic software by four primary and one senior secondary reader. A randomly selected sample of 469 subjects, all with coronary plaques and stratified for cardiovascular risk using the Systematic Coronary Risk Evaluation (SCORE), were analyzed. The reproducibility study (n = 78) showed an agreement for plaque detection of 0.91 (0.84-0.97). The mean percentage difference for plaque volumes was -0.6% the mean absolute percentage difference 19.4% (CV 13.7%, ICC 0.94). There was a positive correlation between SCORE and total plaque volume (rho = 0.30, p < 0.001) and total low attenuation plaque volume (rho = 0.29, p < 0.001).

Conclusions

We have generated a CCTA dataset with high-quality plaque annotations showing good reproducibility and an expected correlation between plaque features and cardiovascular risk. The stratified data sampling has enriched high-risk plaques making the data well suited as training, validation and test data for a fully automatic analysis tool based on deep learning.

Endothelial shear stress computed from coronary computed tomography angiography: A direct comparison to intravascular ultrasound

INTRODUCTION

Intravascular ultrasound (IVUS) studies have shown that biomechanical variables, particularly endothelial shear stress (ESS), add synergistic prognostic insight when combined with anatomic high-risk plaque features. Non-invasive risk assessment of coronary plaques with coronary computed tomography angiography (CCTA) would be helpful to enable broad population risk-screening.

AIM

To compare the accuracy of ESS computation of local ESS metrics by CCTA vs IVUS imaging.

METHODS

We analyzed 59 patients from a registry of patients who underwent both IVUS and CCTA for suspected CAD. CCTA images were acquired using either a 64- or 256-slice scanner. Lumen, vessel, and plaque areas were segmented from both IVUS and CCTA (59 arteries, 686 3-mm segments). Images were co-registered and used to generate a 3-D arterial reconstruction, and local ESS distribution was assessed by computational fluid dynamics (CFD) and reported in consecutive 3-mm segments.

RESULTS

Anatomical plaque characteristics (vessel, lumen, plaque area and minimal luminal area [MLA] per artery) were correlated when measured with IVUS and CCTA: 12.7 ​± ​4.3 vs 10.7 ​± ​4.5 ​mm2, r ​= ​0.63; 6.8 ​± ​2.7 vs 5.6 ​± ​2.7 ​mm2, r ​= ​0.43; 5.9 ​± ​2.9 vs 5.1 ​± ​3.2 ​mm2, r ​= ​0.52; 4.5 ​± ​1.3 vs 4.1 ​± ​1.5 ​mm2, r ​= ​0.67 respectively. ESS metrics of local minimal, maximal, and average ESS were also moderately correlated when measured with IVUS and CCTA (2.0 ​± ​1.4 vs 2.5 ​± ​2.6 ​Pa, r ​= ​0.28; 3.3 ​± ​1.6 vs 4.2 ​± ​3.6 ​Pa, r ​= ​0.42; 2.6 ​± ​1.5 vs 3.3 ​± ​3.0 ​Pa, r ​= ​0.35, respectively). CCTA-based computation accurately identified the spatial localization of local ESS heterogeneity compared to IVUS, with Bland-Altman analyses indicating that the absolute ESS differences between the two CCTA methods were pathobiologically minor.

CONCLUSION

Local ESS evaluation by CCTA is possible and similar to IVUS; and is useful for identifying local flow patterns that are relevant to plaque development, progression, and destabilization.

m6A regulator-mediated RNA methylation modification patterns are involved in the regulation of the immune microenvironment in ischaemic cardiomyopathy

The role of RNA N6-methyladenosine (m6A) modification in the regulation of the immune microenvironment in ischaemic cardiomyopathy (ICM) remains largely unclear. This study first identified differential m6A regulators between ICM and healthy samples, and then systematically evaluated the effects of m6A modification on the characteristics of the immune microenvironment in ICM, including the infiltration of immune cells, the human leukocyte antigen (HLA) gene, and HALLMARKS pathways. A total of seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15 and YTHDF3, were identified using a random forest classifier. A diagnostic nomogram based on these seven key m6A regulators could effectively distinguish patients with ICM from healthy subjects. We further identified two distinct m6A modification patterns (m6A cluster-A and m6A cluster-B) that are mediated by these seven regulators. Meanwhile, we also noted that one m6A regulator, WTAP, was gradually upregulated, while the others were gradually downregulated in the m6A cluster-A vs. m6A cluster-B vs. healthy subjects. In addition, we observed that the degree of infiltration of the activated dendritic cells, macrophages, natural killer (NK) T cells, and type-17 T helper (Th17) cells gradually increased in m6A cluster-A vs. m6A cluster-B vs. healthy subjects. Furthermore, m6A regulators, including FTO, YTHDC1, YTHDF3, FMR1, ZC3H13, and RBM15 were significantly negatively correlated with the above-mentioned immune cells. Additionally, several differential HLA genes and HALLMARKS signalling pathways between the m6A cluster-A and m6A cluster-B groups were also identified. These results suggest that m6A modification plays a key role in the complexity and diversity of the immune microenvironment in ICM, and seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15, and YTHDF3, may be novel biomarkers for the accurate diagnosis of ICM. Immunotyping of patients with ICM will help to develop immunotherapy strategies with a higher level of accuracy for patients with a significant immune response.

Identifying patterns of immune related cells and genes in the peripheral blood of acute myocardial infarction patients using a small cohort

Background

The immune system plays a vital role in the pathophysiology of acute myocardial infarction (AMI). However, the exact immune related mechanism is still unclear. This research study aimed to identify key immune-related genes involved in AMI.

Methods

CIBERSORT, a deconvolution algorithm, was used to determine the proportions of 22 subsets of immune cells in blood samples. The weighted gene co-expression network analysis (WGCNA) was used to identify key modules that are significantly associated with AMI. Then, CIBERSORT combined with WGCNA were used to identify key immune-modules. The protein–protein interaction (PPI) network was constructed and Molecular Complex Detection (MCODE) combined with cytoHubba plugins were used to identify key immune-related genes that may play an important role in the occurrence and progression of AMI.

Results

The CIBERSORT results suggested that there was a decrease in the infiltration of CD8 + T cells, gamma delta (γδ) T cells, and resting mast cells, along with an increase in the infiltration of neutrophils and M0 macrophages in AMI patients. Then, two modules (midnightblue and lightyellow) that were significantly correlated with AMI were identified, and the salmon module was found to be significantly associated with memory B cells. Gene enrichment analysis indicated that the 1,171 genes included in the salmon module are mainly involved in immune-related biological processes. MCODE analysis was used to identify four different MCODE complexes in the salmon module, while four hub genes (EEF1B2, RAC2, SPI1, and ITGAM) were found to be significantly correlated with AMI. The correlation analysis between the key genes and infiltrating immune cells showed that SPI1 and ITGAM were positively associated with neutrophils and M0 macrophages, while they were negatively associated with CD8 + T cells, γδ T cells, regulatory T cells (Tregs), and resting mast cells. The RT-qPCR validation results found that the expression of the ITGAM and SPI1 genes were significantly elevated in the AMI samples compared with the samples from healthy individuals, and the ROC curve analysis showed that ITGAM and SPI1 had a high diagnostic efficiency for the recognition of AMI.

Conclusions

Immune cell infiltration plays a crucial role in the occurrence and development of AMI. ITGAM and SPI1 are key immune-related genes that are potential novel targets for the prevention and treatment of AMI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03517-1.

A novel lncRNA-miRNA-mRNA triple network identifies lncRNA XIST as a biomarker for acute myocardial infarction

Despite the well-established role of long non-coding RNAs (lncRNAs) across various biological processes, their mechanisms in acute myocardial infarction (AMI) are not fully elucidated. The GSE34198 dataset from the Gene Expression Omnibus (GEO) database, which comprised 49 specimens from individuals with AMI and 47 specimens from controls, was extracted and analysed using the weighted gene co-expression network analysis (WGCNA) package. Twenty-seven key genes were identified through a combination of the degree and gene significance (GS) values, and the CDC42 (degree = 64), JAK2 (degree = 41), and CHUK (degree = 30) genes were identified as having the top three-degree values among the 27 genes. Potential interactions between lncRNA, miRNAs and mRNAs were predicted using the starBase V3.0 database, and a lncRNA-miRNA-mRNA triple network containing the lncRNA XIST, twenty-one miRNAs and three hub genes (CDC42, JAK2 and CHUK) was identified. RT-qPCR validation showed that the expression of the JAK2 and CDC42 genes and the lncRNA XIST was noticeably increased in samples from patients with AMI compared to normal samples. Pearson's correlation analysis also proved that JAK2 and CDC42 expression levels correlated positively with lncRNA XIST expression levels. The area under ROC curve (AUC) of lncRNA XIST was 0.886, and the diagnostic efficacy of the lncRNA XIST was significantly better than that of JAK2 and CDC42. The results suggested that the lncRNA XIST appears to be a risk factor for AMI likely through its ability to regulate JAK2 and CDC42 gene expressions, and it is expected to be a novel and reliable biomarker for the diagnosis of AMI.

Coronary artery disease imaging reporting and data system (CAD-RADS): what radiologists need to know?

The aim of this work is to review Coronary Artery Disease Imaging Reporting and Data System (CAD-RADS) that was designed to standardize reporting language and improve the communication of data among radiologists and clinicians. Stenotic lesions are graded into 5 grades ranging from 0 (no stenosis) to 5 (total occlusion), where the highest grade represents the final score. The expert consensus platform has added 4 special modifiers (non-diagnostic, stent, graft, and vulnerability) to aid patient management through linking these scores with decision algorithm and treatment plan. Adherence to standard imaging protocol; knowledge of normal, variant, and anomalous anatomy; and skillful evaluation of stenosis are important for proper utilization of this reporting system. Lastly, radiologists should be aware of the inherited benefits, limitations, and common pitfalls of this classification system.

Coronary Calcium Characteristics as Predictors of Major Adverse Cardiac Events in Symptomatic Patients: Insights From the CORE 320 Multinational Study

Background

The predictive value of coronary artery calcium (CAC) has been widely studied; however, little is known about specific characteristics of CAC that are most predictive. We aimed to determine the independent associations of Agatston score, CAC volume, CAC area, CAC mass, and CAC density score with major adverse cardiac events in patients with suspected coronary artery disease.

Methods and Results

A total of 379 symptomatic participants, aged 45 to 85 years, referred for invasive coronary angiography, who underwent coronary calcium scanning and computed tomography angiography as part of the CORE320 (Combined Noninvasive Coronary Angiography and Myocardial Perfusion Imaging Using 320 Detector Computed Tomography) study, were included. Agatston score, CAC volume, area, mass, and density were computed on noncontrast images. Stenosis measurements were made on contrast‐enhanced images. The primary outcome of 2‐year major adverse cardiac events (30 revascularizations [>182 days of index catheterization], 5 myocardial infarctions, 1 cardiac death, 9 hospitalizations, and 1 arrhythmia) occurred in 32 patients (8.4%). Associations were estimated using multivariable proportional means models. Median age was 62 (interquartile range, 56–68) years, 34% were women, and 56% were white. In separate models, the Agatston, volume, and density scores were all significantly associated with higher risk of major adverse cardiac events after adjustment for age, sex, race, and statin use; density was the strongest predictor in all CAC models. CAC density did not provide incremental value over Agatston score after adjustment for diameter stenosis, age, sex, and race.

Conclusions

In symptomatic patients, CAC density was the strongest independent predictor of major adverse cardiac events among CAC scores, but it did not provide incremental value beyond the Agatston score after adjustment for diameter stenosis.

From CT to artificial intelligence for complex assessment of plaque-associated risk

The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust information on the overall coronary circulation and luminal stenosis, also providing the ability to assess the composition, morphology, and vulnerability of atherosclerotic plaques. In addition, the perivascular adipose tissue (PVAT) has recently emerged as a marker of increased cardiovascular risk. The addition of PVAT quantification to standard CCTA imaging may provide the ability to extract information on local inflammation, for an individualized approach in coronary risk stratification. The development of image post-processing tools over the past several years allowed CCTA to provide a significant amount of data that can be incorporated into machine learning (ML) applications. ML algorithms that use radiomic features extracted from CCTA are still at an early stage. However, the recent development of artificial intelligence will probably bring major changes in the way we integrate clinical, biological, and imaging information, for a complex risk stratification and individualized therapeutic decision making in patients with CAD. This review aims to present the current evidence on the complex role of CCTA in the detection and quantification of vulnerable plaques and the associated coronary inflammation, also describing the most recent developments in the radiomics-based machine learning approach for complex assessment of plaque-associated risk.

LncRNA XIST promotes myocardial infarction by regulating FOS through targeting miR-101a-3p

The purpose of this study was to reveal the hypothesis that lncRNA X inactive specific transcript (XIST) can participate in the regulation of cardiomyocyte apoptosis in neonatal mice cardiomyocytes (NMCMs) and myocardial infarction (MI) through targeting miR-101a-3p. NMCMs were isolated from neonatal C57BL/6 mice and anoxia was induced in hypoxic chamber. MTT assay and flow cytometry were used to determine proliferation and apoptosis respectively. The target relationship among XIST, miR-101a-3p and FOS was revealed by bioinformatic analysis, luciferase reporter assay, pull-down assay and RNA immunoprecipitation assay. The expression of XIST, miR-101a-3p, FOS and apoptosis-related proteins was determined by qRT-PCR or western blot. MI model was constructed to reveal the role of XIST. We found that XIST was up-regulated in NMCMs under anoxia condition. Moreover, XIST increased FOS expression by sponging miR-101a-3p in anoxia cells. Silencing XIST expression improved cell viability and suppressed apoptosis in vitro and inhibited myocardial infarction by reducing the level of c-FOS and apoptosis-related proteins in vivo. Our findings suggest that XIST is involved in MI, modulation of its level can be used as a new strategy or potential target in the treatment of myocardial infarction.

Percent atheroma volume: Optimal variable to report whole-heart atherosclerotic plaque burden with coronary CTA, the PARADIGM study

BACKGROUND AND AIMS

Different methodologies to report whole-heart atherosclerotic plaque on coronary computed tomography angiography (CCTA) have been utilized. We examined which of the three commonly used plaque burden definitions was least affected by differences in body surface area (BSA) and sex.

METHODS

The PARADIGM study includes symptomatic patients with suspected coronary atherosclerosis who underwent serial CCTA >2 years apart. Coronary lumen, vessel, and plaque were quantified from the coronary tree on a 0.5 mm cross-sectional basis by a core-lab, and summed to per-patient. Three quantitative methods of plaque burden were employed: (1) total plaque volume (PV) in mm³, (2) percent atheroma volume (PAV) in % [which equaled: PV/vessel volume * 100%], and (3) normalized total atheroma volume (TAV_norm) in mm³ [which equaled: PV/vessel length * mean population vessel length]. Only data from the baseline CCTA were used. PV, PAV, and TAV_norm were compared between patients in the top quartile of BSA vs the remaining, and between sexes. Associations between vessel volume, BSA, and the three plaque burden methodologies were assessed.

RESULTS

The study population comprised 1479 patients (age 60.7 ± 9.3 years, 58.4% male) who underwent CCTA. A total of 17,649 coronary artery segments were evaluated with a median of 12 (IQR 11-13) segments per-patient (from a 16-segment coronary tree). Patients with a large BSA (top quartile), compared with the remaining patients, had a larger PV and TAV_norm, but similar PAV. The relation between larger BSA and larger absolute plaque volume (PV and TAV_norm) was mediated by the coronary vessel volume. Independent from the atherosclerotic cardiovascular disease risk (ASCVD) score, vessel volume correlated with PV (P < 0.001), and TAV_norm (P = 0.003), but not with PAV (P = 0.201). The three plaque burden methods were equally affected by sex.

CONCLUSIONS

PAV was less affected by patient's body surface area then PV and TAV_norm and may be the preferred method to report coronary atherosclerotic burden.

Coronary computed tomography angiography: a method coming of age

In patients with stable symptoms suggestive of coronary artery disease (CAD), coronary CT angiography (CTA) allows for assessing several aspects of coronary atherosclerosis. Coronary artery stenoses are reliably detected, plaque formation can be quantified and characterized as calcified or non-calcified, and markers of potential instability such as expansive vascular remodeling, spotty calcification, and atheroma size can be described. As opposed to invasive coronary angiography, CTA visualizes the vessel lumen and wall. Being a purely anatomic test, even small plaques are detected with excellent sensitivity. At the other end of the spectrum, the hemodynamic significance of large plaque burden is sometimes overestimated. This may in part be corrected using mathematical modeling. Computational fluid dynamics of vascular anatomy and subtended myocardial mass provide for measures of CT-based fractional flow reserve (FFR_CT). Large prospective trials have demonstrated the diagnostic utility of CTA in particular for ruling out obstructive CAD. The ability to detect non-obstructive plaque allows for improved risk prediction in comparison with functional testing, because even patients with sub-clinical atherosclerosis can be identified and selected for preventive medical treatment. This has led to incorporating CTA as one of several possible diagnostic tests for the evaluation of stable CAD in the actual European guidelines. Recently, it has even been forwarded as the first-line diagnostic test in the United Kingdom. The clinical implications of novel quantitative CTA-derived parameters such as FFR_CT and non-calcified plaque volume are being examined in ongoing studies.

Simplified Bernoulli formula to predict flow limiting stenosis at coronary computed tomography angiography

OBJECTIVE

To compare the diagnostic performance of estimated energy loss (EEL) with diameter stenosis (DS) to estimate significant stenosis by fractional flow reserve (FFR).

MATERIALS AND METHODS

One hundred twenty-five patients were included. EEL was calculated using DS, lesion length, minimal lumen area and left ventricular volume. FFR ≤ 0.80 was determined significant.

RESULTS

EEL improved the accuracy from 63% (95% confidence interval (CI): 55-72%) to 83% (95% CI: 75-89%, p < 0.0001). EEL increased the area under the receiver operating characteristics curve from 0.63 to 0.85 (p < 0.0001).

CONCLUSIONS

EEL improved the diagnostic performance to detect functionally significant stenosis than DS.

64-Slice spiral double-low CT to evaluate the degree of stenosis and plaque composition in diagnosing coronary artery disease

This study examined the application of 64-slice spiral double-low computed tomography (CT) to evaluate the degree of coronary artery stenosis. We examined 45 patients with coronary heart disease by 64-slice spiral double-low CT and coronary angiography (CAG) to determine CT accuracy in evaluating coronary artery stenosis. Imaging analysis from 64-slice spiral double-low CT identified 199 segments with coronary stenosis from 45 patients, including 46 segments with mild stenosis, 38 with moderate stenosis and 115 with severe stenosis or artery occlusion. CT analysis agreed with CAG on the identification of the degree of stenosis in 122 segments, with an overall accuracy of 61.3%. The accuracy for serious stenosis or occlusion was the highest at 69.6%. We also found a strong correlation between coronary plaque compositions and the degree of stenosis. Correspondence analysis showed that the presence of soft plaques closely correlated with severe stenosis, whereas mixed plaques closely correlated with moderate stenosis. Overall, 64-slice spiral double-low CT imaging can effectively assess the degree of coronary artery stenosis in patients with coronary heart disease and accurately detect plaque composition. Thus, 64-slice spiral double-low CT imaging can predict the risk of coronary heart disease and the degree of coronary artery stenosis, which is helpful for early diagnosis and treatment of coronary heart disease.

The Risk Continuum of Atherosclerosis and its Implications for Defining CHD by Coronary Angiography

Patients undergoing coronary angiography for suspected coronary heart disease who are found to have coronary atherosclerotic disease with <50% diameter stenosis may carry a risk of adverse cardiac events similar to that in patients with single-vessel obstructive disease. Yet clinical practice guidelines offer no direction for managing symptomatic patients with nonobstructive coronary atherosclerosis because current diagnostic criteria for coronary heart disease are not met. Accordingly, secondary preventive measures are not endorsed, and their role is not defined in this setting. Available data suggest that we are missing the opportunity to provide effective preventive measures in millions of patients with nonobstructive coronary heart disease. The emergence of noninvasive coronary angiography in patients with suspected coronary heart disease provides the opportunity to transition from a categorical perspective on the presence or absence of coronary heart disease to accepting the risk continuum from atherosclerosis and its implications for diagnosis and management.