Atherosclerotic plaque characteristics by CT angiography identify coronary lesions that cause ischemia: a direct comparison to fractional flow reserve

Development and Validation of a Quantitative Coronary CT Angiography Model for Diagnosis of Vessel-Specific Coronary Ischemia

BACKGROUND

Noninvasive stress testing is commonly used for detection of coronary ischemia but possesses variable accuracy and may result in excessive health care costs.

OBJECTIVES

This study aimed to derive and validate an artificial intelligence-guided quantitative coronary computed tomography angiography (AI-QCT) model for the diagnosis of coronary ischemia that integrates atherosclerosis and vascular morphology measures (AI-QCTISCHEMIA) and to evaluate its prognostic utility for major adverse cardiovascular events (MACE).

METHODS

A post hoc analysis of the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) studies was performed. In both studies, symptomatic patients with suspected stable coronary artery disease had prospectively undergone coronary computed tomography angiography (CTA), myocardial perfusion imaging (MPI), SPECT, or PET, fractional flow reserve by CT (FFRCT), and invasive coronary angiography in conjunction with invasive FFR measurements. The AI-QCTISCHEMIA model was developed in the derivation cohort of the CREDENCE study, and its diagnostic performance for coronary ischemia (FFR ≤0.80) was evaluated in the CREDENCE validation cohort and PACIFIC-1. Its prognostic value was investigated in PACIFIC-1.

RESULTS

In CREDENCE validation (n = 305, age 64.4 ± 9.8 years, 210 [69%] male), the diagnostic performance by area under the receiver-operating characteristics curve (AUC) on per-patient level was 0.80 (95% CI: 0.75-0.85) for AI-QCTISCHEMIA, 0.69 (95% CI: 0.63-0.74; P < 0.001) for FFRCT, and 0.65 (95% CI: 0.59-0.71; P < 0.001) for MPI. In PACIFIC-1 (n = 208, age 58.1 ± 8.7 years, 132 [63%] male), the AUCs were 0.85 (95% CI: 0.79-0.91) for AI-QCTISCHEMIA, 0.78 (95% CI: 0.72-0.84; P = 0.037) for FFRCT, 0.89 (95% CI: 0.84-0.93; P = 0.262) for PET, and 0.72 (95% CI: 0.67-0.78; P < 0.001) for SPECT. Adjusted for clinical risk factors and coronary CTA-determined obstructive stenosis, a positive AI-QCTISCHEMIA test was associated with aHR: 7.6 (95% CI: 1.2-47.0; P = 0.030) for MACE.

CONCLUSIONS

This newly developed coronary CTA-based ischemia model using coronary atherosclerosis and vascular morphology characteristics accurately diagnoses coronary ischemia by invasive FFR and provides robust prognostic utility for MACE beyond presence of stenosis.

The impact of lipoprotein(a) level on cardiac pathologies in diabetes: a cardiac CT study

OBJECTIVES

We aimed to explore the imaging profile of coronary atherosclerosis, perivascular inflammation, myocardial perfusion, and interstitial fibrosis in diabetes stratified by lipoprotein(a) [Lp(a)] levels.

METHODS

In this prospective study, we enrolled diabetic patients who had undergone computed tomography (CT) angiography, stress CT-myocardial perfusion imaging, and late iodine enhancement in 20 months. Then, we categorized them into elevated and normal groups based on an Lp(a) cutoff level of 30 mg/dL. All imaging data, including coronary atherosclerosis parameters, pericoronary adipose tissue (PCAT) density, stress myocardial blood flow (MBF), and extracellular volume (ECV), were collected for further analysis.

RESULTS

In total, 207 participants (mean age: 59.1 ± 12.0 years, 111 males) were included in this study. Patients with elevated Lp(a) level had more pronounced percent atheroma volume (2.55% (1.01-9.01%) versus 1.30% (0-4.95%), p = 0.010), and demonstrated a higher incidence of positive remodeling, spotty calcification, and high-risk plaque (HRP) than those with normal Lp(a) levels (75.6% versus 54.8%, p = 0.015; 26.8% versus 9.6%, p = 0.003; 51.2% versus 30.1%, p = 0.011, respectively). Results of the multivariate analysis revealed that after adjusting for all clinical characteristics, elevated Lp(a) levels were an independent parameter associated with HRP (odds ratio = 2.608; 95% confidence interval: 1.254-5.423, p = 0.010). However, no significant difference was found between the two groups in terms of PCAT density, stress MBF, and ECV.

CONCLUSIONS

Elevated Lp(a) levels are associated with extensive coronary atherosclerosis and HRP development. However, they are not related to perivascular inflammation, decreased myocardial perfusion, and interstitial fibrosis in diabetes.

CLINICAL RELEVANCE STATEMENT

Elevated lipoprotein(a) levels are associated with extensive coronary atherosclerosis and a high incidence of HRPs. However, they are not related to perivascular inflammation, decreased myocardial perfusion, and interstitial fibrosis in diabetes.

KEY POINTS

Diabetes is a known risk factor that accelerates cardiovascular disease progression. Diabetics with elevated lipoprotein(a) (Lp(a)) levels had a higher percent atheroma volume and positive remodeling, spotty calcification, and HRPs. Patients with diabetes should be screened for elevated Lp(a) using CCTA for comprehensive evaluation of atherosclerotic characteristics.

Left anterior descending coronary artery-left circumflex coronary artery bifurcation angle and severity of coronary artery disease; is there any correlation? A cross-sectional study

Background and Aims

The aim of this study is to evaluate the association of coronary computed tomography angiography derived (CCTA) plaque characteristics and the left anterior descending coronary artery (LAD) and left circumflex coronary artery (LCX) bifurcation angle with severity of coronary artery disease (CAD).

Methods

All the stable patients with suspected CAD who underwent CCTA between January to December 2021 were included. Correlation between CCTA-derived aggregated plaque volume (APV), LAD-LCX angle, remodeling index (RI), coronary calcium score with Gensini score in conventional angiography were assessed. One hundred and twenty-two patients who underwent both CCTA and coronary angiography were analyzed.

Results

Our analysis showed that the median (percentile 25% to percentile 75%) of the APV, LAD-LCx angle, and calcium score were 31% (17%-47%), 58° (39°-89°), and 31 (0-186), respectively. Also, the mean ± SD of the RI was 1.05 ± 0.20. Significant correlation between LAD-LCx bifurcation angle (0.0001-0.684), APV (0.002-0.281), RI (0.0001-0.438), and calcium score (0.016-0.217) with Gensini score were detected. There was a linear correlation between the mean LAD-LCx bifurcation angle and the Gensini score. The sensitivity and specificity for the cut-off value of 47.5° for the LAD-LCX angle were 86.7% and 82.1%, respectively.

Conclusion

There is a direct correlation between the LAD-LCx angle and the Gensini score. In addition to plaque characteristics, anatomic-based CCTA-derived indices can be used to identify patients at higher risk for CAD.

Invasive electrochemical impedance spectroscopy with phase delay for experimental atherosclerosis phenotyping

Distinguishing quiescent from rupture-prone atherosclerotic lesions has significant translational and clinical implications. Electrochemical impedance spectroscopy (EIS) characterizes biological tissues by assessing impedance and phase delay responses to alternating current at multiple frequencies. We evaluated invasive 6-point stretchable EIS sensors over a spectrum of experimental atherosclerosis and compared results with intravascular ultrasound (IVUS), molecular positron emission tomography (PET) imaging, and histology. Male New Zealand White rabbits (n = 16) were placed on a high-fat diet, with or without endothelial denudation via balloon injury of the infrarenal abdominal aorta. Rabbits underwent in vivo micro-PET imaging of the abdominal aorta with 68Ga-DOTATATE, 18F-NaF, and 18F-FDG, followed by invasive interrogation via IVUS and EIS. Background signal-corrected values of impedance and phase delay were determined. Abdominal aortic samples were collected for histology. Analyses were performed blindly. EIS impedance was associated with markers of plaque activity including macrophage infiltration (r = .813, p = .008) and macrophage/smooth muscle cell (SMC) ratio (r = .813, p = .026). Moreover, EIS phase delay correlated with anatomic markers of plaque burden, namely intima/media ratio (r = .883, p = .004) and %stenosis (r = .901, p = .002), similar to IVUS. 68Ga-DOTATATE correlated with intimal macrophage infiltration (r = .861, p = .003) and macrophage/SMC ratio (r = .831, p = .021), 18F-NaF with SMC infiltration (r = -.842, p = .018), and 18F-FDG correlated with macrophage/SMC ratio (r = .787, p = .036). EIS with phase delay integrates key atherosclerosis features that otherwise require multiple complementary invasive and non-invasive imaging approaches to capture. These findings indicate the potential of invasive EIS to comprehensively evaluate human coronary artery disease.

WITHDRAWN: Coronary artery segmentation based on ACMA-Net and unscented Kalman filter algorithm

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Evaluation of fractional flow reserve and atherosclerotic plaque characteristics on coronary non-contrast T1-weighted magnetic resonance imaging

BACKGROUND AND AIMS

The relationship between high-risk coronary plaque characteristics regardless of the severity of lesion stenosis and myocardial ischemia remains unsettled. High-intensity plaques (HIPs) on non-contrast T1-weighted magnetic resonance imaging (T1WI) have been characterized as high-risk coronary plaques. We sought to elucidate whether the presence of coronary HIPs on T1WI influences fractional flow reserve (FFR) in the distal segment of the vessel.

METHODS

We retrospectively analyzed 281 vessels in 231 patients with chronic coronary syndrome who underwent invasive FFR measurement and coronary T1WI using a multicenter registry. The plaque-to-myocardial signal intensity ratio (PMR) of the most stenotic lesion was evaluated; a coronary plaque with PMR ≥1.4 was defined as a HIP.

RESULTS

The median PMR of coronary plaques on T1WI in vessels with FFR ≤0.80 was significantly higher than that of plaques with FFR >0.80 (1.17 [interquartile range (IQR): 0.99-1.44] vs. 0.97 [IQR: 0.85-1.09]; p < 0.001). Multivariable analysis showed that an increase in PMR of the most stenotic segment was associated with lower FFR (beta-coefficient, -0.050; p < 0.001). The presence of coronary HIPs was an independent predictor of FFR ≤0.80 (odds ratio (OR), 6.18; 95% confidence interval (CI), 1.93-19.77; p = 0.002). Even after adjusting for plaque composition characteristics based on computed tomography angiography, the presence of coronary HIPs was an independent predictor of FFR ≤0.80 (OR, 4.48; 95% CI, 1.19-16.80; p = 0.026).

CONCLUSIONS

Coronary plaques with high PMR are associated with low FFR in the corresponding vessel, indicating that plaque morphology might influence myocardial ischemia severity.

Prognostic Implications of Quantitative Flow Ratio and Plaque Characteristics in Intravascular Ultrasound-Guided Treatment Strategy

BACKGROUND

Quantitative flow ratio (QFR) is a method for evaluating fractional flow reserve without the use of an invasive coronary pressure wire or pharmacological hyperemic agent.

OBJECTIVES

The aim of this study was to investigate the prognostic implications of QFR and plaque characteristics in patients who underwent intravascular ultrasound (IVUS)-guided treatment for intermediate lesions.

METHODS

Among the IVUS-guided strategy group in the FLAVOUR (Fractional Flow Reserve and Intravascular Ultrasound for Clinical Outcomes in Patients with Intermediate Stenosis) trial, vessels suitable for QFR analysis were included in this study. High-risk features were defined as low QFR (≤0.90), quantitative high-risk plaque characteristics (qn-HRPCs) (minimal lumen area ≤3.5 mm2, or plaque burden ≥70%), and qualitative high-risk plaque characteristics (ql-HRPCs) (attenuated plaque, positive remodeling, or plaque rupture) assessed using IVUS. The primary clinical endpoint was target vessel failure (TVF), defined as a composite of cardiac death, target vessel myocardial infarction, and target vessel revascularization.

RESULTS

A total of 415 (46.1%) vessels could be analyzable for QFR. The numbers of qn-HRPCs and ql-HRPCs increased with decreasing QFR. Among deferred vessels, those with 3 high-risk features exhibits a significantly higher risk of TVF compared with those with ≤2 high-risk features (12.0% vs 2.7%; HR: 4.54; 95% CI: 1.02-20.29).

CONCLUSIONS

Among the IVUS-guided deferred group, vessels with qn-HRPC and ql-HRPC with low QFR (≤0.90) exhibited a significantly higher risk for TVF compared with those with ≤2 features. Integrative assessment of angiography-derived fractional flow reserve and anatomical and morphological plaque characteristics is recommended to improve clinical outcomes in patients undergoing IVUS-guided deferred treatment.

Computed Tomography-Derived Physiology Assessment: State-of-the-Art Review

Coronary computed tomography angiography (CCTA) and CCTA-derived fractional flow reserve (FFRCT) are the best non-invasive techniques to assess coronary artery disease (CAD) and myocardial ischemia. Advances in these technologies allow a paradigm shift to the use of CCTA and FFRCT for advanced plaque characterization and planning myocardial revascularization.

Low-attenuation coronary plaque burden and troponin release in chronic coronary syndrome: A mediation analysis

BACKGROUND

Coronary low-attenuation plaque (LAP) burden is a strong predictor of myocardial infarction in patients with stable chest pain. We aimed to assess the relationship between LAP burden and circulating levels of high-sensitivity cardiac troponin T (hs-cTnT), and to explore the potential underlying etiology in patients undergoing clinically indicated coronary CT angiography (CCTA).

METHODS

A comprehensive metabolic and lipid panel, as well as C-reactive protein (CRP) and hs-cTnT tests were obtained from consecutive patients with stable chest pain at the time of CCTA. Qualitative and quantitative coronary plaque analysis, CT-derived fractional flow reserve (FFR) calculation, and pericoronary adipose tissue (PCAT) attenuation measurement around the right coronary artery were performed on CCTA images. Linear regression analyses were performed to identify independent associations with hs-cTnT concentration and mediation analysis was used to assess whether ischemia or markers of inflammation mediate hs-cTnT elevation.

RESULTS

In total, 114 patients (56.3 ​± ​10.6 years, 44.7 ​% female) were enrolled. In multivariable analysis, age (β ​= ​0.04 [95%CI: 0.02; 0.06], p ​< ​0.001), female sex (β ​= ​-0.77 [95%CI: -1.20; 0.33], p ​< ​0.001), and LAP burden (β ​= ​0.03 [95%CI: 0.001; 0.06], p ​= ​0.04) were independently associated with hs-cTnT levels. Mediation analysis, on the other hand, did not identify a significant mediating effect of lesion-specific ischemia based on CT-FFR, circulating CRP levels, or PCAT values between LAP burden and hs-cTnT levels (all p ​> ​0.05).

CONCLUSION

Although ischemia and inflammation have previously been proposed to mediate the association between LAP burden and hs-cTnT levels, our results did not confirm the role of these pathophysiological pathways in patients with stable chest pain.

Enhancing Risk Stratification on Coronary Computed Tomography Angiography: The Role of Artificial Intelligence

PURPOSE

To describe and outline the role of artificial intelligence (AI) in assisting coronary computed tomography angiography (CCTA) in enhancing risk stratification.

METHODS

A comprehensive review of the literature was performed to identify published work investigating the utility of applying AI to CCTA.

FINDINGS

CCTA is an excellent diagnostic tool for the detection of atherosclerotic cardiovascular disease. The noninvasive nature and high diagnostic accuracy have made CCTA a viable alternative to invasive coronary angiography to detect luminal stenosis. However, it is now understood that stenosis is just one factor that predicts cardiac risk and other factors need to be considered. CCTA-derived plaque biomarkers have since emerged as established predictors of cardiac events to improve risk stratification. Despite awareness of these biomarkers, they are still yet to be incorporated into routine clinical practice. The major barriers to implementation include the specialized skills required for image evaluation and the time intensive nature of analysis. With the many recent advancements in the technology, AI presents itself as a promising solution. AI is attractive because it has the potential to rapidly automate technically challenging tasks with exceptional accuracy.

IMPLICATIONS

Developments in the field of AI are occurring at a rapid rate. There is already increasing evidence of the potential AI has to greatly improve the utility of CCTA by improving analysis time and extracting additional prognostic data from new plaque biomarkers. There are, however, technical and ethical challenges that need to be considered before implementing such technology into routine clinical practice.

Coronary Atherosclerosis Phenotypes in Focal and Diffuse Disease

BACKGROUND

The interplay between coronary hemodynamics and plaque characteristics remains poorly understood.

OBJECTIVES

The aim of this study was to compare atherosclerotic plaque phenotypes between focal and diffuse coronary artery disease (CAD) defined by coronary hemodynamics.

METHODS

This multicenter, prospective, single-arm study was conducted in 5 countries. Patients with functionally significant lesions based on an invasive fractional flow reserve ≤0.80 were included. Plaque analysis was performed by using coronary computed tomography angiography and optical coherence tomography. CAD patterns were assessed using motorized fractional flow reserve pullbacks and quantified by pullback pressure gradient (PPG). Focal and diffuse CAD was defined according to the median PPG value.

RESULTS

A total of 117 patients (120 vessels) were included. The median PPG was 0.66 (IQR: 0.54-0.75). According to coronary computed tomography angiography analysis, plaque burden was higher in patients with focal CAD (87% ± 8% focal vs 82% ± 10% diffuse; P = 0.003). Calcifications were significantly more prevalent in patients with diffuse CAD (Agatston score per vessel: 51 [IQR: 11-204] focal vs 158 [IQR: 52-341] diffuse; P = 0.024). According to optical coherence tomography analysis, patients with focal CAD had a significantly higher prevalence of circumferential lipid-rich plaque (37% focal vs 4% diffuse; P = 0.001) and thin-cap fibroatheroma (TCFA) (47% focal vs 10% diffuse; P = 0.002). Focal disease defined by PPG predicted the presence of TCFA with an area under the curve of 0.73 (95% CI: 0.58-0.87).

CONCLUSIONS

Atherosclerotic plaque phenotypes associate with intracoronary hemodynamics. Focal CAD had a higher plaque burden and was predominantly lipid-rich with a high prevalence of TCFA, whereas calcifications were more prevalent in diffuse CAD. (Precise Percutaneous Coronary Intervention Plan [P3]; NCT03782688).

Machine learning based ischemia-specific stenosis prediction: A Chinese multicenter coronary CT angiography study

OBJECTIVES

To evaluate the performance of coronary computed tomography angiography (CCTA) derived characteristics including CT derived fractional flow reserve (CT-FFR) with FFR as a reference standard in identifying the lesion-specific ischemia by machine learning (ML) algorithms.

METHODS

The retrospective analysis enrolled 596 vessels in 462 patients (mean age, 61 years ± 11 [SD]; 71.4 % men) with suspected coronary artery disease who underwent CCTA and invasive FFR. The data were divided into training cohort, internal validation cohort, external validation cohorts 1 and 2 according to participating centers. All CCTA-derived parameters, which contained 10 qualitative and 33 quantitative plaque parameters, were collected to establish ML model. The Boruta and unsupervised clustering algorithm were implemented to select important and non-redundant parameters. Finally, the eight features with the highest mean importance were included for further ML model establishment and decision tree building. Five models were built to predict lesion-specific ischemia: stenosis degree from CCTA, CT-FFR, ΔCT-FFR, ML model and nested model.

RESULTS

Low-attenuation plaque, bend and lesion length were the main predictors of ischemia-specific lesions. Of 5 models, the ML model showed favorable discrimination for ischemia-specific lesions in the training and three validation sets (area under the curve [95 % confidence interval], 0.93 [0.90-0.96], 0.86 [0.79-0.94], 0.88 [0.83-0.94], and 0.90 [0.84-0.96], respectively). The nested model which combined the ML model and CT-FFR showed better diagnostic efficacy (AUC [95 %CI], 0.96 [0.94-0.99], 0.92 [0.86-0.99], 0.92 [0.86-0.99] and 0.94 [0.91-0.98], respectively; all P < 0.05), and net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were significantly higher than CT-FFR alone.

CONCLUSIONS

Comprehensive CCTA-derived multiparameter model could better predict the ischemia-specific lesions by ML algorithms compared to stenosis degree from CTA, CT-FFR and ΔCT-FFR. Decision tree can be used to predict myocardial ischemia effectively.

Association of serum cystatin C level with coronary atherosclerotic plaque burden: a comprehensive analysis of observational studies and genetic study

BACKGROUND AND AIMS

Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. However, the relationship between serum cystatin C level and coronary atherosclerotic plaque burden is limited. We aimed to evaluate the relationship between circulating cystatin C and coronary atherosclerotic plaque burden.

METHODS

This study was a cross-sectional study based on China community population. Measurements of plaque burden were based on the segment-involvement score (SIS) and segment stenosis score (SSS), which derived from the Coronary Artery Tree Model Depicting Coronary Artery Plaque Scores. Logistic regression model was used to demonstrate the association between cystatin C level and coronary artery plaque burden. Mendelian randomization (MR) analyses were conducted to assess the causal effect of cystatin C level on coronary atherosclerosis risk.

RESULTS

A total of 3,043 objects were included in the present study. The odds risks (OR) of severe plaque burden in the highest serum cystatin C levels (OR: 2.50; Cl:1.59-3.91; P < 0.001) and medium-level cystatin C levels (OR: 1.86; 95% Cl: 1.21-2.88; P = 0.005) were significantly higher after fulled adjusted confounders compared with the lowest levels of serum cystatin C by SSS. The MR analysis showed that genetic predicted cystatin C levels was associated with an increased risk of coronary atherosclerosis (OR, 1.004; 95% CI, 1.002-1.006, P < 0.001) .

CONCLUSION

Elevated serum cystatin C levels were associated with coronary atherosclerotic plaque burden. Cystatin C levels had a causal effect on an increased risk of coronary atherosclerosis at the genetic level. WHAT IS ALREADY KNOWN ON THIS TOPIC?: Coronary artery disease is currently the most common cardiovascular disease and the leading global cause of mortality. Previous studies reported that higher serum cystatin C levels were associated with an increased risk for future cardiovascular events, independent of the normal creatinine levels or estimated glomerular filtration rate (eGFR) values. The presence of high-risk coronary atherosclerotic plaque burden is associated with increased risk of cardiovascular events. However, the association between serum cystatin C and coronary atherosclerotic plaque burden is not very clear. WHAT THIS STUDY ADDS?: Our study demonstrated that the elevated serum cystatin C levels were associated with coronary atherosclerotic plaque burden. In addition, we found that serum cystatin C levels had a causal effect on an increased risk of coronary atherosclerosis at the genetic level. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY?: Current research finds that serum cystatin C levels were associated with coronary atherosclerosis. The metabolic pathway of cystatin C could be a target for new therapies against CAD.

Diagnostic accuracy of noninvasive fractional flow reserve derived from computed tomography angiography in ischemia-specific coronary artery stenosis and indeterminate lesions: results from a multicenter study in China

Background

To determine the diagnostic performance of a novel computational fluid dynamics (CFD)-based algorithm for in situ CT-FFR in patients with ischemia-induced coronary artery stenosis. Additionally, we investigated whether the diagnostic accuracy of CT-FFR differs significantly across the spectrum of disease and analyzed the influencing factors that contribute to misdiagnosis.

Methods

Coronary computed tomography angiography (CCTA), invasive coronary angiography (ICA), and FFR were performed on 324 vessels from 301 patients from six clinical medical centers. Local investigators used CCTA and ICA to conduct assessments of stenosis, and CT-FFR calculations were performed in the core laboratory. For CCTA and ICA, CT-FFR ≤ 0.8 and a stenosis diameter ≥ 50% were identified as lesion-specific ischemia. Univariate logistic regression models were used to assess the effect of features on discordant lesions (false negative and false positive) in different CT-FFR categories. The diagnostic performance of CT-FFR was analyzed using an invasive FFR ≤ 0.8 as the gold standard.

Results

The Youden index indicated an optimal threshold of 0.80 for CT-FFR to identify functionally ischemic lesions. On a per-patient basis, the diagnostic sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) for CT-FFR were 96% (91%-98%), 92% (87%-96%), 94% (90%-96%), 91% (85%-95%), and 96% (92%-99%), respectively. The diagnostic efficacy of CT-FFR was higher than that of CCTA without the influence of calcification. Closer to the cut point, there was less certainty, with the agreement between the invasive FFR and the CT-FFR being at its lowest in the CT-FFR range of 0.7-0.8. In all lesions, luminal stenosis ≥ 50% significantly affected the risk of reduced false negatives (FN) and false positives (FP) results by CT-FFR, irrespective of the association with calcified plaque.

Conclusions

In summary, CT-FFR based on the new parameter-optimized CFD model has a better diagnostic performance than CTA for lesion-specific ischemia. The presence of calcified plaque has no significant effect on the diagnostic performance of CT-FFR and is independent of the degree of calcification. Given the range of applicability of our software, its use at a CT-FFR of 0.7-0.8 requires caution and must be considered in the context of multiple factors.

Differential predictability for high-risk plaque characteristics between fractional flow reserve and instantaneous wave-free ratio

To evaluate the differential associations of high-risk plaque characteristics (HRPC) with resting or hyperemic physiologic indexes (instantaneous wave-free ratio [iFR] or fractional flow reserve [FFR]), a total of 214 vessels from 127 patients with stable angina or acute coronary syndrome who underwent coronary computed tomography angiography (CCTA) and invasive physiologic assessment were investigated. HPRC were classified into quantitative (minimal luminal area < 4 mm2 or plaque burden ≥ 70%) and qualitative features (low attenuation plaque, positive remodeling, napkin ring sign, or spotty calcification). Vessels with FFR ≤ 0.80 or iFR ≤ 0.89 had significantly higher proportions of HRPC than those with FFR > 0.80 or iFR > 0.89, respectively. FFR was independently associated with both quantitative and qualitative HRPC, but iFR was only associated with quantitative HRPC. Both FFR and iFR were significantly associated with the presence of ≥ 3 HRPC, and FFR demonstrated higher discrimination ability than iFR (AUC 0.703 vs. 0.648, P = 0.045), which was predominantly driven by greater discriminating ability of FFR for quantitative HRPC (AUC 0.832 vs. 0.744, P = 0.005). In conclusion, both FFR and iFR were significantly associated with CCTA-derived HRPC. Compared with iFR, however, FFR was independently associated with the presence of qualitative HRPC and showed a higher predictive ability for the presence of ≥ 3 HRPC.

Construction and validation of a clinical prediction model for asymptomatic obstructive coronary stenosis in patients with carotid stenosis

Background

Coronary artery stenosis occurs frequently in patients with carotid artery stenosis. We developed a clinical predictive model to investigate the clinical risk of asymptomatic obstructive coronary artery stenosis in patients with carotid artery stenosis ≥ 50%.

Methods

From January 2018 to January 2022, carotid stenosis patients hospitalized at the First Affiliated Hospital of Zhengzhou University's Department of Endovascular Surgery were subjected to a retrospective analysis of their clinical information and imaging results. Excluded criteria were patients with lacking data, symptomatic coronary stenosis, prior coronary artery bypass grafting, and coronary stent implantation. Patients were separated into case and control groups according to whether or not they had obstructive coronary stenosis. Independent predictors were screened using univariate and multivariate logistic regression, and their accuracy was confirmed using least absolute shrinkage and selection operator (LASSO) regression. A Nomogram prediction model was developed using the aforementioned filtered factors. The model's discrimination and specificity were evaluated using the receiver operating characteristic curve (ROC) and Hosmer-Lemeshow goodness-of-fit test. Internal validation employed the Bootstrap procedure. The clinical decision curve analysis (DCA) of the prediction model was developed to assess the clinical applicability of the model.

Results

The investigation included a total of 227 patients, of whom 132 (58.1%) had coronary artery stenosis. Hypertension, Grade I plaque, HbA1c ≥ 7.0%, MPV ≥ 9.2fl, and Fib ≥ 3.0 g/L were independent predictors, with OR values of (2.506, 0.219, 0.457, 1.876, 2.005), according to multivariate logistic regression. Risk factor screening and validation using lasso regression. The predictors chosen based on the optimal λ value are consistent with the predictors identified by multiple regression. The area under the ROC curve (AUC) of the model based on the above predictors was 0.701 (0.633-0.770), indicating that the model discriminated well. The calibration curve of the model closely matched the actual curve, and P > 0.05 in the Hosmer-Lemeshow goodness-of-fit test indicated the model's accuracy. The results of the DCA curve demonstrate the clinical applicability of the prediction model.

Conclusion

Hypertension, grade I plaque, HbA1c ≥ 7.0%, MPV ≥ 9.2 fl, and Fib ≥ 3.0 g/L are predictors of asymptomatic coronary stenosis in patients with carotid stenosis ≥50%. The diagnostic model is clinically applicable and useful for identifying patients at high risk.

Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion

Background

This study sought to evaluate the association between coronary plaque characteristics, changes in the fractional flow reserve (FFR) derived from computed tomography across the lesion (ΔFFRCT), and lesion-specific ischemia using the FFR in patients with suspected or known coronary artery disease.

Methods

The study assessed coronary computed tomography (CT) angiography stenosis, plaque characteristics, ΔFFRCT, and FFR in 164 vessels of 144 patients. Obstructive stenosis was defined as stenosis ≥50%. An area under the receiver -operating characteristics curve (AUC) analysis was conducted to define the optimal thresholds for ΔFFRCT and the plaque variables. Ischemia was defined as a FFR of ≤0.80.

Results

The optimal cut-off value of ΔFFRCT was 0.14. Low-attenuation plaque (LAP) ≥76.23 mm3 and a percentage aggregate plaque volume (%APV) ≥28.91% can be used to predict ischemia independent of other plaque characteristics. The addition of LAP ≥76.23 mm3 and %APV ≥28.91% improved the discrimination (AUC, 0.742 vs. 0.649, P=0.001) and reclassification abilities [category-free net reclassification index (NRI), 0.339, P=0.027; relative integrated discrimination improvement (IDI) index, 0.093, P<0.001] of the assessments compared to the stenosis evaluation alone, and the addition of information about ΔFFRCT ≥0.14 further increased the discrimination (AUC, 0.828 vs. 0.742, P=0.004) and reclassification abilities (NRI, 1.029, P<0.001; relative IDI, 0.140, P<0.001) of the assessments.

Conclusions

The addition of the plaque assessment and ΔFFRCT to the stenosis assessments improved the identification of ischemia compared to the stenosis assessment alone.

Prognostic Utility of Coronary Computed Tomography Angiography-derived Plaque Information on Long-term Outcome in Patients With and Without Diabetes Mellitus

PURPOSE

To investigate the long-term prognostic value of coronary computed tomography angiography (cCTA)-derived plaque information on major adverse cardiac events (MACE) in patients with and without diabetes mellitus.

MATERIALS AND METHODS

In all, 64 patients with diabetes (63.3±10.1 y, 66% male) and suspected coronary artery disease who underwent cCTA were matched with 297 patients without diabetes according to age, sex, cardiovascular risk factors, and statin and antithrombotic therapy. MACE were recorded. cCTA-derived risk scores and plaque measures were assessed. The discriminatory power to identify MACE was evaluated using multivariable regression analysis and concordance indices.

RESULTS

After a median follow-up of 5.4 years, MACE occurred in 31 patients (8.6%). In patients with diabetes, cCTA risk scores and plaque measures were significantly higher compared with nondiabetic patients (all P <0.05). The following plaque measures were predictors of MACE using multivariable Cox regression analysis (hazard ratio [HR]) in patients with diabetes: segment stenosis score (HR=1.20, P <0.001), low-attenuation plaque (HR=3.47, P =0.05), and in nondiabetic patients: segment stenosis score (HR=1.92, P <0.001), Agatston score (HR=1.0009, P =0.04), and low-attenuation plaque (HR=4.15, P =0.04). A multivariable model showed a significantly improved C-index of 0.96 (95% confidence interval: 0.94-0.0.97) for MACE prediction, when compared with single measures alone.

CONCLUSION

Diabetes is associated with a significantly higher extent of coronary artery disease and plaque features, which have independent predictive values for MACE. cCTA-derived plaque information portends improved risk stratification of patients with diabetes beyond the assessment of obstructive stenosis on cCTA alone with subsequent impact on individualized treatment decision-making.

Impact of coronary disease patterns, anatomical factors, micro-vascular disease and non-coronary cardiac factors on invasive coronary physiology

Invasive coronary physiology has been applied by interventional cardiologists to guide the management of coronary artery disease (CAD), with well-defined thresholds applied to determine whether CAD should be managed with optimal medical therapy (OMT) alone or OMT and percutaneous coronary intervention (PCI). There are multiple modalities in clinical use, including hyperaemic and non-hyperaemic indices. Despite endorsement in the major guidelines, there are various factors which impact and confound the readings of invasive coronary physiology, both within the coronary tree and beyond. This review article aims to summarise the mechanisms by which these factors impact invasive coronary physiology, and distinguish factors that contribute to ischaemia from confounding factors. The potential for mis-classification of ischaemic status is highlighted. Lastly, the authors identify targets for future research to improve the precision of physiology-guided management of CAD.

Integration of fractional flow reserve derived from CT into clinical practice

Fractional flow reserve (FFR) is currently considered as the gold standard for revascularization decision-making in patients with stable coronary artery disease (CAD). The application of computational fluid dynamics to coronary computed tomography (CT) angiography (CCTA) enables calculation of FFR without additional testing, radiation exposure, contrast medium injection, and hyperemia (FFR_CT). Although multiple diagnostic and clinical studies have enriched the scientific evidence, it is still challenging to integrate FFR_CT into clinical practice. Both meticulous scientific backgrounds and precise anatomical data derived from CCTA are fundamental for FFR_CT computation, and there are numerous factors impacting on FFR_CT calculation and interpretation: coronary artery stenosis, calcium, atherosclerosis, luminal volume, and left ventricular myocardial mass. Further, there is a gap that clinicians using FFR_CT need to recognize in interpretation of FFR_CT results between diagnostic studies and clinical studies. In this review, we summarize multiple evidence related to FFR_CT computation and interpretation to refine the FFR_CT strategy in patients with stable CAD.

Gender Differences in Epicardial Adipose Tissue and Plaque Composition by Coronary CT Angiography: Association with Cardiovascular Outcome

Background: To investigate gender differences in epicardial adipose tissue (EAT) and plaque composition by coronary CT angiography (CCTA) and the association with cardiovascular outcome. Methods: Data of 352 patients (64.2 ± 10.3 years, 38% female) with suspected coronary artery disease (CAD) who underwent CCTA were retrospectively analyzed. EAT volume and plaque composition from CCTA were compared between men and women. Major adverse cardiovascular events (MACE) were recorded from follow-up. Results: Men were more likely to have obstructive CAD, higher Agatston scores, and a larger total and non-calcified plaque burden. In addition, men displayed more adverse plaque characteristics and EAT volume compared to women (all p < 0.05). After a median follow-up of 5.1 years, MACE occurred in 8 women (6%) and 22 men (10%). In multivariable analysis, Agatston calcium score (HR 1.0008, p = 0.014), EAT volume (HR 1.067, p = 0.049), and low-attenuation plaque (HR 3.82, p = 0.036) were independent predictors for MACE in men, whereas only low-attenuation plaque (HR 2.42, p = 0.041) showed predictive value for events in women. Conclusion: Women demonstrated less overall plaque burden, fewer adverse plaque characteristics, and a smaller EAT volume compared to men. However, low-attenuation plaque is a predictor for MACE in both genders. Thus, a differentiated plaque analysis is warranted to understand gender differences of atherosclerosis to guide medical therapy and prevention strategies.

Computed Tomography-Derived Physiology Assessment: State-of-the-Art Review

Coronary computed tomography angiography (CCTA) and CCTA-derived fractional flow reserve (FFRCT) are the best non-invasive techniques to assess coronary artery disease (CAD) and myocardial ischemia. Advances in these technologies allow a paradigm shift to the use of CCTA and FFRCT for advanced plaque characterization and planning myocardial revascularization.

Association of epicardial adipose tissue with coronary CT angiography plaque parameters on cardiovascular outcome in patients with and without diabetes mellitus

BACKGROUND AND AIMS

We aimed to evaluate the association of epicardial adipose tissue (EAT) with coronary CT angiography (CCTA) plaque parameters on cardiovascular outcome in patients with and without diabetes mellitus.

METHODS

Data of 353 patients (62.9 ± 10.4 years, 62% male), who underwent CCTA as part of their clinical workup for the evaluation of suspected or known CAD, were retrospectively analyzed. EAT volume and plaque parameters from CCTA were compared in patients with diabetes (n = 63) and without diabetes (n = 290). Follow-up was performed to record adverse cardiovascular events. The predictive value to detect adverse cardiovascular events was assessed using concordance indices (CIs) and multivariable Cox proportional hazards analysis.

RESULTS

In total, 33 events occurred after a median follow-up of 5.1 years. In patients with diabetes, EAT volume and plaque parameters were significantly higher than in patients without diabetes (all p < 0.05). A multivariable model demonstrated an incrementally improved C-index of 0.84 (95%CI 0.80-0.88) over the Framingham risk score and single measures alone. In multivariable Cox regression analysis EAT volume (Hazard ratio[HR] 1.21, p = 0.022), obstructive CAD (HR 1.18, p = 0.042), and ≥2 high-risk plaque features (HR 2.13, p = 0.031) were associated with events in patients with diabetes and obstructive CAD (HR 1.88, p = 0.017), and Agatston calcium score (HR 1.009, p = 0.039) in patients without diabetes.

CONCLUSIONS

EAT, as a biomarker of inflammation, and plaque parameters, as an extent of atherosclerotic CAD, are higher in patients with diabetes and are associated with increased adverse cardiovascular outcomes. These parameters may help identify patients at high risk with need for more aggressive therapeutic and preventive care.

Testosterone replacement therapy and cardiovascular disease

The use of testosterone therapy has a complex history of apprehension and questions regarding its safety. Despite an eventual consensus that testosterone therapy was safe and effective, several studies relating to cardiovascular risks emerged in the last decade, rekindling skepticism regarding the safety of testosterone therapy. Given the utility of testosterone therapy in treating the symptoms of hypogonadism, it remains crucial to closely examine the safety of testosterone therapy. The present article synthesizes the current evidence regarding cardiovascular risks that may be associated with testosterone therapy, the potential mechanisms regarding testosterone's efficacy, and future directions in evaluating the safety of its use.

Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow

BACKGROUND

A pathophysiological interplay exists between plaque morphology and coronary physiology. Machine learning (ML) is increasingly being applied to coronary computed tomography angiography (CCTA) for cardiovascular risk stratification. We sought to assess the performance of a ML score integrating CCTA-based quantitative plaque features for predicting vessel-specific ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by positron emission tomography (PET).

METHODS

This post-hoc analysis of the PACIFIC trial (Prospective Comparison of Cardiac Positron Emission Tomography/Computed Tomography [CT]' Single Photon Emission Computed Tomography/CT Perfusion Imaging and CT Coronary Angiography with Invasive Coronary Angiography) included 208 patients with suspected coronary artery disease who prospectively underwent CCTA' [15O]H2O PET, and invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. An ML algorithm trained on the prospective NXT trial (484 vessels) was used to develop a ML score for the prediction of ischemia (FFR≤0.80), which was then evaluated in 581 vessels from the PACIFIC trial. Thereafter, the ML score was applied for predicting impaired hyperemic MBF (≤2.30 mL/min per g) from corresponding PET scans. The performance of the ML score was compared with CCTA reads and noninvasive FFR derived from CCTA (FFRCT).

RESULTS

One hundred thirty-nine (23.9%) vessels had FFR-defined ischemia, and 195 (33.6%) vessels had impaired hyperemic MBF. For the prediction of FFR-defined ischemia, the ML score yielded an area under the receiver-operating characteristic curve of 0.92, which was significantly higher than that of visual stenosis grade (0.84; P<0.001) and comparable with that of FFRCT (0.93; P=0.34). Quantitative percent diameter stenosis and low-density noncalcified plaque volume had the greatest ML feature importance for predicting FFR-defined ischemia. When applied for impaired MBF prediction, the ML score exhibited an area under the receiver-operating characteristic curve of 0.80; significantly higher than visual stenosis grade (area under the receiver-operating characteristic curve 0.74; P=0.02) and comparable with FFRCT (area under the receiver-operating characteristic curve 0.77; P=0.16).

CONCLUSIONS

An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and impaired MBF by PET, performing superiorly to standard CCTA stenosis evaluation and comparably to FFRCT.

Importance of plaque volume and composition for the prediction of myocardial ischaemia using sequential coronary computed tomography angiography/positron emission tomography imaging

AIMS

Coronary atherosclerosis with a large necrotic core has been postulated to reduce the vasodilatory capacity of vascular tissue. In the present analysis, we explored whether total plaque volume and necrotic core volume on coronary computed tomography angiography (CCTA) are independently associated with myocardial ischaemia on positron emission tomography (PET).

METHODS AND RESULTS

From a registry of symptomatic patients with suspected coronary artery disease and clinically indicated CCTA with sequential [15O]H2O PET myocardial perfusion imaging, we quantitatively measured diameter stenosis, total and compositional plaque volumes on CCTA. Primary endpoint was myocardial ischaemia on PET, defined as an absolute stress myocardial blood flow ≤2.4 mL/g/min in ≥1 segment. Multivariable prediction models for myocardial ischaemia were consecutively created using logistic regression analysis (stenosis model: diameter stenosis ≥50%; plaque volume model: +total plaque volume; plaque composition model: +necrotic core volume). A total of 493 patients (mean age 63 ± 8 years, 54% men) underwent sequential CCTA/PET imaging. In 153 (31%) patients, myocardial ischaemia was detected on PET. Diameter stenosis ≥50% (P < 0.001) and necrotic core volume (P = 0.029) were independently associated with myocardial ischaemia, while total plaque volume showed borderline significance (P = 0.052). The plaque composition model (χ2 = 169) provided incremental value for the prediction of ischaemia when compared with the stenosis model (χ2 = 138, P < 0.001) and plaque volume model (χ2 = 164, P = 0.021).

CONCLUSION

The volume of necrotic core on CCTA independently and incrementally predicts myocardial ischaemia on PET, beyond diameter stenosis alone.

Atherosclerotic plaque characteristics on quantitative coronary computed tomography angiography associated with ischemia on positron emission tomography in diabetic patients

Patients with diabetes mellitus (DM) may show diffuse coronary artery atherosclerosis on coronary computed tomography angiography (CTA). The present study aimed at quantification of atherosclerotic plaque with CTA and its association with myocardial ischemia on positron emission tomography (PET) in DM patients. Of 922 symptomatic outpatients without previously known coronary artery disease who underwent CTA, 115 with DM (mean age 65 ± 8 years, 58% male) who had coronary atherosclerosis and underwent both quantified CTA (QCTA) and PET were included in the study. QCTA analysis was performed on a per-vessel basis and the most stenotic lesion of each vessel was considered. Myocardial ischemia on PET was based on absolute myocardial blood flow at stress ≤ 2.4 ml/g/min. Of the 345 vessels included in the analysis, 135 (39%) had flow-limiting stenosis and were characterized by having longer lesions, higher plaque volume, more extensive plaque burden and higher percentage of dense calcium (37 ± 22% vs 28 ± 22%, p = 0.001). On univariable analysis, QCTA parameters indicating the degree of stenosis, the plaque extent and composition were associated with presence of ischemia. The addition of the QCTA degree of stenosis parameters (x2 36.45 vs 88.18, p < 0.001) and the QCTA plaque extent parameters (x2 88.18 vs 97.44, p = 0.01) to a baseline model increased the association with ischemia. In DM patients, QCTA variables of vessel stenosis, plaque extent and composition are associated with ischemia on PET and characterize the hemodynamic significant atherosclerotic lesion.

Deep learning-based atherosclerotic coronary plaque segmentation on coronary CT angiography

OBJECTIVES

Volumetric evaluation of coronary artery disease (CAD) allows better prediction of cardiac events. However, CAD segmentation is labor intensive. Our objective was to create an open-source deep learning (DL) model to segment coronary plaques on coronary CT angiography (CCTA).

METHODS

Three hundred eight individuals' 894 CCTA scans with 3035 manually segmented plaques by an expert reader (considered as ground truth) were used to train (186/308, 60%), validate (tune, 61/308, 20%), and test (61/308, 20%) a 3D U-net model. We also evaluated the model on an external test set of 50 individuals with vulnerable plaques acquired at a different site. Furthermore, we applied transfer learning on 77 individuals' data and re-evaluated the model's performance using intra-class correlation coefficient (ICC).

RESULTS

On the test set, DL outperformed the currently used minimum cost approach method to quantify total: ICC: 0.88 [CI: 0.85-0.91] vs. 0.63 [CI: 0.42-0.76], noncalcified: 0.84 [CI: 0.80-0.88] vs. 0.45 [CI: 0.26-0.59], calcified: 0.99 [CI: 0.98-0.99] vs. 0.96 [CI: 0.94-0.97], and low attenuation noncalcified: 0.25 [CI: 0.13-0.37] vs. -0.01 [CI: -0.13 to 0.11] plaque volumes. On the external dataset, substantial improvement was observed in DL model performance after transfer learning, total: 0.62 [CI: 0.01-0.84] vs. 0.94 [CI: 0.87-0.97], noncalcified: 0.54 [CI: -0.04 to 0.80] vs. 0.93 [CI: 0.86-0.96], calcified: 0.91 [CI:0.85-0.95] vs. 0.95 [CI: 0.91-0.97], and low attenuation noncalcified 0.48 [CI: 0.18-0.69] vs. 0.86 [CI: 0.76-0.92].

CONCLUSIONS

Our open-source DL algorithm achieved excellent agreement with expert CAD segmentations. However, transfer learning may be required to achieve accurate segmentations in the case of different plaque characteristics or machinery.

KEY POINTS

• Deep learning 3D U-net model for coronary segmentation achieves comparable results with expert readers' volumetric plaque quantification. • Transfer learning may be needed to achieve similar results for other scanner and plaque characteristics. • The developed deep learning algorithm is open-source and may be implemented in any CT analysis software.

The Perivascular Fat Attenuation Index Improves the Diagnostic Performance for Functional Coronary Stenosis

Background: Coronary computed tomography angiography (CCTA) is an established first-line test in the investigation of patients with suspected coronary artery disease (CAD), while the perivascular fat attenuation index (FAI) derived from CT seems to be a feasible and efficient tool for the identification of ischemia. The association between the FAI and lesion-specific ischemia as assessed by fractional flow reserve (FFR) remains unclear. Methods: In a total of 261 patients, 294 vessels were assessed for CCTA stenosis, vessel-specific FAI, lesion-specific FAI, and plaque characteristics. The diagnostic accuracies of each parameter and the combined approach were analyzed via the receiver operating characteristic curve (ROC) with FFR as the reference standard. The determinants of FAI were statistically analyzed. Results: The cutoff values of vessel-specific FAI and lesion-specific FAI scores calculated according to the Youden index were −70.97 and −73.95 HU, respectively. No significant differences were noted between them; however, they exhibited a strong correlation. No significant differences were noted between the area under the curve (AUC) scores of vessel-specific FAI (0.677), lesion-specific FAI (0.665), and CCTA (0.607) (p > 0.05 for all) results. The addition of two FAI measures to the CCTA showed improvements in the discrimination (AUC) and reclassification ability (relative integrated discrimination improvement (IDI) and category-free net reclassification index (NRI)), vessel-specific FAI (AUC, 0.696; NRI, 49.6%; IDI, 5.9%), and lesion-specific FAI scores (AUC, 0.676; NRI, 43.3%; IDI, 5.4%); (p < 0.01 for all). Multivariate analysis revealed that low-attenuation plaque (LAP) volume was an independent predictor of two FAI measures. Conclusion: The combined approach of adding vessel-specific FAI or lesion-specific FAI scores could improve the identification of ischemia compared with CCTA alone. The LAP volume was the independent risk factor for both tools.

Differences in Plaque Characteristics and Myocardial Mass

Background

The mechanism of the fractional flow reserve (FFR) difference according to sex has not been clearly understood.

Objectives

This study sought to evaluate sex differences in coronary stenosis, plaque characteristics, and left ventricular (LV) mass and their implications for physiological significance.

Methods

This was a post hoc analysis of a pooled population of multicenter, international prospective cohorts. Patients (166 women and 489 men) underwent coronary computed tomography angiography (CCTA) within 90 days before invasive FFR measurements were included. The minimal lumen area, percent of plaque burden, whole vessel plaque volume by composition, high-risk plaque characteristics, and LV mass were analyzed from CCTA images.

Results

Among 1,188 vessels analyzed, the FFR value was higher in women than that in men (0.85 ± 0.13 vs 0.82 ± 0.14; P = 0.001) despite a similar percentage of diameter stenosis between the sexes (45.9% ± 18.9% vs 46.1% ± 17.7%; P = 0.920). The composition of fibrofatty plaque + necrotic core (13.1% ± 16.9% vs 21.2% ± 19.9%; P < 0.001) and frequencies of low attenuation plaque (12.7% vs 24.5%; P < 0.001) and positive remodeling (33.8% vs 45.5%; P = 0.001) were lower in women than in men. Vessel, plaque, and lumen volumes were significantly smaller in women than that in men (all P < 0.001); however, no sex difference was observed in any of these parameters after adjustment for LV mass (all P > 0.10). Sex was not an independent predictor of the FFR value after adjustment for stenosis severity, plaque characteristics, and LV mass.

Conclusions

Higher FFR values for the same stenosis severity in women can be explained by fewer high-risk plaque characteristics and smaller myocardial mass in women than that in men. (CCTA-FFR Registry for Risk Prediction; NCT04037163)

Myocardial Strain Imaging With Electrocardiogram-Gated and Coherent Compounding for Early Diagnosis of Coronary Artery Disease

Myocardial elastography (ME) is an ultrasound-based technique that uses radiofrequency signals for 2-D cardiac motion tracking and strain imaging at a high frame rate. Early diagnosis of coronary artery disease (CAD) is critical for timely treatment and improvement of patient outcome. The objective of this study was to assess the performance of ME radial and circumferential strains in the detection and characterization of CAD in patients. In this study, 86 patients suspected of CAD were imaged with ME prior to invasive coronary angiography (ICA). End-systolic radial and circumferential left ventricular strains were estimated in all patients in each of their perfusion territories: left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA). ME radial strains were capable of differentiating the obstructive CAD group (55.3 ± 29.8%) from the non-obstructive CAD (72.5 ± 46.8%, p < 0.05) and no CAD groups (73.4 ± 30.4%, p < 0.05) in the RCA territory. ME circumferential strains were capable of differentiating the obstructive CAD group (-3.1 ± 7.5%) from the non-obstructive CAD (-7.2 ± 6.8%, p < 0.05) and normal (-6.9 ± 8.0%, p < 0.05) groups in the LAD territory and to differentiate the normal group (-17.1 ± 8.2%) from the obstructive (-12.8 ± 7.2%, p < 0.05) and non-obstructive CAD (-13.6 ± 8.5%, p < 0.05) groups in the RCA territory. ME circumferential strain performed better than ME radial strain in differentiating normal, non-obstructive and obstructive perfusion territories. In the LCX territory, both ME radial and circumferential strains decreased when the level of stenosis was higher. However, it was not statistically significant. The findings presented herein indicate that ME radial and circumferential estimation obtained from ECG-gated and compounded acquisitions is a promising tool for early, non-invasive and radiation-free detection of CAD in patients.

Pericoronary fat attenuation index and coronary plaque quantified from coronary computed tomography angiography identify ischemia-causing lesions

BACKGROUND

The association between pericoronary fat attenuation index (FAI), plaque characteristics, and lesion-specific ischemia identified by fractional flow reserve (FFR) remains unclear.

METHODS

Coronary computed tomography angiography (CCTA) stenosis, FAI, plaque characteristics, FFR derived from computed tomography (FFR_CT) and FFR were assessed in 280 vessels of 247 patients. Stenosis ≥50% was considered obstructive. Optimal thresholds of FAI and plaque variables were defined by the area under the receiver-operating characteristics curve (AUC) analysis. Ischemia was defined by FFR ≤ 0.80.

RESULTS

FAI ≥ -71.9 HU, low-attenuation plaque (LAP) ≥ 49.62 mm³ and aggregate plaque volume (APV) ≥ 28.91% predicted ischemia independent of other plaque characteristics. The addition of FAI ≥ -71.9 HU improved discrimination (AUC, 0.720 vs. 0.674, P = 0.035) and reclassification abilities (category-free net reclassification index [NRI], 0.470, P < 0.001; relative integrated discrimination improvement [IDI], 0.047, P < 0.001) of ischemia compared with stenosis evaluation alone, with further discrimination (AUC, 0.772 vs. 0.720, P = 0.028) and reclassification abilities (NRI, 0.385, P = 0.001; relative IDI, 0.077, P < 0.001) of ischemia by adding information regarding LAP ≥49.62 mm³ + APV ≥ 28.91%. And the diagnostic performance of combination approach was comparable to that of FFR_CT alone (AUC, 0.772 vs. 0.762, P = 0.771).

CONCLUSIONS

Stenosis severity, FAI, plaque characteristics predicted lesion-specific ischemia. The combination of FAI and plaque assessment improved the discrimination of ischemia compared with stenosis assessment alone.

Association of Plaque Location and Vessel Geometry Determined by Coronary Computed Tomographic Angiography With Future Acute Coronary Syndrome-Causing Culprit Lesions

IMPORTANCE

Distinct plaque locations and vessel geometric features predispose to altered coronary flow hemodynamics. The association between these lesion-level characteristics assessed by coronary computed tomographic angiography (CCTA) and risk of future acute coronary syndrome (ACS) is unknown.

OBJECTIVE

To examine whether CCTA-derived adverse geometric characteristics (AGCs) of coronary lesions describing location and vessel geometry add to plaque morphology and burden for identifying culprit lesion precursors associated with future ACS.

DESIGN, SETTING, AND PARTICIPANTS

This substudy of ICONIC (Incident Coronary Syndromes Identified by Computed Tomography), a multicenter nested case-control cohort study, included patients with ACS and a culprit lesion precursor identified on baseline CCTA (n = 116) and propensity score-matched non-ACS controls (n = 116). Data were collected from July 20, 2012, to April 30, 2017, and analyzed from October 1, 2020, to October 31, 2021.

EXPOSURES

Coronary lesions were evaluated for the following 3 AGCs: (1) distance from the coronary ostium to lesion; (2) location at vessel bifurcations; and (3) vessel tortuosity, defined as the presence of 1 bend of greater than 90° or 3 curves of 45° to 90° using a 3-point angle within the lesion.

MAIN OUTCOMES AND MEASURES

Association between lesion-level AGCs and risk of future ACS-causing culprit lesions.

RESULTS

Of 548 lesions, 116 culprit lesion precursors were identified in 116 patients (80 [69.0%] men; mean [SD], age 62.7 [11.5] years). Compared with nonculprit lesions, culprit lesion precursors had a shorter distance from the ostium (median, 35.1 [IQR, 23.6-48.4] mm vs 44.5 [IQR, 28.2-70.8] mm), more frequently localized to bifurcations (85 [73.3%] vs 168 [38.9%]), and had more tortuous vessel segments (5 [4.3%] vs 6 [1.4%]; all P < .05). In multivariable Cox regression analysis, an increasing number of AGCs was associated with a greater risk of future culprit lesions (hazard ratio [HR] for 1 AGC, 2.90 [95% CI, 1.38-6.08]; P = .005; HR for ≥2 AGCs, 6.84 [95% CI, 3.33-14.04]; P < .001). Adverse geometric characteristics provided incremental discriminatory value for culprit lesion precursors when added to a model containing stenosis severity, adverse morphological plaque characteristics, and quantitative plaque characteristics (area under the curve, 0.766 [95% CI, 0.718-0.814] vs 0.733 [95% CI, 0.685-0.782]). In per-patient comparison, patients with ACS had a higher frequency of lesions with adverse plaque characteristics, AGCs, or both compared with control patients (≥2 adverse plaque characteristics, 70 [60.3%] vs 50 [43.1%]; ≥2 AGCs, 92 [79.3%] vs 60 [51.7%]; ≥2 of both, 37 [31.9%] vs 20 [17.2%]; all P < .05).

CONCLUSIONS AND RELEVANCE

These findings support the concept that CCTA-derived AGCs capturing lesion location and vessel geometry are associated with risk of future ACS-causing culprit lesions. Adverse geometric characteristics may provide additive prognostic information beyond plaque assessment in CCTA.

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

BACKGROUND

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Change in Computed Tomography-Derived Fractional Flow Reserve Across the Lesion Improve the Diagnostic Performance of Functional Coronary Stenosis

Aims: This study sought to evaluate the diagnostic performance of change in computed tomography-derived fractional flow reserve (CT-FFR) across the lesion (ΔCT-FFR) for identifying ischemia lesions with FFR as the reference standard.

Methods: Patients who underwent coronary CT angiography (CCTA) and FFR measurement within 1 week from December 2018 to December 2019 were retrospectively enrolled. CT-FFR within 2 cm distal to the lesion, ΔCT-FFR and plaque characteristics were analyzed. The diagnostic accuracy of CCTA (coronary stenosis ≥ 50%), CT-FFR ≤ 0.80, and ΔCT-FFR ≥ 0.15 (based on the largest Youden index) were assessed with FFR as the reference standard. The relationship between plaque characteristics and ΔCT-FFR was analyzed.

Results: The specificity of ΔCT-FFR and CT-FFR were 70.8 and 67.4%, respectively, which were both higher than CCTA (39.3%) (both P &lt; 0.001), while there were no statistical significance in sensitivity among the three (84.5, 77.4, 88.1%, respectively; P = 0.08). The area under the curves (AUCs) of ΔCT-FFR and CT-FFR were 0.803 and 0.743, respectively, which were both higher than that of CCTA (0.637) (both P &lt; 0.05), and the AUC of ΔCT-FFR was higher than that of CT-FFR (P &lt; 0.001). Multivariable analysis showed that low-attenuation plaque (LAP) volume (odds ratio [OR], 1.006) and plaque length (OR, 1.021) were independently correlated with ΔCT-FFR (both P &lt; 0.05).

Conclusions: CT-FFR and ΔCT-FFR and here especially the ΔCT-FFR could improve the diagnostic performance of ischemia compared with CCTA alone. LAP volume and plaque length were the independent risk factors of ΔCT-FFR.

Quantitative plaque assessment by coronary computed tomography angiography: An up-to-date review

Coronary computed tomography angiography has an emerging role in the diagnostic workup of coronary artery disease. Due to its high sensitivity and negative predictive value, coronary computed tomography angiography can rule out obstructive coronary artery diseases and substitute invasive coronary angiography in many cases. In addition, coronary computed tomography angiography provides a unique information beyond stenosis grading as it can visualize atherosclerosis and quantify its extent. Qualitative and quantitative plaque assessment provides an incremental value in the prediction of future major adverse cardiac events. Moreover, determining adverse plaque features has a potential to identify advanced atherosclerosis and patients at increased risk of acute coronary syndrome. Nevertheless, challenges may emerge with the process of quantifying coronary plaques due to limited reproducibility, lack of automated, standardized and validated techniques. Therefore, reliable quantified data are scarce due to the various computed tomography scanners and software platforms and investigations with small sample sizes. Radiomics and machine learning-based image processing methods are relatively new in the field of cardiovascular plaque imaging. These techniques hold the promise to improve diagnostic performance, reproducibility and prognostic value of computed tomography based plaque assessment.

Interactions Between Morphological Plaque Characteristics and Coronary Physiology: From Pathophysiological Basis to Clinical Implications

High-risk coronary plaque refers to a distinct set of plaque characteristics prone to future coronary events. Coronary physiology represents a group of indexes reflective of the local physiological environment and hemodynamic changes in the macrovascular and microvascular system. Although a large body of evidence has supported the clinical relevance of these 2 factors, currently, identifying plaque morphology cannot reliably capture the lesion subset that causes hard events. Also, the guideline-directed approach based on physiological indexes cannot fully predict and prevent clinical events. In parallel, there is accumulating evidence that these 2 aspects of coronary artery disease influence each other with significant clinical implications, despite traditionally being considered to have separate effects on significances, treatments, and outcomes. In this state-of-the-art review, we explore the clinical evidence of pathophysiological interplay of physiological indexes related to local hemodynamics, epicardial stenosis, and microvascular dysfunction with plaque morphological characteristics that provide a better understanding of the nature of coronary events. Furthermore, we examine the emerging data on the complementary role between plaque morphology and coronary physiology in prognostication and how to apply this concept to overcome the limitations of individual assessment alone. Finally, we propose the potential benefit of integrative assessment of coronary anatomy, plaque quantity and quality, and physiological aspects of a target lesion and vessels for personalized risk profiling and optimized treatment strategy.

Impact of vascular morphology and plaque characteristics on computed tomography derived fractional flow reserve in early stage coronary artery disease

BACKGROUND

Computed-tomography (CT) derived fractional-flow-reserve (FFR_CT) gradually may decrease from proximal to distal vessels even without apparent coronary artery disease (CAD). It may be unclear whether the decrease in FFR_CT at the distal coronal artery is physiological or due to stenosis. We decided to study predictive factors of an FFR_CT decline below the pathological value of 0.80 in no-apparent CAD.

METHODS

A total of 150 consecutive patients who had both CT angiography coupled to FFR_CT analysis and invasive angiogram showing < 20% coronary stenosis were included. Vessels were divided into two groups according to FFR_CT at the distal vessel: FFR_CT > 0.80 (n = 317) and FFR_CT ≤ 0.80 (n = 114). ΔFFR_CT was defined as the change in FFR_CT from proximal to distal vessel. Vessel morphology (vessel length and lumen volume) and plaque characteristics [low-attenuation plaque volume, intermediate-attenuation (IAP) plaque volume, and calcified plaque volume] were evaluated.

RESULTS

FFR_CT decreased from proximal to distal for the three major vessels in both FFR_CT > 0.80 and FFR_CT ≤ 0.80. Compared to FFR_CT > 0.80, IAP volume was significantly higher in all three major vessels in FFR_CT ≤ 0.80. ΔFFR_CT was correlated with vessel length and lumen volume in FFR_CT > 0.80, whereas ΔFFR_CT was correlated with IAP volume in FFR_CT ≤ 0.80. IAP volume above 44.8 mm³ was the strongest predictor of distal FFR_CT of ≤ 0.80.

CONCLUSIONS

The presence of IAP is a major predictor of gradual decrease of FFR_CT below 0.80 in no-apparent CAD vessels. Vessel morphology and plaque characteristics should be considered when interpreting FFR_CT.

Computed Tomography Coronary Plaque Characteristics Predict Ischemia Detected by Invasive Fractional Flow Reserve

PURPOSE

Coronary computed tomography angiography (CCTA) plaque quantification has been proposed to be of incremental value in the prediction of ischemia, although prior studies have shown conflicting results. We aimed to determine whether CCTA plaque features assessed on a commercial vendor platform predict invasive fractional flow reserve (FFR)/instantaneous wave-free ratio (IFR).

METHODS

Consecutive patients who underwent CCTA for evaluation of suspected stable coronary artery disease followed by invasive coronary physiology testing within 60 days at a single academic center were identified retrospectively. Semiautomated plaque quantification of the vessel proximal to the location of FFR/IFR measurement was carried out in TeraRecon, along with simple visual assessment for high-risk plaque features of positive remodeling, spotty calcification, low-attenuation plaque (LAP), and lesion length. Ischemia was defined by FFR ≤0.80 or IFR ≤0.89.

RESULTS

A total of 134 patients (62% male, mean age 62±10 y) were included in this study. On univariate logistic regression, the following visual plaque analysis parameters were predictive of ischemia: positive remodeling (odds ratio [OR] with 95% confidence interval [CI]: 4.96; 2.25-10.95; P<0.001), lesion length (OR for every 1 mm with 95% CI: 1.24; 1.14-1.34; P<0.001), spotty calcification (OR with 95% CI: 6.67; 1.67-26.64; P=0.007), and LAP (OR with 95% CI: 30; 3.78-246; P=0.001). None of the semiautomated plaque quantification parameters, such as noncalcified plaque volume or LAP volume, were predictive of ischemia. On stepwise multivariable logistic regression, lesion length (OR with 95% CI: 1.25; 1.14-1.37; P<0.0001) and LAP (OR with 95% CI: 43; 4.4-438; P=0.001) were significant predictors of ischemia, improving the area under the curve of CCTA from 0.53 to 0.87.

CONCLUSIONS

Simple visual plaque assessment for high-risk plaque features improved the performance of CCTA to predict ischemia. Semiautomated plaque quantification performed on a commercial vendor platform was not predictive of ischemia.

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Effect of plaque compositions on fractional flow reserve in a fluid-structure interaction analysis

Coronary artery disease involves the reduction of blood flow to the myocardium due to atherosclerotic plaques. The findings of myocardial ischemia may indicate severe coronary stenosis, but many studies have demonstrated a mismatch between lumen stenosis and fractional flow reserve (FFR). Recently, some clinical studies have found that the composition of atherosclerotic plaques may be a potential missing link between stenosis and ischemia. To investigate the relationship between myocardial ischemia and plaque composition, we have developed and adopted a new fluid-structure interaction (FSI) patient-specific coronary plaque model, based on computed tomography angiography data, to assess the impact on FFR as a biomechanical indicator of ischemia. A total of 180 analyses have been performed in 3D-FSI coronary artery disease models based on plaque compositions, plaque location, and stenosis degree. Hemodynamic analysis of simulation results and comparisons with other methods has been conducted to validate our models. Our results have successfully verified that the different compositions of plaques have resulted in differences in the calculated FFR. The mean FFR values with lipid plaques are [Formula: see text] as compared to the mean FFR values in lesions with fibrous plaques [Formula: see text] and calcified plaques [Formula: see text]. Besides, FFR differences between the three different plaque compositions have been shown to increase as the diameter stenosis increased. Plaque composition affects vascular stiffness and vascular dilation ability, and thereby affects the stenosis degree, resulting in abnormal FFR leading to myocardial ischemia. This interrelationship can help to diagnose the cause of high-risk coronary artery disease, leading to myocardial ischemia.

Physiological significance of pericoronary inflammation in epicardial functional stenosis and global coronary flow reserve

Both fractional flow reserve (FFR) and global coronary flow reserve (g-CFR) provide prognostic information in patients with stable coronary artery disease (CAD). Inflammation plays a vital role in impaired endothelial dysfunction and atherosclerotic progression, potentially predicting cardiovascular mortality. This study aimed to evaluate the physiological significance of pericoronary adipose tissue inflammation assessed by CT attenuation (PCATA) in epicardial functional stenosis severity and g-CFR in patients with CAD. A total of 131 CAD patients with a single de novo epicardial coronary stenosis who underwent coronary CT-angiography (CCTA), phase-contrast cine-magnetic resonance imaging (PC-CMR) and FFR measurement were studied. PCATA was assessed using the mean CT attenuation value. G-CFR was obtained by quantifying absolute coronary sinus flow (ml/min/g) by PC-CMR at rest and during maximum hyperemia. Median FFR, g-CFR, and PCATA values were 0.75, 2.59, and − 71.3, respectively. Serum creatinine, NT-proBNP, left ventricular end-diastolic volume, and PCATA were independently associated with g-CFR. PCATA showed a significant incremental predictive efficacy for impaired g-CFR (< 2.0) when added to the clinical risk model. PCATA was significantly associated with g-CFR, independent of FFR. Our results suggest the pathophysiological mechanisms linking perivascular inflammation with g-CFR in CAD patients.

Measurement of compensatory arterial remodelling over time with serial coronary computed tomography angiography and 3D metrics

AIMS

The magnitude of alterations in which coronary arteries remodel and narrow over time is not well understood. We aimed to examine changes in coronary arterial remodelling and luminal narrowing by three-dimensional (3D) metrics from serial coronary computed tomography angiography (CCTA).

METHODS AND RESULTS

From a multicentre registry of patients with suspected coronary artery disease who underwent clinically indicated serial CCTA (median interscan interval = 3.3 years), we quantitatively measured coronary plaque, vessel, and lumen volumes on both scans. Primary outcome was the per-segment change in coronary vessel and lumen volume from a change in plaque volume, focusing on arterial remodelling. Multivariate generalized estimating equations including statins were calculated comparing associations between groups of baseline percent atheroma volume (PAV) and location within the coronary artery tree. From 1245 patients (mean age 61 ± 9 years, 39% women), a total of 5721 segments were analysed. For each 1.00 mm3 increase in plaque volume, the vessel volume increased by 0.71 mm3 [95% confidence interval (CI) 0.63 to 0.79 mm3, P < 0.001] with a corresponding reduction in lumen volume by 0.29 mm3 (95% CI -0.37 to -0.21 mm3, P < 0.001). Serial 3D arterial remodelling and luminal narrowing was similar in segments with low and high baseline PAV (P ≥ 0.496). No differences were observed between left main and non-left main segments, proximal and distal segments and side branch and non-side branch segments (P ≥ 0.281).

CONCLUSIONS

Over time, atherosclerotic coronary plaque reveals prominent outward arterial remodelling that co-occurs with modest luminal narrowing. These findings provide additional insight into the compensatory mechanisms involved in the progression of coronary atherosclerosis.

SIRM-SIC appropriateness criteria for the use of Cardiac Computed Tomography. Part 1: Congenital heart diseases, primary prevention, risk assessment before surgery, suspected CAD in symptomatic patients, plaque and epicardial adipose tissue characterization, and functional assessment of stenosis

In the past 20 years, Cardiac Computed Tomography (CCT) has become a pivotal technique for the noninvasive diagnostic work-up of coronary and cardiac diseases. Continuous technical and methodological improvements, combined with fast growing scientific evidence, have progressively expanded the clinical role of CCT. Recent large multicenter randomized clinical trials documented the high prognostic value of CCT and its capability to increase the cost-effectiveness of the management of patients with suspected CAD. In the meantime, CCT, initially perceived as a simple non-invasive technique for studying coronary anatomy, has transformed into a multiparametric "one-stop-shop" approach able to investigate the heart in a comprehensive way, including functional, structural and pathophysiological biomarkers. In this complex and revolutionary scenario, it is urgently needed to provide an updated guide for the appropriate use of CCT in different clinical settings. This manuscript, endorsed by the Italian Society of Medical and Interventional Radiology (SIRM) and by the Italian Society of Cardiology (SIC), represents the first of two consensus documents collecting the expert opinion of Radiologists and Cardiologists about current appropriate use of CCT.

Exploring the diagnostic effectiveness for myocardial ischaemia based on CCTA myocardial texture features

BACKGROUND

To explore the characteristics of myocardial textures on coronary computed tomography angiography (CCTA) images in patients with coronary atherosclerotic heart disease, a classification model was established, and the diagnostic effectiveness of CCTA for myocardial ischaemia patients was explored.

METHODS

This was a retrospective analysis of the CCTA images of 155 patients with clinically diagnosed coronary heart disease from September 2019 to January 2020, 79 of whom were considered positive (myocardial ischaemia) and 76 negative (normal myocardial blood supply) according to their clinical diagnoses. By using the deep learning model-based CQK software, the myocardium was automatically segmented from the CCTA images and used to extract texture features. All patients were randomly divided into a training cohort and a test cohort at a 7:3 ratio. The Spearman correlation and least absolute shrinkage and selection operator (LASSO) method were used for feature selection. Based on the selected features of the training cohort, a multivariable logistic regression model was established. Finally, the test cohort was used to verify the regression model.

RESULTS

A total of 387 features were extracted from the CCTA images of the 155 coronary heart disease patients. After performing dimensionality reduction with the Spearman correlation and LASSO, three texture features were selected. The accuracy, area under the curve, specificity, sensitivity, positive predictive value and negative predictive value of the constructed multivariable logistic regression model with the test cohort were 0.783, 0.875, 0.733, 0.875, 0.650 and 0.769, respectively.

CONCLUSION

CCTA imaging texture features of the myocardium have potential as biomarkers for diagnosing myocardial ischaemia.

ANMCO POSITION PAPER: Prognostic and therapeutic relevance of non-obstructive coronary atherosclerosis

Atherosclerosis often affects the coronary arterial tree. Frequently the disease does not translate in significant narrowing of the vessels, thus determining only a non-obstructive disease. This condition that is described as non-obstructive coronary artery disease (NobsCAD) should be distinguished from the absence of disease (i.e. smooth coronary arteries) as it carries a specific prognostic value. The detection and reporting of NobsCAD should prompt preventive measures that can be individualized upon the degree of the underlying burden of disease. The accompanying clinical condition, the other cardiovascular risk factors present, and the description of the severity and extent of NobsCAD should provide the framework for an individualized treatment that should also consider the best available scientific evidence and guidelines. The description of NobsCAD represents important information to be collected whenever a coronary angiogram (both invasive and non-invasive) is performed. Treating the patient according to the presence and extent of NobsCAD offers prognostic benefits well beyond those offered by considering only the traditional cardiovascular risk factors. In order to reach this goal, NobsCAD should not be confused with the absence of coronary atherosclerosis or even ignored when detected as if it was a trivial information to provide.