Plasma lipidomics and coronary plaque changes: a substudy of the SMARTool clinical trial.

AIMS: To date, no studies have investigated the association between lipid species and coronary plaque changes over time, quantitatively assessed by serial imaging. We aimed to prospectively determine the association between lipid species quantified by a plasma lipidomic analysis and coronary plaque changes according to composition assessed by a quantitative serial analysis of coronary computed tomography angiography (CTA). METHODS AND RESULTS: Patients with suspected coronary artery disease (CAD) undergoing baseline coronary CTA were prospectively enrolled by seven EU centres in the SMARTool study and submitted to clinical, molecular, and coronary CTA re-evaluation at follow-up (an inter-scan period of 6.39 ± 1.17 years). Out of 202 patients who were analysed in the SMARTool main clinical study, a lipidomic analysis was performed in 154 patients before the baseline coronary CTA, and this group was included in the present study. A quantitative CTA analysis was performed by using a separate core laboratory blinded from clinical data. In the univariable analysis, it was found that no lipid species were significantly associated with annual total and calcified plaque changes. After adjusting for clinical variables at baseline and statin use, it was found that three lipid species were significantly associated with non-calcified plaque progression. In detail, cholesteryl ester(20:3), sphingomyelin (SM)(40:3), and SM(41:1) were found to be positively related to non-calcified plaque progression (Bonferroni-adjusted P-values = 0.005, 0.016, and 0.004, respectively). CONCLUSION: The current study showed an independent relationship between specific lipid species determined by a plasma lipidomic analysis and non-calcified coronary plaque progression assessed by a serial, quantitative coronary CTA analysis.

Association of Circulating Neutrophils with Relative Volume of Lipid-Rich Necrotic Core of Coronary Plaques in Stable Patients: A Substudy of SMARTool European Project.

BACKGROUND AND AIMS: Coronary atherosclerosis is a chronic non-resolving inflammatory process wherein the interaction of innate immune cells and platelets plays a major role. Circulating neutrophils, in particular, adhere to the activated endothelium and migrate into the vascular wall, promoting monocyte recruitment and influencing plaque phenotype and stability at all stages of its evolution. We aimed to evaluate, by flow cytometry, if blood neutrophil number and phenotype-including their phenotypic relationships with platelets, monocytes and lymphocytes-have an association with lipid-rich necrotic core volume (LRNCV), a generic index of coronary plaque vulnerability, in a group of stable patients with chronic coronary syndrome (CCS). METHODS: In 55 patients, (68.53 ± 1.07 years of age, mean ± SEM; 71% male), the total LRNCV in each subject was assessed by a quantitative analysis of all coronary plaques detected by computed tomography coronary angiography (CTCA) and was normalized to the total plaque volume. The expression of CD14, CD16, CD18, CD11b, HLA-DR, CD163, CCR2, CCR5, CX3CR1, CXCR4 and CD41a cell surface markers was quantified by flow cytometry. Adhesion molecules, cytokines and chemokines, as well as MMP9 plasma levels, were measured by ELISA. RESULTS: On a per-patient basis, LRNCV values were positively associated, by a multiple regression analysis, with the neutrophil count (n°/µL) (p = 0.02), neutrophil/lymphocyte ratio (p = 0.007), neutrophil/platelet ratio (p = 0.01), neutrophil RFI CD11b expression (p = 0.02) and neutrophil-platelet adhesion index (p = 0.01). Significantly positive multiple regression associations of LRNCV values with phenotypic ratios between neutrophil RFI CD11b expression and several lymphocyte and monocyte surface markers were also observed. In the bivariate correlation analysis, a significantly positive association was found between RFI values of neutrophil-CD41a+ complexes and neutrophil RFI CD11b expression (p < 0.0001). CONCLUSIONS: These preliminary findings suggest that a sustained increase in circulating neutrophils, together with the up-regulation of the integrin/activation membrane neutrophil marker CD11b may contribute, through the progressive intra-plaque accumulation of necrotic/apoptotic cells exceeding the efferocytosis/anti-inflammatory capacity of infiltrating macrophages and lymphocytes, to the relative enlargement of the lipid-rich necrotic core volume of coronary plaques in stable CAD patients, thus increasing their individual risk of acute complication.

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

BACKGROUND AND AIMS: MMP-9 is a predictor of atherosclerotic plaque instability and adverse cardiovascular events, but longitudinal data on the association between MMP9 and coronary disease progression are lacking. This study is aimed at investigating whether MMP9 is associated with atherosclerotic plaque progression and the related molecular basis in stable patients with chronic coronary syndrome (CCS). METHODS: MMP9 serum levels were measured in 157 CCS patients (58 ± 8 years of age; 66% male) undergoing coronary computed tomography angiography at baseline and after a follow up period of 6.5 ± 1.1 years to assess progression of Total, Fibrous, Fibro-fatty, Necrotic Core, and Dense Calcium plaque volumes (PV). Gene expression analysis was evaluated in whole blood using a transcriptomic approach by RNA-seq. RESULTS: At multivariate analysis, serum MMP9 was associated with annual change of Total and Necrotic Core PV (Coefficient 3.205, SE 1.321, P = 0.017; 1.449, SE 0.690, P = 0.038, respectively), while MMP9 gene expression with Necrotic Core PV (Coefficient 70.559, SE 32.629, P = 0.034), independently from traditional cardiovascular risk factors, medications, and presence of obstructive CAD. After transcriptomic analysis, MMP9 expression was linked to expression of genes involved in the innate immunity. CONCLUSIONS: Among CCS patients, MMP9 is an independent predictive marker of progression of adverse coronary plaques, possibly reflecting the activity of inflammatory pathways conditioning adverse plaque phenotypes. Thus, blood MMP9 might be used for the identification of patients with residual risk even with optimal management of classical cardiovascular risk factors who may derive the greatest benefit from targeted anti-inflammatory drugs.

Erythro-Magneto-HA-Virosome: A Bio-Inspired Drug Delivery System for Active Targeting of Drugs in the Lungs.

Over the past few decades, finding more efficient and selective administration routes has gained significant attention due to its crucial role in the bioavailability, absorption rate and pharmacokinetics of therapeutic substances. The pulmonary delivery of drugs has become an attractive target of scientific and biomedical interest in the health care research area, as the lung, thanks to its high permeability and large absorptive surface area and good blood supply, is capable of absorbing pharmaceuticals either for local deposition or for systemic delivery. Nevertheless, the pulmonary drug delivery is relatively complex, and strategies to mitigate the effects of mechanical, chemical and immunological barriers are required. Herein, engineered erythrocytes, the Erythro-Magneto-Hemagglutinin (HA)-virosomes (EMHVs), are used as a novel strategy for efficiently delivering drugs to the lungs. EMHV bio-based carriers exploit the physical properties of magnetic nanoparticles to achieve effective targeting after their intravenous injection thanks to an external magnetic field. In addition, the presence of hemagglutinin fusion proteins on EMHVs' membrane allows the DDS to anchor and fuse with the target tissue and locally release the therapeutic compound. Our results on the biomechanical and biophysical properties of EMHVs, such as the membrane robustness and deformability and the high magnetic susceptibility, as well as their in vivo biodistribution, highlight that this bio-inspired DDS is a promising platform for the controlled and lung-targeting delivery of drugs, and represents a valuable alternative to inhalation therapy to fulfill unmet clinical needs.

Bone morphogenetic protein-4 system expression in human coronary artery endothelial and smooth muscle cells under dynamic flow: effect of medicated bioresorbable vascular scaffolds at low and normal shear stress.

Endothelial and smooth muscle cell dysfunction is an early event at the onset of atherosclerosis, a heterogeneous and multifactorial pathology of the vascular wall. Bone morphogenetic protein (BMP)-4, a mechanosensitive autocrine cytokine, and BMPR-1a, BMPR-1b, BMPR-2 specific receptors play a key role in atherosclerotic plaque formation and vascular calcification and BMP4 is regarded as a biomarker of endothelial cell activation. The study aimed to examine the BMP4 system expression by Real-Time PCR in Human Coronary Artery Endothelial (HCAECs) and Smooth Muscle Cells (HCASMCs) under different flow rates determining low or physiological shear stress in the presence/absence of medicated Bioresorbable Vascular Scaffold (BVS). The HCAEC and HCASMC were subjected to 1-10-20 dyne/cm2 shear stress in a laminar flow bioreactor system, with/without BVS+ Everolimus (600 nM). In HCAECs without BVS the BMP4 expression was similar at 1, 20 dyne/cm2 decreasing at 10 dyne/cm2, while adding BVS+ Everolimus, it decreased both at 1, 10 compared to 20 dyne/cm2. In HCASMCs without BVS + Everolimus, the BMP4 system mRNA expression was significantly reduced at 1, 10 dyne/cm2 compared to 20 dyne/cm2, while in the presence of BVS+ Everolimus, higher BMP4 mRNA levels were observed at 10 compared to 1, 20 dyne/cm2. In HCAECs and HCASMCs BMPRs were expressed in all experimental conditions except for BMPR-1a at 1 dyne/cm2 in HCAEC. Significant correlations were found between BMP4 and BMPRs. The more negligible on BMP4 expression due to low shear stress in HCAEC compared to HCASMC and its reduction in the presence of BVS+ Everolimus at low shear stress highlighted the protection of BMP4-mediated against endothelial dysfunction and neoatherogenesis.

Machine Learning Coronary Artery Disease Prediction Based on Imaging and Non-Imaging Data.

The prediction of obstructive atherosclerotic disease has significant clinical meaning for the decision making. In this study, a machine learning predictive model based on gradient boosting classifier is presented, aiming to identify the patients of high CAD risk and those of low CAD risk. The machine learning methodology includes five steps: the preprocessing of the input data, the class imbalance handling applying the Easy Ensemble algorithm, the recursive feature elimination technique implementation, the implementation of gradient boosting classifier, and finally the model evaluation, while the fine tuning of the presented model was implemented through a randomized search optimization of the model's hyper-parameters over an internal 3-fold cross-validation. In total, 187 participants with suspicion of CAD previously underwent CTCA during EVINCI and ARTreat clinical studies and were prospectively included to undergo follow-up CTCA. The predictive model was trained using imaging data (geometrical and blood flow based) and non-imaging data. The overall predictive accuracy of the model was 0.81, using both imaging and non-imaging data. The innovative aspect of the proposed study is the combination of imaging-based data with the typical CAD risk factors to provide an integrated CAD risk-predictive model.

Blood M2-like Monocyte Polarization Is Associated with Calcific Plaque Phenotype in Stable Coronary Artery Disease: A Sub-Study of SMARTool Clinical Trial.

BACKGROUND: Atherosclerosis is a chronic inflammatory disease. The balance between pro- and anti-inflammatory factors, acting on the arterial wall, promotes less or more coronary plaque macro-calcification, respectively. We investigated the association between monocyte phenotypic polarization and CTCA-assessed plaque dense-calcium volume (DCV) in patients with stable coronary artery disease (CAD). METHODS: In 55 patients, individual DCV component was assessed by quantitative CTCA and normalized to total plaque volume. Flow cytometry expression of CD14, CD16, CD18, CD11b, HLA-DR, CD163, CCR2, CCR5, CX3CR1 and CXCR4 was quantified. Adhesion molecules and cytokines were measured by ELISA. RESULTS: DCV values were significantly associated, by multiple regression analysis, with the expression (RFI) of CCR5 (p = 0.04), CX3CR1 (p = 0.03), CCR2 (p = 0.02), CD163 (p = 0.005) on all monocytes, and with the phenotypic M2-like polarization ratio, RFI CCR5/CD11b (p = 0.01). A positive correlation with the increased expression of chemokines receptors CCR2, CCR5 and CX3CR1 on subsets Mon1 was also present. Among cytokines, the ratio between IL-10 and IL-6 was found to be strongly associated with DCV (p = 0.009). CONCLUSIONS: The association between DCV and M2-like phenotypic polarization of circulating monocytes indicates that plaque macro-calcification in stable CAD may be partly modulated by an anti-inflammatory monocyte functional state, as evidenced by cell membrane receptor patterns.

Silencing Survivin: a Key Therapeutic Strategy for Cardiac Hypertrophy.

Cardiac hypertrophy, in its aspects of localized thickening of the interventricular septum and concentric increase of the left ventricle, constitutes a risk factor of heart failure. Myocardial hypertrophy, in the presence of different degree of myocardial fibrosis, is paralleled by significant molecular, cellular, and histological changes inducing alteration of cardiac extracellular matrix composition as well as sarcomeres and cytoskeleton remodeling. Previous studies indicate osteopontin (OPN) and more recently survivin (SURV) overexpression as the hallmarks of heart failure although SURV function in the heart is not completely clarified. In this study, we investigated the involvement of SURV in intracellular signaling of hypertrophic cardiomyocytes and the impact of its transcriptional silencing, laying the foundation for novel target gene therapy in cardiac hypertrophy. Oligonucleotide-based molecules, like theranostic optical nanosensors (molecular beacons) and siRNAs, targeting SURV and OPN mRNAs, were developed. Their diagnostic and therapeutic potential was evaluated in vitro in hypertrophic FGF23-induced human cardiomyocytes and in vivo in transverse aortic constriction hypertrophic mouse model. Engineered erythrocyte was used as shuttle to selectively target and transfer siRNA molecules into unhealthy cardiac cells in vivo. The results highlight how the SURV knockdown could negatively influence the expression of genes involved in myocardial fibrosis in vitro and restores structural, functional, and morphometric features in vivo. Together, these data suggested that SURV is a key factor in inducing cardiomyocytes hypertrophy, and its shutdown is crucial in slowing disease progression as well as reversing cardiac hypertrophy. In the perspective, targeted delivery of siRNAs through engineered erythrocytes can represent a promising therapeutic strategy to treat cardiac hypertrophy. Theranostic SURV molecular beacon (MB-SURV), transfected into FGF23-induced hypertrophic human cardiomyocytes, significantly dampened SURV overexpression. SURV down-regulation determines the tuning down of MMP9, TIMP1 and TIMP4 extracellular matrix remodeling factors while induces the overexpression of the cardioprotective MCAD factor, which counterbalance the absence of pro-survival and anti-apoptotic SURV activity to protect cardiomyocytes from death. In transverse aortic constriction (TAC) mouse model, the SURV silencing restores the LV mass levels to values not different from the sham group and counteracts the progressive decline of EF, maintaining its values always higher with respect to TAC group. These data demonstrate the central role of SURV in the cardiac reverse remodeling and its therapeutic potential to reverse cardiac hypertrophy.

A proof-of-concept study for the prediction of the de-novo atherosclerotic plaque development using finite elements.

The type of the atherosclerotic plaque has significant clinical meaning since plaque vulnerability depends on its type. In this work, we present a computational approach which predicts the development of new plaques in coronary arteries. More specifically, we employ a multi-level model which simulates the blood fluid dynamics, the lipoprotein transport and their accumulation in the arterial wall and the triggering of inflammation using convection-diffusion-reaction equations and in the final level, we estimate the plaque volume which causes the arterial wall thickening. The novelty of this work relies on the conceptual approach that using the information from 94 patients with computed tomography coronary angiography (CTCA) imaging at two time points we identify the correlation of the computational results with the real plaque components detected in CTCA. In the next step, we use these correlations to generate two types of de-novo plaques: calcified and non-calcified. Evaluation of the model's performance is achieved using eleven patients, who present de-novo plaques at the follow-up imaging. The results demonstrate that the computationally generated plaques are associated significantly with the real plaques indicating that the proposed approach could be used for the prediction of specific plaque type formation.

Error Propagation in the Simulation of Atherosclerotic Plaque Growth and the Prediction of Atherosclerotic Disease Progression.

Assessments of coronary artery disease can be achieved using non-invasive computed tomography coronary angiography (CTCA). CTCA can be further used for the 3D reconstruction of the coronary arteries and the development of computational models. However, image acquisition and arterial reconstruction introduce an error which can be propagated, affecting the computational results and the accuracy of diagnostic and prognostic models. In this work, we investigate the effect of an imaging error, propagated to a diagnostic index calculated using computational modelling of blood flow and then to prognostic models based on plaque growth modelling or binary logistic predictive modelling. The analysis was performed utilizing data from 20 patients collected at two time points with interscan period of six years. The collected data includes clinical and risk factors, biological and biohumoral data, and CTCA imaging. The results demonstrated that the error propagated and may have significantly affected some of the final outcomes. The calculated propagated error seemed to be minor for shear stress, but was major for some variables of the plaque growth model. In parallel, in the current analysis SmartFFR was not considerably affected, with the limitation of only one case located into the gray zone.

A specific plasma lipid signature associated with high triglycerides and low HDL cholesterol identifies residual CAD risk in patients with chronic coronary syndrome.

BACKGROUND AND AIMS: Elevated triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) define a specific lipid profile associated with residual coronary artery disease (CAD) risk independently of total cholesterol and low-density lipoprotein cholesterol (LDL-C) levels. Aim of the present study was to assess whether TG/HDL-C ratio, coronary atherosclerosis and their change over time are characterized by a specific lipidomic profiling in stable patients with chronic coronary syndrome (CCS). METHODS: TG/HDL-C ratio was calculated in 193 patients (57.8 ± 7.6 years, 115 males) with CCS characterized by clinical, bio-humoral profiles and cardiac imaging. Patient-specific plasma targeted lipidomics was defined through a high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) strategy. Patients underwent coronary computed tomography angiography (CTA) and an individual CTA risk score, combining extent, severity, composition, and location of plaques, was calculated. All patients entered a follow-up (6.39 ± 1.17 years), including clinical, lipidomics and coronary CTA assessments. RESULTS: Patients were divided in groups according to baseline TG/HDL-C quartiles: IQ (<1.391), IIQ (1.392-2.000), IIIQ (2.001-3.286), and IVQ (≥3.287). A specific pattern of altered lipids, characterized by reduced plasma levels of cholesterol esters, phosphatidylcholines and sphingomyelins, was associated with higher TG/HDL-C both at baseline and follow-up (IVQ vs IQ). The CTA risk score increased over time and this lipid signature was also associated with higher CTA score at follow-up. CONCLUSIONS: In stable CCS, a specific lipidomic signature identifies those patients with higher TG/HDL- C ratio and higher CTA score over time, suggesting possible molecular pathways of residual CAD risk not tackled by current optimal medical treatments.

Triglycerides and low HDL cholesterol predict coronary heart disease risk in patients with stable angina.

We assessed whether high triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) levels, expressed by an increased TG/HDL-C ratio, predict coronary atherosclerotic disease (CAD) outcomes in patients with stable angina. We studied 355 patients (60 ± 9 years, 211 males) with stable angina who underwent coronary computed tomography angiography (CTA), were managed clinically and followed for 4.5 ± 0.9 years. The primary composite outcome was all-cause mortality and non-fatal myocardial infarction. At baseline, the proportion of males, patients with metabolic syndrome, diabetes and obstructive CAD increased across TG/HDL-C ratio quartiles, together with markers of insulin resistance, hepatic and adipose tissue dysfunction and myocardial damage, with no difference in total cholesterol or LDL-C. At follow-up, the global CTA risk score (HR 1.06, 95% confidence interval (CI) 1.03-1.09, P = 0.001) and the IV quartile of the TG/HDL-C ratio (HR 2.85, 95% CI 1.30-6.26, P < 0.01) were the only independent predictors of the primary outcome. The TG/HDL-C ratio and the CTA risk score progressed over time despite increased use of lipid-lowering drugs and reduction in LDL-C. In patients with stable angina, high TG and low HDL-C levels are associated with CAD related outcomes independently of LDL-C and treatments.Trial registration. EVINCI study: ClinicalTrials.gov NCT00979199, registered September 17, 2009; SMARTool study: ClinicalTrials.gov NCT04448691, registered June 26, 2020.

SmartFFR, a New Functional Index of Coronary Stenosis: Comparison With Invasive FFR Data.

Aims: In this study, we evaluate the efficacy of SmartFFR, a new functional index of coronary stenosis severity compared with gold standard invasive measurement of fractional flow reserve (FFR). We also assess the influence of the type of simulation employed on smartFFR (i.e. Fluid Structure Interaction vs. rigid wall assumption). Methods and Results: In a dataset of 167 patients undergoing either computed tomography coronary angiography (CTCA) and invasive coronary angiography or only invasive coronary angiography (ICA), as well as invasive FFR measurement, SmartFFR was computed after the 3D reconstruction of the vessels of interest and the subsequent blood flow simulations. 202 vessels were analyzed with a mean total computational time of seven minutes. SmartFFR was used to process all models reconstructed by either method. The mean FFR value of the examined dataset was 0.846 ± 0.089 with 95% CI for the mean of 0.833-0.858, whereas the mean SmartFFR value was 0.853 ± 0.095 with 95% CI for the mean of 0.84-0.866. SmartFFR was significantly correlated with invasive FFR values (RCCTA = 0.86, p CCTA < 0.0001, RICA = 0.84, p ICA < 0.0001, R overall = 0.833, p overall < 0.0001), showing good agreement as depicted by the Bland-Altman method of analysis. The optimal SmartFFR threshold to diagnose ischemia was ≤0.83 for the overall dataset, ≤0.83 for the CTCA-derived dataset and ≤0.81 for the ICA-derived dataset, as defined by a ROC analysis (AUCoverall = 0.956, p < 0.001, AUCICA = 0.975, p < 0.001, AUCCCTA = 0.952, p < 0.001). Conclusion: SmartFFR is a fast and accurate on-site index of hemodynamic significance of coronary stenosis both at single coronary segment and at two or more branches level simultaneously, which can be applied to all CTCA or ICA sequences of acceptable quality.

Predictive Added Value of Selected Plasma Lipids to a Re-estimated Minimal Risk Tool.

Background: Lipidomics is emerging for biomarker discovery in cardiovascular disease, and circulating lipids are increasingly incorporated in risk models to predict cardiovascular events. Moreover, specific classes of lipids, such as sphingomyelins, ceramides, and triglycerides, have been related to coronary artery disease (CAD) severity and plaque characteristics. To avoid unnecessary testing, it is important to identify individuals at low CAD risk. The only pretest model available so far to rule out the presence of coronary atherosclerosis in patients with chest pain, but normal coronary arteries, is the minimal risk tool (MRT). Aim: Using state-of-the-art statistical methods, we aim to verify the additive predictive value of a set of lipids, derived from targeted plasma lipidomics of suspected CAD patients, to a re-estimated version of the MRT for ruling out the presence of coronary atherosclerosis assessed by coronary CT angiography (CCTA). Methods: Two hundred and fifty-six subjects with suspected stable CAD recruited from five European countries within H2020-SMARTool, undergoing CCTA and blood sampling for clinical biochemistry and lipidomics, were selected. The MRT was validated by regression methods and then re-estimated (reMRT). The reMRT was used as a baseline model in a likelihood ratio test approach to assess the added predictive value of each lipid from 13 among ceramides, triglycerides, and sphingomyelins. Except for one lipid, the analysis was carried out on more than 240 subjects for each lipid. A sensitivity analysis was carried out by considering two alternative models developed on the cohort as baseline models. Results: In 205 subjects, coronary atherosclerosis ranged from minimal lesions to overt obstructive CAD, while in 51 subjects (19.9%) the coronary arteries were intact. Four triglycerides and seven sphingomyelins were significantly (p < 0.05) and differentially expressed in the two groups and, at a lesser extent, one ceramide (p = 0.067). The probability of being at minimal risk was significantly better estimated by adding either Cer(d18:1/16:0) (p = 0.01), SM(40:2) (p = 0.04), or SM(41:1) at a lesser extent (p = 0.052) to reMRT than by applying the reMRT alone. The sensitivity analysis confirmed the relevance of these lipids. Furthermore, the addition of SM(34:1), SM(38:2), SM(41:2), and SM(42:4) improved the predictive performance of at least one of the other baseline models. None of the selected triglycerides was found to provide an added value. Conclusions: Plasma lipidomics can be a promising source of diagnostic and prognostic biomarkers in cardiovascular disease, exploitable not only to assess the risk of adverse events but also to identify subjects without coronary atherosclerosis, thus reducing unnecessary further testing in normal subjects.

Discrimination capability of pretest probability of stable coronary artery disease: a systematic review and meta-analysis suggesting how to improve validation procedures.

OBJECTIVE: Externally validated pretest probability models for risk stratification of subjects with chest pain and suspected stable coronary artery disease (CAD), determined through invasive coronary angiography or coronary CT angiography, are analysed to characterise the best validation procedures in terms of discriminatory ability, predictive variables and method completeness. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Global Health (Ovid), Healthstar (Ovid) and MEDLINE (Ovid) searched on 22 April 2020. ELIGIBILITY CRITERIA: We included studies validating pretest models for the first-line assessment of patients with chest pain and suspected stable CAD. Reasons for exclusion: acute coronary syndrome, unstable chest pain, a history of myocardial infarction or previous revascularisation; models referring to diagnostic procedures different from the usual practices of the first-line assessment; univariable models; lack of quantitative discrimination capability. METHODS: Eligibility screening and review were performed independently by all the authors. Disagreements were resolved by consensus among all the authors. The quality assessment of studies conforms to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A random effects meta-analysis of area under the receiver operating characteristic curve (AUC) values for each validated model was performed. RESULTS: 27 studies were included for a total of 15 models. Besides age, sex and symptom typicality, other risk factors are smoking, hypertension, diabetes mellitus and dyslipidaemia. Only one model considers genetic profile. AUC values range from 0.51 to 0.81. Significant heterogeneity (p<0.003) was found in all but two cases (p>0.12). Values of I2 >90% for most analyses and not significant meta-regression results undermined relevant interpretations. A detailed discussion of individual results was then carried out. CONCLUSIONS: We recommend a clearer statement of endpoints, their consistent measurement both in the derivation and validation phases, more comprehensive validation analyses and the enhancement of threshold validations to assess the effects of pretest models on clinical management. PROSPERO REGISTRATION NUMBER: CRD42019139388.

A study on the accuracy and efficiency of the improved numerical model for stent implantation using clinical data.

BACKGROUND AND OBJECTIVES: Stent implantation procedure should be carefully planned and adapted to the particular patient in order to minimize possible complications. Numerical simulations can provide useful quantitative data about the state of the artery after the implantation, as well as information about the benefits of the intervention from the hemodynamical point of view. METHODS: In this paper, a numerical model for stent implantation is presented. This numerical model simulates the stent expansion, the interaction of the stent with arterial wall and the deformation of the arterial wall under the influence of the stent. FE method was used to perform CFD simulations and the effects of stenting were analyzed by comparing the hemodynamic parameters before and after stent implantation. RESULTS: Clinical data for overall 34 patients was used for the simulations, and for 9 of them data from follow up examinations was used to validate the results of simulations of stent implantation. CONCLUSIONS: The good agreement of results (less than 4.1% of SD error for all the 9 validation cases) demonstrated the accuracy of the presented numerical model. The developed approach can be a valuable tool for the improvement of pre-operative planning and patient-specific treatment optimization.

Sex differences in coronary plaque changes assessed by serial computed tomography angiography.

Long-term data on sex-differences in coronary plaque changes over time is lacking in a low-to-intermediate risk population of stable coronary artery disease (CAD). The aim of this study was to evaluate the role of sex on long-term plaque progression and evolution of plaque composition. Furthermore, the influence of menopause on plaque progression and composition was also evaluated. Patients that underwent a coronary computed tomography angiography (CTA) were prospectively included to undergo a follow-up coronary CTA. Total and compositional plaque volumes were normalized using the vessel volume to calculate a percentage atheroma volume (PAV). To investigate the influence of menopause on plaque progression, patients were divided into two groups, under and over 55 years of age. In total, 211 patients were included in this analysis, 146 (69%) men. The mean interscan period between baseline and follow-up coronary CTA was 6.2 ± 1.4 years. Women were older, had higher HDL levels and presented more often with atypical chest pain. Men had 434 plaque sites and women 156. On a per-lesion analysis, women had less fibro-fatty PAV compared to men (ß -1.3 ± 0.4%; p < 0.001), with no other significant differences. When stratifying patients by 55 years age threshold, fibro-fatty PAV remained higher in men in both age groups (p < 0.05) whilst women younger than 55 years demonstrated more regression of fibrous (ß -0.8 ± 0.3% per year; p = 0.002) and non-calcified PAV (ß -0.7 ± 0.3% per year; p = 0.027). In a low-to-intermediate risk population of stable CAD patients, no significant sex differences in total PAV increase over time were observed. Fibro-fatty PAV was lower in women at any age and women under 55 years demonstrated significantly greater reduction in fibrous and non-calcified PAV over time compared to age-matched men. (ClinicalTrials.gov number, NCT04448691.).

A Novel Approach to Generate a Virtual Population of Human Coronary Arteries for In Silico Clinical Trials of Stent Design.

Goal: To develop a cardiovascular virtual population using statistical modeling and computational biomechanics. Methods: A clinical data augmentation algorithm is implemented to efficiently generate virtual clinical data using a real clinical dataset. An atherosclerotic plaque growth model is employed to 3D reconstructed coronary arterial segments to generate virtual coronary arterial geometries (geometrical data). Last, the combination of the virtual clinical and geometrical data is achieved using a methodology that allows for the generation of a realistic virtual population which can be used in in silico clinical trials. Results: The results show good agreement between real and virtual clinical data presenting a mean gof 0.1 ± 0.08. 400 virtual coronary arteries were generated, while the final virtual population includes 10,000 patients. Conclusions: The virtual arterial geometries are efficiently matched to the generated clinical data, both increasing and complementing the variability of the virtual population.

Cardiac Computed Tomography Perfusion: Contrast Agents, Challenges and Emerging Methodologies from Preclinical Research to the Clinics.

Computed Tomography (CT) has long been regarded as a purely anatomical imaging modality. Recent advances on CT technology and Contrast Agents (CA) in both clinical and preclinical cardiac imaging offer opportunities for the use of CT in functional imaging. Combined with modern ECG-gating techniques, functional CT has now become a reality allowing a comprehensive evaluation of myocardial global and regional function, perfusion and coronary angiography. This article aims at reviewing the current status of cardiac CT perfusion and micro-CT perfusion with established and experimental scanners and contrast agents, from clinical practice to the experimental domain of investigations based on animal models of heart diseases.

Site specific prediction of PCI stenting based on imaging and biomechanics data using gradient boosting tree ensembles.

Cardiovascular diseases are nowadays considered as the main cause of morbidity and mortality worldwide. Coronary Artery Disease (CAD), the most typical form of cardiovascular disease is diagnosed by a variety of imaging modalities, both invasive and non-invasive, which involve either risk implications or high cost. Therefore, several attempts have been undertaken to early diagnose and predict either the high CAD risk patients or the cardiovascular events, implementing machine learning techniques. The purpose of this study is to present a classification scheme for the prediction of Percutaneous Coronary Intervention (PCI) stenting placement, using image-based data. The proposed classification model is a gradient boosting classifier, incorporated into a class imbalance handling technique, the Easy ensemble scheme and aims to classify coronary segments into high CAD risk and low CAD risk, based on their PCI placement. Through this study, we investigate the importance of image based features, concluding that the combination of the coronary degree of stenosis and the fractional flow reserve achieves accuracy 78%.