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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Background Advances in three-dimensional reconstruction techniques and computational fluid dynamics of coronary CT angiography (CCTA) data sets make feasible evaluation of endothelial shear stress (ESS) in the vessel wall. Purpose To investigate the relationship between CCTA-derived computational fluid dynamics metrics, anatomic and morphologic characteristics of coronary lesions, and their comparative performance in predicting impaired coronary vasodilating capability assessed by using PET myocardial perfusion imaging (MPI). Materials and Methods In this retrospective study, conducted between October 2019 and September 2020, coronary vessels in patients with stable chest pain and with intermediate probability of coronary artery disease who underwent both CCTA and PET MPI with oxygen 15-labeled water or nitrogen 13 ammonia and quantification of myocardial blood flow were analyzed. CCTA images were used in assessing stenosis severity, lesion-specific total plaque volume (PV), noncalcified PV, calcified PV, and plaque phenotype. PET MPI was used in assessing significant coronary stenosis. The predictive performance of the CCTA-derived parameters was evaluated by using area under the receiver operating characteristic curve (AUC) analysis. Results There were 92 coronary vessels evaluated in 53 patients (mean age, 65 years ± 7; 31 men). ESS was higher in lesions with greater than 50% stenosis versus those without significant stenosis (mean, 15.1 Pa ± 30 vs 4.6 Pa ± 4 vs 3.3 Pa ± 3; P = .004). ESS was higher in functionally significant versus nonsignificant lesions (median, 7 Pa [interquartile range, 5-23 Pa] vs 2.6 Pa [interquartile range, 1.8-5 Pa], respectively; P ≤ .001). Adding ESS to stenosis severity improved prediction (change in AUC, 0.10; 95% CI: 0.04, 0.17; P = .002) for functionally significant lesions. Conclusion The combination of endothelial shear stress with coronary CT angiography (CCTA) stenosis severity improved prediction of an abnormal PET myocardial perfusion imaging result versus CCTA stenosis severity alone. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Kusmirek and Wieben in this issue.

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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.).

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BACKGROUND AND AIMS: Atherosclerosis is an inflammatory disease with long-lasting activation of innate immunity and monocytes are the main blood cellular effectors. We aimed to investigate monocyte phenotype (subset fraction and marker expression) at different stages of coronary atherosclerosis in stable coronary artery disease (CAD) patients. METHODS: 73 patients with chronic coronary syndrome were evaluated by CT coronary angiography (CTCA) and classified by maximal diameter stenosis of major vessels into three groups of CAD severity: CAD1 (no CAD/minimal CAD, n° = 30), CAD2 (non-obstructive CAD, n° = 21), and CAD3 (obstructive CAD, n° = 22). Flow cytometry for CD14, CD16, and CCR2 was used to quantify Mon1, Mon2, and Mon3 subsets. Expression of CD14, CD16, CD18, CD11b, HLA-DR, CD163, CCR2, CCR5, CX3CR1, and CXCR4 was also measured. Adhesion molecules and cytokines were quantified by ELISA. RESULTS: Total cell count and fraction of Mon2 were higher in CAD2 and CAD3 compared to CAD1. By multivariate regression analysis, Mon2 cell fraction and Mon2 expression of CX3CR1, CD18, and CD16 showed a statistically significant and independent increase, parallel to stenosis severity, from CAD1 to CAD2 and CAD3 groups. A similar trend was also present for CX3CR1 and HLA-DR expressions on total monocyte population. A less calcified plaque composition was associated to a higher Mon2 expression of CD16 and higher TNF-α levels. IL-10 levels were lower at greater stenosis severity, while the IFN-γ/IL-10 ratio, a marker of a systemic pro-inflammatory imbalance, was directly correlated to stenosis degree and number of noncalcified plaques. CONCLUSIONS: The results of this study suggest that a specific pattern of inflammation-correlated monocyte marker expression is associated to higher stenosis severity and less calcified lesions in stable CAD. The clinical trial Identifier is NCT04448691.

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Background Progression of coronary artery disease using serial coronary computed tomography angiography (CTA) is of clinical interest. Our primary aim was to prospectively assess the impact of clinical characteristics and statin use on quantitatively assessed coronary plaque progression in a low-risk study population during long-term follow-up. Methods Patients who previously underwent coronary CTA for suspected coronary artery disease were prospectively included to undergo follow-up coronary CTA. The primary end point was coronary artery disease progression, defined as the absolute annual increase in total, calcified, and noncalcified plaque volume by quantitative CTA analysis. Results In total, 202 patients underwent serial coronary CTA with a mean interscan period of 6.2±1.4 years. On a per-plaque basis, increasing age (ß=0.070; P=0.058) and hypertension (ß=1.380; P=0.075) were nonsignificantly associated with annual total plaque progression. Male sex (ß=1.676; P=0.009), diabetes mellitus (ß=1.725; P=0.012), and statin use (ß=1.498; P=0.046) showed an independent association with annual progression of calcified plaque. While hypertension (ß=2.259; P=0.015) was an independent determinant of noncalcified plaque progression, statin use (ß=-2.178; P=0.050) was borderline significantly associated with a reduced progression of noncalcified plaque. Conclusions Statin use was associated with an increased progression of calcified coronary plaque and a reduced progression of noncalcified coronary plaque, potentially reflecting calcification of the noncalcified plaque component. Whereas hypertension was the only modifiable risk factor predictive of noncalcified plaque progression, diabetes mellitus mainly led to an increase in calcified plaque. These findings could yield the need for intensified preventive treatment of patients with diabetes mellitus and hypertension to slow and stabilize coronary artery disease progression and improve clinical outcome.

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BACKGROUND AND OBJECTIVE: One of the most widely adopted endovascular treatment procedures is the stent implantation. The effectiveness of the treatment depends on the appropriate stent expansion. However, it is difficult to accurately predict the outcome of such an endovascular intervention. Numerical simulations represent a useful tool to study the complex behavior of the stent during deployment. This study presents a numerical model capable of simulating this process. METHODS: The numerical model consists of three parts: modeling of stent expansion, modeling the interaction of the stent with the arterial wall and the deformation of the arterial wall. The model is able to predict the shapes of both stent and arterial wall during the entire deployment process. Simulations are performed using patient-specific clinical data that ensures more realistic results. RESULTS: The numerical simulations of stent deployment are performed using the extracted geometry of the coronary arteries of two patients. The obtained results are validated against clinical data from the follow up examination and both quantitative and qualitative analysis of the results is presented. The areas of several slices of the arterial wall are calculated for all the three states (before, after and follow up) and the standard error of the area when comparing simulation and follow up examination is 5.27% for patient #1 and 4.5% for patient #2. CONCLUSIONS: The final goal of numerical simulations in stent deployment should be to provide a clinical tool that is capable of reliably predicting the treatment outcome. This study showed through the good agreement of results of the numerical simulations and clinical data that the presented numerical model represents a step towards this final goal. These simulations can also provide valuable information about distribution of forces and stress in the arterial wall that can improve pre-operative planning and treatment optimization.

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AIMS: To test the hypothesis that virtual functional assessment index (vFAI) is related with regional flow parameters derived by quantitative positron emission tomography (PET) and can be used to assess abnormal vasodilating capability in coronary vessels with stenotic lesions at coronary computed tomography angiography (CCTA). METHODS AND RESULTS: vFAI, stress myocardial blood flow (MBF), and myocardial flow reserve (MFR) were assessed in 78 patients (mean age 62.2 ± 7.7 years) with intermediate pre-test likelihood of coronary artery disease (CAD). Coronary stenoses ≥50% were considered angiographically significant. PET was considered positive for significant CAD, when more than one contiguous segments showed stress MBF ≤2.3 mL/g/min for 15O-water or <1.79 mL/g/min for 13N-ammonia. MFR thresholds were ≤2.5 and ≤2.0, respectively. vFAI was lower in vessels with abnormal stress MBF (0.76 ± 0.10 vs. 0.89 ± 0.07, P < 0.001) or MFR (0.80 ± 0.10 vs. 0.89 ± 0.07, P < 0.001). vFAI had an accuracy of 78.6% and 75% in unmasking abnormal stress MBF and MFR in 15O-water and 82.7% and 71.2% in 13N-ammonia studies, respectively. Addition of vFAI to anatomical CCTA data increased the ability for predicting abnormal stress MBF and MFR in 15O-water studies [AUCccta + vfai = 0.866, 95% confidence interval (CI) 0.783-0.949; P = 0.013 and AUCccta + vfai = 0.737, 95% CI 0.648-0.825; P = 0.007, respectively]. An incremental value was also demonstrated for prediction of stress MBF (AUCccta + vfai = 0.887, 95% CI 0.799-0.974; P = 0.001) in 13N-ammonia studies. A similar trend was recorded for MFR (AUCccta + vfai = 0.780, 95% CI 0.632-0.929; P = 0.13). CONCLUSION: vFAI identifies accurately the presence of impaired vasodilating capability. In combination with anatomical data, vFAI enhances the diagnostic performance of CCTA.

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AIMS: We aimed to investigate the performance of virtual functional assessment of coronary stenoses using intravascular ultrasound (IVUS)-based three-dimensional (3D) coronary artery reconstruction against the invasively measured fractional flow reserve (FFR). METHODS AND RESULTS: Twenty-two (22) patients with either typical symptoms of stable angina or a positive stress test, who underwent IVUS and FFR, were included in this study. Five (5) patients presented FFR values lower than the 0.80 threshold, indicating ischaemia. IVUS-based 3D reconstruction and blood flow simulation were performed and the virtual functional assessment index (vFAI) was calculated. A strong correlation between IVUS-based vFAI and FFR was observed (Spearman correlation coefficient [rs]=0.88, p<0.0001). There was a small overestimation of the FFR by the IVUS-based vFAI (mean difference=0.0196±0.037; p=0.023 for difference from zero). All cases with haemodynamically significant stenoses (FFR≤0.8) were correctly categorised by the IVUS-based vFAI (vFAI≤0.8). CONCLUSION: The proposed approach allows the complete and comprehensive assessment of coronary stenoses providing anatomic and physiologic information, pre- and post-intervention, using only an IVUS catheter without the use of a pressure wire.

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OBJECTIVES: Application of computational fluid dynamics (CFD) to three-dimensional CTCA datasets has been shown to provide accurate assessment of the hemodynamic significance of a coronary lesion. We aim to test the feasibility of calculating a novel CTCA-based virtual functional assessment index (vFAI) of coronary stenoses > 30% and ≤ 90% by using an automated in-house-developed software and to evaluate its efficacy as compared to the invasively measured fractional flow reserve (FFR). METHODS AND RESULTS: In 63 patients with chest pain symptoms and intermediate (20-90%) pre-test likelihood of coronary artery disease undergoing CTCA and invasive coronary angiography with FFR measurement, vFAI calculations were performed after 3D reconstruction of the coronary vessels and flow simulations using the finite element method. A total of 74 vessels were analyzed. Mean CTCA processing time was 25(± 10) min. There was a strong correlation between vFAI and FFR, (R = 0.93, p < 0.001) and a very good agreement between the two parameters by the Bland-Altman method of analysis. The mean difference of measurements from the two methods was 0.03 (SD = 0.033), indicating a small systematic overestimation of the FFR by vFAI. Using a receiver-operating characteristic curve analysis, the optimal vFAI cutoff value for identifying an FFR threshold of ≤ 0.8 was ≤ 0.82 (95% CI 0.81 to 0.88). CONCLUSIONS: vFAI can be effectively derived from the application of computational fluid dynamics to three-dimensional CTCA datasets. In patients with coronary stenosis severity > 30% and ≤ 90%, vFAI performs well against FFR and may efficiently distinguish between hemodynamically significant from non-significant lesions. KEY POINTS: Virtual functional assessment index (vFAI) can be effectively derived from 3D CTCA datasets. In patients with coronary stenoses severity > 30% and ≤ 90%, vFAI performs well against FFR. vFAI may efficiently distinguish between functionally significant from non-significant lesions.

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SMARTool aims to perform accurate risk stratification of coronary artery disease patients as well as to provide early diagnosis and prediction of disease progression. This is achieved by the acquisition of data from about 263 patients including computed tomography angiographic images, clinical, molecular, biohumoral, exposome, inflammatory and omics data. Data are collected in two time points with a followup period of approximately 5 years. In the first step, data mining techniques are implemented for the estimation of risk stratification. In the next step, patients, who are classified as medium to high risk are considered for coronary imaging and computational modelling of blood flow, plaque growth and stenosis severity assessment. Additionally, patients with increased stenosis are selected for stent deployment. All the above modules are integrated in a cloud-based platform for the clinical decision support (CDSS) of patients with coronary artery disease. The work presents preliminary results employing the SMARTool dataset as well as the concept and architecture of the under development platform.

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Nowadays, cardiovascular diseases are very common and are considered as the main cause of morbidity and mortality worldwide. Coronary Artery Disease (CAD), the most typical cardiovascular disease is diagnosed by a variety of medical imaging modalities, which involve costs and complications. Therefore, several attempts have been undertaken to early diagnose and predict CAD status and progression through machine learning approaches. The purpose of this study is to present a machine learning technique for the prediction of CAD, using image-based data and clinical data. We investigate the effect of vascular anatomical features of the three coronary arteries on the graduation of CAD. A classification model is built to predict the future status of CAD, including cases of "no CAD" patients, "non-obstructive CAD" patients and "obstructive CAD" patients. The best accuracy was achieved by the implementation of a tree-based classifier, J48 classifier, after a ranking feature selection methodology. The majority of the selected features are the vessel geometry derived features, among the traditional risk factors. The combination of geometrical risk factors with the conventional ones constitutes a novel scheme for the CAD prediction.

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BACKGROUND: In the pathogenesis of atherosclerosis, a central role is represented by endothelial inflammation with influx of chemokine-mediated leukocytes in the vascular wall. Aim of this study was to analyze the effect of different shear stresses on endothelial gene expression and compute gene network involved in atherosclerotic disease, in particular to homeostasis, inflammatory cell migration, and apoptotic processes. METHODS: HUVECs were subjected to shear stress of 1, 5, and 10 dyne/cm2 in a Flow Bioreactor for 24 hours to compare gene expression modulation. Total RNA was analyzed by Affymetrix technology and the expression of two specific genes (CXCR4 and ICAM-1) was validated by RT-PCR. To highlight possible regulations between genes and as further validation, a bioinformatics analysis was performed. RESULTS: At low shear stress (1 dyne/cm2) we observed the following: (a) strong upregulation of CXCR4; (b) mild upregulation of Caspase-8; (c) mild downregulation of ICAM-1; (d) marked downexpression of TNFAIP3. Bioinformatics analysis showed the presence of network composed by 59 new interactors (14 transcription factors and 45 microRNAs) appearing strongly related to shear stress. CONCLUSIONS: The significant modulation of these genes at low shear stress and their close relationships through transcription factors and microRNAs suggest that all may promote an initial inflamed endothelial cell phenotype, favoring the atherosclerotic disease.

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SMARTool aims to the development of a clinical decision support system (CDSS) for the management and stratification of patients with coronary artery disease (CAD). This will be achieved by performing computational modeling of the main processes of atherosclerotic plaque growth. More specifically, computed tomography coronary angiography (CTCA) is acquired and 3-dimensional (3D) reconstruction is performed for the arterial trees. Then, blood flow and plaque growth modeling is employed simulating the major processes of atherosclerosis, such as the estimation of endothelial shear stress (ESS), the lipids transportation, low density lipoprotein (LDL) oxidation, macrophages migration and plaque development. The plaque growth model integrates information from genetic and biological data of the patients. The SMARTool system enables also the calculation of the virtual functional assessment index (vFAI), an index equivalent to the invasively measured fractional flow reserve (FFR), to provide decision support for patients with stenosed arteries. Finally, it integrates modeling of stent deployment. In this work preliminary results are presented. More specifically, the reconstruction methodology has mean value of Dice Coefficient and Hausdorff Distance is 0.749 and 1.746, respectively, while low ESS and high LDL concentration can predict plaque progression.

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