Using 2D In Vivo IVUS-Based Models for Human Coronary Plaque Progression Analysis and Comparison with 3D Fluid-Structure Interaction Models: A Multi-Patient Study

Computational modeling has been used extensively in cardiovascular and biological research, providing valuable information. However, 3D vulnerable plaque model construction with complex geometrical features and multicomponents is often very time consuming and not practical for clinical implementation. This paper investigated if 2D atherosclerotic plaque models could be used to replace 3D models to perform correlation analysis and achieve similar results. In vivo intravascular ultrasound (IVUS) coronary plaque data were acquired from a patient follow-up study to construct 2D structure-only and 3D FSI models to obtain plaque wall stress (PWS) and strain (PWSn) data. One hundred and twenty-seven (127) matched IVUS slices at baseline and follow up were obtained from 3 patients. Our results showed that 2D models overestimated stress and strain by 30% and 33%, respectively, compared to results from 3D FSI models. 2D/3D correlation comparison indicated that 116 out of 127 slices had a consistent correlation between plaque progression (WTI) and wall thickness; 103 out of 127 slices had a consistent correlation between WTI and PWS; and 99 out of 127 slices had a consistent correlation between WTI and PWSn. This leads to the potential that 2D models could be used in actual clinical implementation where quick analysis delivery time is essential.     

In vivo serial MRI-based models and statistical methods to quantify sensitivity and specificity of mechanical predictors for carotid plaque rupture: location and beyond

It has been hypothesized that mechanical risk factors may be used to predict future atherosclerotic plaque rupture. Truly predictive methods for plaque rupture and methods to identify the best predictor(s) from all the candidates are lacking in the literature. A novel combination of computational and statistical models based on serial magnetic resonance imaging (MRI) was introduced to quantify sensitivity and specificity of mechanical predictors to identify the best candidate for plaque rupture site prediction. Serial in vivo MRI data of carotid plaque from one patient was acquired with follow-up scan showing ulceration. 3D computational fluid-structure interaction (FSI) models using both baseline and follow-up data were constructed and plaque wall stress (PWS) and strain (PWSn) and flow maximum shear stress (FSS) were extracted from all 600 matched nodal points (100 points per matched slice, baseline matching follow-up) on the lumen surface for analysis. Each of the 600 points was marked "ulcer" or "nonulcer" using follow-up scan. Predictive statistical models for each of the seven combinations of PWS, PWSn, and FSS were trained using the follow-up data and applied to the baseline data to assess their sensitivity and specificity using the 600 data points for ulcer predictions. Sensitivity of prediction is defined as the proportion of the true positive outcomes that are predicted to be positive. Specificity of prediction is defined as the proportion of the true negative outcomes that are correctly predicted to be negative. Using probability 0.3 as a threshold to infer ulcer occurrence at the prediction stage, the combination of PWS and PWSn provided the best predictive accuracy with (sensitivity, specificity)?=?(0.97, 0.958). Sensitivity and specificity given by PWS, PWSn, and FSS individually were (0.788, 0.968), (0.515, 0.968), and (0.758, 0.928), respectively. The proposed computational-statistical process provides a novel method and a framework to assess the sensitivity and specificity of various risk indicators and offers the potential to identify the optimized predictor for plaque rupture using serial MRI with follow-up scan showing ulceration as the gold standard for method validation. While serial MRI data with actual rupture are hard to acquire, this single-case study suggests that combination of multiple predictors may provide potential improvement to existing plaque assessment schemes. With large-scale patient studies, this predictive modeling process may provide more solid ground for rupture predictor selection strategies and methods for image-based plaque vulnerability assessment.     

Multi-patient study for coronary vulnerable plaque model comparisons: 2D/3D and fluid–structure interaction simulations

Several image-based computational models have been used to perform mechanical analysis for atherosclerotic plaque progression and vulnerability investigations. However, differences of computational predictions from those models have not been quantified at multi-patient level. In vivo intravascular ultrasound (IVUS) coronary plaque data were acquired from seven patients. Seven 2D/3D models with/without circumferential shrink, cyclic bending and fluid–structure interactions (FSI) were constructed for the seven patients to perform model comparisons and quantify impact of 2D simplification, circumferential shrink, FSI and cyclic bending plaque wall stress/strain (PWS/PWSn) and flow shear stress (FSS) calculations. PWS/PWSn and FSS averages from seven patients (388 slices for 2D and 3D thin-layer models) were used for comparison. Compared to 2D models with shrink process, 2D models without shrink process overestimated PWS by 17.26%. PWS change at location with greatest curvature change from 3D FSI models with/without cyclic bending varied from 15.07% to 49.52% for the seven patients (average = 30.13%). Mean Max-FSS, Min-FSS and Ave-FSS from the flow-only models under maximum pressure condition were 4.02%, 11.29% and 5.45% higher than those from full FSI models with cycle bending, respectively. Mean PWS and PWSn differences between FSI and structure-only models were only 4.38% and 1.78%. Model differences had noticeable patient variations. FSI and flow-only model differences were greater for minimum FSS predictions, notable since low FSS is known to be related to plaque progression. Structure-only models could provide PWS/PWSn calculations as good approximations to FSI models for simplicity and time savings in calculation.

     

A negative correlation between human carotid atherosclerotic plaque progression and plaque wall stress: in vivo MRI-based 2D/3D FSI models

It is well accepted that atherosclerosis initiation and progression correlate positively with low and oscillating flow wall shear stresses (FSS). However, this mechanism cannot explain why advanced plaques continue to grow under elevated FSS conditions. In vivo magnetic resonance imaging (MRI)-based 2D/3D multi-component models with fluid-structure interactions (FSI, 3D only) for human carotid atherosclerotic plaques were introduced to quantify correlations between plaque progression measured by wall thickness increase (WTI) and plaque wall (structure) stress (PWS) conditions. A histologically validated multi-contrast MRI protocol was used to acquire multi-year in vivo MRI images. Our results using 2D models (200-700 data points/patient) indicated that 18 out of 21 patients studied showed significant negative correlation between WTI and PWS at time 2 (T2). The 95% confidence interval for the Pearson correlation coefficient is (-0.443,-0.246), p<0.0001. Our 3D FSI model supported the 2D correlation results and further indicated that combining both plaque structure stress and flow shear stress gave better approximation results (PWS, T2: R(2)=0.279; FSS, T1: R(2)=0.276; combining both: R(2)=0.637). These pilot studies suggest that both lower PWS and lower FSS may contribute to continued plaque progression and should be taken into consideration in future investigations of diseases related to atherosclerosis.     

Advanced human carotid plaque progression correlates positively with flow shear stress using follow-up scan data: An in vivo MRI multi-patient 3D FSI study

Although it has been well-accepted that atherosclerosis initiation and early progression correlate negatively with flow wall shear stresses (FSS), increasing evidence suggests mechanisms governing advanced plaque progression are not well understood. Fourteen patients were scanned 2–4 times at 18 month intervals using a histologically validated multi-contrast magnetic resonance imaging (MRI) protocol to acquire carotid plaque progression data. Thirty-two scan pairs (baseline and follow-up scans) were formed with slices matched for model construction and analysis. 3D fluid–structure interaction (FSI) models were constructed and plaque wall stress (PWS) and flow shear stress (FSS) were obtained from all matching lumen data points (400–1000 per plaque; 100 points per matched slice) to quantify correlations with plaque progression measured by vessel wall thickness increase (WTI). Using FSS and PWS data from follow-up scan, 21 out of 32 scan pairs showed a significant positive correlation between WTI and FSS (positive/negative/no significance ratio=21/8/3), and 26 out of 32 scan pairs showed a significant negative correlation between WTI and PWS (positive/negative/no significance ratio=2/26/4). The mean FSS value of lipid core nodes (n=5294) from all 47 plaque models was 63.5 dyn/cm², which was 45% higher than that from all normal vessel nodes (n=27553, p<0.00001). The results from this intensive FSI study indicate that flow shear stress from follow-up scan correlates positively with advanced plaque progression which is different from what has been observed in plaque initiation and early-stage progression. It should be noted that the correlation results do not automatically lead to any causality conclusions.     

Compressive mechanical properties of atherosclerotic plaques—Indentation test to characterise the local anisotropic behaviour

Accurate material models and associated parameters of atherosclerotic plaques are crucial for reliable biomechanical plaque prediction models. These biomechanical models have the potential to increase our understanding of plaque progression and failure, possibly improving risk assessment of plaque rupture, which is the main cause of ischaemic strokes and myocardial infarction. However, experimental biomechanical data on atherosclerotic plaque tissue is scarce and shows a high variability. In addition, most of the biomechanical models assume isotropic behaviour of plaque tissue, which is a general over-simplification. This review discusses the past and the current literature that focus on mechanical properties of plaque derived from compression experiments, using unconfined compression, micro-indentation or nano-indentation. Results will be discussed and the techniques will be mutually compared. Thereafter, an in-house developed indentation method combined with an inverse finite element method is introduced, allowing analysis of the local anisotropic mechanical properties of atherosclerotic plaques. The advantages and limitations of this method will be evaluated and compared to other methods reported in literature.     

Morphological and Stress Vulnerability Indices for Human Coronary Plaques and Their Correlations with Cap Thickness and Lipid Percent: An IVUS-Based Fluid-Structure Interaction Multi-patient Study

Plaque vulnerability, defined as the likelihood that a plaque would rupture, is difficult to quantify due to lack of in vivo plaque rupture data. Morphological and stress-based plaque vulnerability indices were introduced as alternatives to obtain quantitative vulnerability assessment. Correlations between these indices and key plaque features were investigated. In vivo intravascular ultrasound (IVUS) data were acquired from 14 patients and IVUS-based 3D fluid-structure interaction (FSI) coronary plaque models with cyclic bending were constructed to obtain plaque wall stress/strain and flow shear stress for analysis. For the 617 slices from the 14 patients, lipid percentage, min cap thickness, critical plaque wall stress (CPWS), strain (CPWSn) and flow shear stress (CFSS) were recorded, and cap index, lipid index and morphological index were assigned to each slice using methods consistent with American Heart Association (AHA) plaque classification schemes. A stress index was introduced based on CPWS. Linear Mixed-Effects (LME) models were used to analyze the correlations between the mechanical and morphological indices and key morphological factors associated with plaque rupture. Our results indicated that for all 617 slices, CPWS correlated with min cap thickness, cap index, morphological index with r = -0.6414, 0.7852, and 0.7411 respectively (p<0.0001). The correlation between CPWS and lipid percentage, lipid index were weaker (r = 0.2445, r = 0.2338, p<0.0001). Stress index correlated with cap index, lipid index, morphological index positively with r = 0.8185, 0.3067, and 0.7715, respectively, all with p<0.0001. For all 617 slices, the stress index has 66.77% agreement with morphological index. Morphological and stress indices may serve as quantitative plaque vulnerability assessment supported by their strong correlations with morphological features associated with plaque rupture. Differences between the two indices may lead to better plaque assessment schemes when both indices were jointly used with further validations from clinical studies.     

Coronary Computed Tomography Angiography Based Assessment of Endothelial Shear Stress and Its Association with Atherosclerotic Plaque Distribution In-Vivo

Purpose

The relationship between low endothelial shear stress (ESS) and coronary atherosclerosis is well established. ESS assessment so far depended on invasive procedures. The aim of this study was to demonstrate the relationship between ESS and coronary atherosclerosis by using non-invasive coronary computed tomography angiography (CTA) for computational fluid dynamics (CFD) simulations.

Methods

A total number of 7 consecutive patients with suspected coronary artery disease who received CTA and invasive angiography with IVUS analysis were included in this study. CTA examinations were performed using a dual-source scanner. These datasets were used to build a 3D mesh model. CFD calculations were performed using a validated CFD solver. The presence of plaque was assumed if the thickness of the intima-media complex exceeded 0.3 mm in IVUS. Plaque composition was derived by IVUS radiofrequency data analysis.

Results

Plaque was present in 32.1% of all analyzed cross-sections. Plaque prevalence was highest in areas of low ESS (49.6%) and high ESS (34.8%). In parts exposed to intermediate-low and intermediate-high ESS few plaques were found (20.0% and 24.0%) (p<0.001). Wall thickness was closely associated with local ESS. Intima-media thickness was 0.43±0.34mm in low and 0.38±0.32mm in high ESS segments. It was significantly lower when the arterial wall was exposed to intermediate ESS (0.25±0.18mm and 0.28 ± 0.20mm) (p<0.001). Fibrofatty tissue was predominately found in areas exposed to low ESS (p≤0.023).

Conclusions

In this study a close association of atherosclerotic plaque distribution and ESS pattern could be demonstrated in-vivo. Adding CFD analysis to coronary CTA offers the possibility to gather morphologic and physiologic data within one non-invasive examination.     

Quantification of new structural features of coronary plaques by computational post-hoc analysis of virtual histology-intravascular ultrasound images

Cardiovascular disease and complications are often mediated by the development and rupture of atherosclerotic plaques. Plaque composition is a major factor that determines plaque vulnerability. Intravascular ultrasound (IVUS) and spectral analysis of the radio frequency signal provide an in vivo tissue characterisation of atherosclerotic plaques, known as virtual histology (VH–IVUS). In VH–IVUS analysis, four histological tissue components are classified: fibrous, fibro/fatty, necrotic core and calcium. Existing technology determines only the area of each component within the plaque. Quantitative, objective characterisation of other plaque components' patterns within the plaque is lacking. The aim of this study was to determine new compositional and structural indices which indicate spatial distribution, heterogeneity and dispersity of each VH–IVUS-derived component within the plaque area and also with respect to the plaque–lumen border. We developed an automated computational system in Java for the analysis of both single cross-sectional segments and the whole length of the examined plaque (volumetric analysis). The following parameters were computed: the number of different solid segments and the area of the largest solid segment of each component within the plaque, the per cent of the lumen border that is surrounded by each component, the number of different solid segments and the largest area of a solid segment of each component that adjoins the lumen border. Especially components' localisation in relation to the lumen border may significantly influence plaque vulnerability and plaque–stent interaction, which should be investigated in future clinical studies.     

A prediction tool for plaque progression based on patient-specific multi-physical modeling

Atherosclerotic plaque rupture is responsible for a majority of acute vascular syndromes and this study aims to develop a prediction tool for plaque progression and rupture. Based on the follow-up coronary intravascular ultrasound imaging data, we performed patient-specific multi-physical modeling study on four patients to obtain the evolutional processes of the microenvironment during plaque progression. Four main pathophysiological processes, i.e., lipid deposition, inflammatory response, migration and proliferation of smooth muscle cells (SMCs), and neovascularization were coupled based on the interactions demonstrated by experimental and clinical observations. A scoring table integrating the dynamic microenvironmental indicators with the classical risk index was proposed to differentiate their progression to stable and unstable plaques. The heterogeneity of plaque microenvironment for each patient was demonstrated by the growth curves of the main microenvironmental factors. The possible plaque developments were predicted by incorporating the systematic index with microenvironmental indicators. Five microenvironmental factors (LDL, ox-LDL, MCP-1, SMC, and foam cell) showed significant differences between stable and unstable group (p < 0.01). The inflammatory microenvironments (monocyte and macrophage) had negative correlations with the necrotic core (NC) expansion in the stable group, while very strong positive correlations in unstable group. The inflammatory microenvironment is strongly correlated to the NC expansion in unstable plaques, suggesting that the inflammatory factors may play an important role in the formation of a vulnerable plaque. This prediction tool will improve our understanding of the mechanism of plaque progression and provide a new strategy for early detection and prediction of high-risk plaques.     

Convolution Neural Networks and Support Vector Machines for Automatic Segmentation of Intracoronary Optical Coherence Tomography

Cardiovascular diseases are closely associated with deteriorating atherosclerotic plaques. Optical coherence tomography (OCT) is a recently developed intravascular imaging technique with high resolution approximately 10 microns and could provide accurate quantification of coronary plaque morphology. However, tissue segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective. To overcome these limitations, two automatic segmentation methods for intracoronary OCT image based on support vector machine (SVM) and convolutional neural network (CNN) were performed to identify the plaque region and characterize plaque components. In vivo IVUS and OCT coronary plaque data from 5 patients were acquired at Emory University with patient’s consent obtained. Seventy-seven matched IVUS and OCT slices with good image quality and lipid cores were selected for this study. Manual OCT segmentation was performed by experts using virtual histology IVUS as guidance, and used as gold standard in the automatic segmentations. The overall classification accuracy based on CNN method achieved 95.8%, and the accuracy based on SVM was 71.9%. The CNN-based segmentation method can better characterize plaque compositions on OCT images and greatly reduce the time spent by doctors in segmenting and identifying plaques.     

3D computational parametric analysis of eccentric atheroma plaque: influence of axial and circumferential residual stresses

Plaque rupture plays a role in the majority of acute coronary syndromes. Rupture has usually been associated with stress concentrations, which are mainly affected by the plaque geometry and the tissue properties. The aim of this study is to evaluate the influence of morphology on the risk of plaque rupture, including the main geometrical factors, and to assess the role of circumferential and axial residual stresses by means of a parametric 3D finite element model. For this purpose, a 3D parametric finite element model of the coronary artery with eccentric atheroma plaque was developed. Healthy (adventitia and media in areas without atheroma plaque) and diseased (fibrotic and lipidic) tissues were considered in the model. The geometrical parameters used to define and design the idealized coronary plaque anatomy were the lipid core length, the stenosis ratio, the fibrous cap thickness, and the lipid core ratio. Finally, residual stresses in longitudinal and circumferential directions were incorporated into the model to analyse the influence of the important mechanical factors in the vulnerability of the plaque. Viewing the results, we conclude that residual stresses should be considered in the modelling of this kind of problems since they cause a significant alteration of the vulnerable plaque region limits. The obtained results show that the fibrous cap thickness and the lipid core length, in combination with the lipid core width, appear to be the key morphological parameters that play a determinant role in the maximal principal stress (MPS). However, the stenosis ratio is found to not play a significant role in vulnerability related to the MPS. Plaque rupture should therefore be observed as a consequence, not only of the cap thickness, but as a combination of the stenosis ratio, the fibrous cap thickness and the lipid core dimensions.     

Analysis of endothelial protein C receptor gene and metabolic profile in Prader-Willi syndrome and obese subjects

The endothelial protein C receptor (EPCR) has a critical role in the regulation of anticoagulant and anti-inflammatory functions of activated protein C (APC). Abnormalities in EPCR might be associated with an increased risk of thrombosis. In this respect, a 23 bp insertion in the exon 3 of the EPCR gene predicts a truncated protein which cannot bind APC. High levels of C-reactive protein (CRP), a strong predictor of cardiovascular events, are found both in the obese and in subjects with Prader-Willi syndrome (PWS). Several cardiovascular risk factors are already present in prepubertal PWS children, but it is uncertain which mechanism contributes to the increased risk of cardiovascular disease in PWS. We analyzed the distribution of 23 bp insertion in the EPCR gene in 81 overweight and obese PWS subjects, 52 adults and 29 children, and in 58 overweight and obese children and adolescents (controls). We found that 1/58 (1.7%) of the controls was heterozygous for the 23 bp insertion, while this mutation was never found in PWS subjects. Furthermore, we evaluated CRP levels, glucose, insulin, and lipid profile, and we found higher CRP values in PWS adults with respect to children with PWS and controls, and a better insulin sensitivity in all PWS subjects than in the controls. This study suggests that in PWS subjects there is no predisposition to develop thrombotic events in association with EPCR gene alteration and demonstrates substantial differences regarding metabolic and inflammatory profile between PWS and non-PWS obese children, with further impairment in adults with PWS.     

Fibrinolysis: Its initiation and regulation

Fibrinolytic system is one of the major proteolytic pathways in vivo and primarily responsible for dissolution of thrombi. Two enzymes are primarily involved in this proteolytic system; plasminogen activator (PA) and plasmin. Plasmin is formed by a limited proteolysis of plasminogen by PA, which is mainly synthesized by and secreted from vascular endothelial cells. This proteolytic process proceeds physiologically only on the surface of fibrin. Thus, initiation and progression of the fibrinolytic process depend on the function of endothelial cells and fibrin formation. Endothelial cells may also synthesize and excrete PA inhibitor (PAI) which inhibits immediately, PA once released. The rates of synthesis and excretion of PA and PAI by endothelial cells are regulated by various factors. Among them, thrombin stimulates the release of PA whereas activated protein C may decrease the release of PAI. Thus, both enzymes enhance fibrinolytic potential. PA which has escaped from inhibition by PAI binds to fibrin. ₂-Plasmin inhibitor (₂PI) inhibits the binding of plasminogen to fibrin, thereby suppressing this fibrin-associated plasminogen activation. A part of ₂PI is cross-linked to fibrin by activated factor XIII when fibrin is formed, and the ₂PI thus cross-linked to fibrin inhibits in situ plasmin formed on fibrin. Thus, ₂PI as well as PAI plays a central role in inhibition of fibrinolysis.     

Risk Models to Predict Chronic Kidney Disease and Its Progression: A Systematic Review

Background

Chronic kidney disease (CKD) is common, and associated with increased risk of cardiovascular disease and end-stage renal disease, which are potentially preventable through early identification and treatment of individuals at risk. Although risk factors for occurrence and progression of CKD have been identified, their utility for CKD risk stratification through prediction models remains unclear. We critically assessed risk models to predict CKD and its progression, and evaluated their suitability for clinical use.

Methods and Findings

We systematically searched MEDLINE and Embase (1 January 1980 to 20 June 2012). Dual review was conducted to identify studies that reported on the development, validation, or impact assessment of a model constructed to predict the occurrence/presence of CKD or progression to advanced stages. Data were extracted on study characteristics, risk predictors, discrimination, calibration, and reclassification performance of models, as well as validation and impact analyses. We included 26 publications reporting on 30 CKD occurrence prediction risk scores and 17 CKD progression prediction risk scores. The vast majority of CKD risk models had acceptable-to-good discriminatory performance (area under the receiver operating characteristic curve>0.70) in the derivation sample. Calibration was less commonly assessed, but overall was found to be acceptable. Only eight CKD occurrence and five CKD progression risk models have been externally validated, displaying modest-to-acceptable discrimination. Whether novel biomarkers of CKD (circulatory or genetic) can improve prediction largely remains unclear, and impact studies of CKD prediction models have not yet been conducted. Limitations of risk models include the lack of ethnic diversity in derivation samples, and the scarcity of validation studies. The review is limited by the lack of an agreed-on system for rating prediction models, and the difficulty of assessing publication bias.

Conclusions

The development and clinical application of renal risk scores is in its infancy; however, the discriminatory performance of existing tools is acceptable. The effect of using these models in practice is still to be explored. Please see later in the article for the Editors'' Summary     

Gene expression monitoring accurately predicts medulloblastoma positive and negative clinical outcomes

Prediction of medulloblastoma clinical outcome is crucial to personalizing treatment, both to identify high-risk patients for aggressive or alternative therapy and to spare those at low risk from excessive treatment. The best predictors [Pomeroy et al. (2002) Nature 415, 436–442], based on gene expression monitoring at diagnosis, have shown much less accuracy in recognizing patients with eventual failed outcomes – <50% for the predictor making fewest total errors – than those who would survive, while a single gene predictor exhibited reverse asymmetry. Such inaccuracy in recognizing one of the outcomes is a problem for clinical use. We hypothesized that a non-linear model could be built to significantly improve prediction of medulloblastoma outcome, thereby promoting use of gene-expression-based predictors in a clinical setting. In fact, this approach resulted in fewer errors and much less asymmetry in prediction, and bidirectional accuracy of about 80% could be obtained via its combination with other methods. Indeed, three combinations of methods were identified that yielded significantly better predictions of clinical outcome than previously attained, making feasible predictors of medulloblastoma treatment response with greatly improved bidirectional accuracy essential for clinical use.     

Enhanced External Counterpulsation Treatment May Intervene The Advanced Atherosclerotic Plaque Progression by Inducing The Variations of Mechanical Factors: A 3D FSI Study Based on in vivo Animal Experiment

Growing evidences suggest that long-term enhanced external counterpulsation (EECP) treatment can inhibit the initiation of atherosclerotic lesion by improving the hemodynamic environment in aortas. However, whether this kind procedure will intervene the progression of advanced atherosclerotic plaque remains elusive and causes great concern in its clinical application presently. In the current paper, a pilot study combining animal experiment and numerical simulation was conducted to investigate the acute mechanical stress variations during EECP intervention, and then to assess the possible chronic effects. An experimentally induced hypercholesterolemic porcine model was developed and the basic hemodynamic measurement was performed in vivo before and during EECP treatment. Meanwhile, A 3D fluid-structure interaction (FSI) model of blood vessel with symmetric local stenosis was developed for the numerical calculation of some important mechanical factors. The results show that EECP augmented 12.21% of the plaque wall stress (PWS), 57.72% of the time average wall shear stress (AWSS) and 43.67% of the non-dimensional wall shear stress gradient (WSSGnd) at throat site of the stenosis. We suggest that long-term EECP treatment may intervene the advanced plaque progression by inducing the significant variations of some important mechanical factors, but its proper effects will need a further research combined follow-up observation in clinic.     

Necrotic core thickness and positive arterial remodeling index: emergent biomechanical factors for evaluating the risk of plaque rupture

Fibrous cap thickness is often considered as diagnostic of the degree of plaque instability. Necrotic core area (Core(area)) and the arterial remodeling index (Remod(index)), on the other hand, are difficult to use as clinical morphological indexes: literature data show a wide dispersion of Core(area) thresholds above which plaque becomes unstable. Although histopathology shows a strong correlation between Core(area) and Remod(index), it remains unclear how these interact and affect peak cap stress (Cap(stress)), a known predictor of rupture. The aim of this study was to investigate the change in plaque vulnerability as a function of necrotic core size and plaque morphology. Cap(stress) value was calculated on 5,500 idealized atherosclerotic vessel models that had the original feature of mimicking the positive arterial remodeling process described by Glagov. Twenty-four nonruptured plaques acquired by intravascular ultrasound on patients were used to test the performance of the associated idealized morphological models. Taking advantage of the extensive simulations, we investigated the effects of anatomical plaque features on Cap(stress). It was found that: 1) at the early stages of positive remodeling, lesions were more prone to rupture, which could explain the progression and growth of clinically silent plaques and 2) in addition to cap thickness, necrotic core thickness, rather than area, was critical in determining plaque stability. This study demonstrates that plaque instability is to be viewed not as a consequence of fibrous cap thickness alone but rather as a combination of cap thickness, necrotic core thickness, and the arterial remodeling index.     

Ambivalence of progenitor cells in vascular repair and plaque stability

PURPOSE OF REVIEW: To discuss crucial cues (chemokines, adhesion molecules and pharmacological means) that guide and control the context-specific mobilization, recruitment and fate of circulating progenitor cells in arterial repair and plaque stability. RECENT FINDINGS: The mobilization and recruitment of bone marrow derived or resident progenitor cells giving rise to smooth muscle cells have been implicated in accelerated forms of primary plaque formation and neointimal hyperplasia after arterial injury. By contrast, convincing evidence has emerged that the arterial homing of endothelial progenitor cells contributes to endothelial recovery and thereby limits neointimal growth after endothelial denudation. In the chronic context of primary atherosclerosis, plaque progression and destabilization, a more complex picture has become apparent. Clinically, the number and function of endothelial progenitor cells have been linked with an improved endothelial function or regeneration and have been frequently inversely correlated with cardiovascular risk (factors). In animal models, however, the injection of bone marrow cells or endothelial progenitor cells, as well as the application of stem-cell mobilizing factors, have been associated with an exacerbation of atherosclerosis and unstable plaque phenotype, whereas the contribution of smooth muscle progenitors to primary atherosclerosis appears to be more confined to supporting plaque stability. SUMMARY: Considering the balance between distinct circulating vascular progenitor cells and identifying mechanisms for selective control of their mobilization and homing appears crucial to improve prediction and to directly modulate endogenous vascular remodeling processes.