To delineate the influence of hemodynamic force on cell adhesion processes, model in vitro fluidic assays that mimic physiological conditions are commonly employed. Herein, we offer a framework for solution of the three-dimensional Navier- Stokes equations using computational fluid dynamics (CFD) to estimate the forces resulting from fluid flow near a plane acting on a sphere that is either stationary or in free flow, and we compare these results to a widely used theoretical model that assumes Stokes flow with a constant shear rate. We find that while the full three-dimensional solutions using a parabolic velocity profile in CFD simulations yield similar translational velocities to those predicted by the theoretical method, the CFD approach results in approximately 50% larger rotational velocities over the wall shear stress range of 0.1-5.0 dynes cm-2. This leads to an approximately 25% difference in force and torque calculations between the two methods. When compared with experimental measurements of translational and rotational velocities of microspheres or cells perfused in microfluidic channels, the CFD simulations yield significantly less error. We propose that CFD modelling can provide better estimations of hemodynamic force levels acting on perfused microspheres and cells in flow fields through microfluidic devices used for cell adhesion dynamics analysis.

Investigating biophysical cellular interactions in the circulation currently requires choosing between in vivo models, which are difficult to interpret due in part to the hemodynamic and geometric complexities of the vasculature; or in vitro systems, which suffer from non-physiologic assumptions and/or require specialized microfabrication facilities and expertise. To bridge that gap, we developed an in vitro "do-it-yourself" perfusable vasculature model that recapitulates in vivo geometries, such as aneurysms, stenoses, and bifurcations, and supports endothelial cell culture. These inexpensive, disposable devices can be created rapidly (<2 hours) with high precision and repeatability, using standard off-the-shelf laboratory supplies. Using these "endothelialized" systems, we demonstrate that spatial variation in vascular cell adhesion molecule (VCAM-1) expression correlates with the wall shear stress patterns of vascular geometries. We further observe that the presence of endothelial cells in stenoses reduces platelet adhesion but increases sickle cell disease (SCD) red blood cell (RBC) adhesion in bifurcations. Overall, our method enables researchers from all disciplines to study cellular interactions in physiologically relevant, yet simple-to-make, in vitro vasculature models.

BACKGROUND: We hypothesized that nebivolol, a β-blocker with nitric oxide-mediated activity, compared with atenolol, a β-blocker without such activity, would decrease oxidative stress and improve the effects of endothelial dysfunction and wall shear stress (WSS), thereby reducing atherosclerosis progression and vulnerability in patients with nonobstructive coronary artery disease. METHODS AND RESULTS: In this pilot double-blinded randomized controlled trial, 24 patients treated for 1 year with nebivolol 10 mg versus atenolol 100 mg plus standard medical therapy underwent baseline and follow-up coronary angiography with assessments of inflammatory and oxidative stress biomarkers, microvascular function, endothelial function, and virtual histology intravascular ultrasound. WSS was calculated from computational fluid dynamics. Virtual histology intravascular ultrasound segments were assessed for vessel volumetrics and remodeling. There was a trend toward more low-WSS segments in the nebivolol cohort (P=0.06). Low-WSS regions were associated with greater plaque progression (P<0.0001) and constrictive remodeling (P=0.04); conversely, high-WSS segments demonstrated plaque regression and excessive expansive remodeling. Nebivolol patients had decreased lumen and vessel areas along with increased plaque area, resulting in more constrictive remodeling (P=0.002). There were no significant differences in biomarker levels, microvascular function, endothelial function, or number of thin-capped fibroatheromas per vessel. Importantly, after adjusting for β-blocker, low-WSS segments remained significantly associated with lumen loss and plaque progression. CONCLUSION: Nebivolol, compared with atenolol, was associated with greater plaque progression and constrictive remodeling, likely driven by more low-WSS segments in the nebivolol arm. Both β-blockers had similar effects on oxidative stress, microvascular function, and endothelial function.

In recent years, there has been a significant effort to identify high-risk plaques in vivo prior to acute events. While number of imaging modalities have been developed to identify morphologic characteristics of high-risk plaques, prospective natural-history observational studies suggest that vulnerability is not solely dependent on plaque morphology and likely involves additional contributing mechanisms. High wall shear stress (WSS) has recently been proposed as one possible causative factor, promoting the development of high-risk plaques. High WSS has been shown to induce specific changes in endothelial cell behavior, exacerbating inflammation and stimulating progression of the atherosclerotic lipid core. In line with experimental and autopsy studies, several human studies have shown associations between high WSS and known morphological features of high-risk plaques. However, despite increasing evidence, there is still no longitudinal data linking high WSS to clinical events. As the interplay between atherosclerotic plaque, artery, and WSS is highly dynamic, large natural history studies of atherosclerosis that include WSS measurements are now warranted. This review will summarize the available clinical evidence on high WSS as a possible etiological mechanism underlying high-risk plaque development.

Cardiovascular disease (CVD) is the leading cause of death worldwide. Huge effort has been made in many disciplines including medical imaging, computational modeling, biomechanics, bioengineering, medical devices, animal and clinical studies, population studies as well as genomic, molecular, cellular and organ-level studies seeking improved methods for early detection, diagnosis, prevention and treatment of these diseases [1-14]. However, the mechanisms governing the initiation, progression and the occurrence of final acute clinical CVD events are still poorly understood. A large number of victims of these diseases who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs [8,9]. Most cardiovascular diseases are associated with vulnerable plaques. A grand challenge here is to develop new imaging techniques, predictive methods and patient screening tools to identify vulnerable plaques and patients who are more vulnerable to plaque rupture and associated clinical events such as stroke and heart attack, and recommend proper treatment plans to prevent those clinical events from happening. Articles in this special issue came from two symposia held recently focusing on "Cardiovascular Diseases and Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications." One was held at Worcester Polytechnic Institute (WPI), Worcester, MA, USA, July 13-14, 2014, right after the 7th World Congress of Biomechanics. This symposium was endorsed by the World Council of Biomechanics, and partially supported by a grant from NIH-National Institute of Biomedical Image and Bioengineering. The other was held at Southeast University (SEU), Nanjing, China, April 18-20, 2014.

BACKGROUND: Extremes of wall shear stress (WSS) have been associated with plaque progression and transformation, which has raised interest in the clinical assessment of WSS. We hypothesized that calculated coronary WSS is predicted only partially by luminal geometry and that WSS is related to plaque composition. METHODS AND RESULTS: Twenty-seven patients with coronary artery disease underwent virtual histology intravascular ultrasound and Doppler velocity measurement for computational fluid dynamics modeling for WSS calculation in each virtual histology intravascular ultrasound segment (N=3581 segments). We assessed the association of WSS with plaque burden and distribution and with plaque composition. WSS remained relatively constant across the lower 3 quartiles of plaque burden (P=0.08) but increased in the highest quartile of plaque burden (P<0.001). Segments distal to lesions or within bifurcations were more likely to have low WSS (P<0.001). However, the majority of segments distal to lesions (80%) and within bifurcations (89%) did not exhibit low WSS. After adjustment for plaque burden, there was a negative association between WSS and percent necrotic core and calcium. For every 10 dynes/cm(2) increase in WSS, percent necrotic core decreased by 17% (P=0.01), and percent dense calcium decreased by 17% (P<0.001). There was no significant association between WSS and percent of fibrous or fibrofatty plaque components (P=NS). CONCLUSIONS: IN PATIENTS WITH CORONARY ARTERY DISEASE: (1) Luminal geometry predicts calculated WSS only partially, which suggests that detailed computational techniques must be used to calculate WSS. (2) Low WSS is associated with plaque necrotic core and calcium, independent of plaque burden, which suggests a link between WSS and coronary plaque phenotype. (J Am Heart Assoc. 2012;1:e002543 doi: 10.1161/JAHA.112.002543.).

Objective Current understanding of shear sensitive signaling pathways has primarily been studied in vitro largely due to a lack of adequate in vivo models. Our objective was to develop a simple and well characterized murine aortic coarctation model to acutely alter the hemodynamic environment in vivo and test the hypothesis that endothelial inflammatory protein expression is acutely upregulated in vivo in by low magnitude oscillatory WSS. Methods and Results Our model utilizes the shape memory response of nitinol clips to reproducibly induce an aortic coarctation and allow subsequent focal control over WSS in the aorta. We modeled the corresponding hemodynamic environment using computational fluid dynamics and showed that the coarctation produces low magnitude oscillatory WSS distal to the clip. To assess the biological significance of this model, we correlated WSS to inflammatory protein expression and fatty streak formation. VCAM-1 expression and fatty streak formation were both found to increase significantly in regions corresponding to acutely induced low magnitude oscillatory WSS. Conclusions We have developed a novel aortic coarctation model that will be a useful tool for analyzing the in vivo molecular mechanisms of mechanotransduction in various murine models.

Assessment and prediction of vulnerable plaque progression and rupture risk are of utmost importance for diagnosis, management and treatment of cardiovascular diseases and possible prevention of acute cardiovascular events such as heart attack and stroke. However, accurate assessment of plaque vulnerability assessment and prediction of its future changes require accurate plaque cap thickness, tissue component and structure quantifications and mechanical stress/strain calculations. Multi-modality intravascular ultrasound (IVUS), optical coherence tomography (OCT) and angiography image data with follow-up were acquired from ten patients to obtain accurate and reliable plaque morphology for model construction. Three-dimensional thin-slice finite element models were constructed for 228 matched IVUS + OCT slices to obtain plaque stress/strain data for analysis. Quantitative plaque cap thickness and stress/strain indices were introduced as substitute quantitative plaque vulnerability indices (PVIs) and a machine learning method (random forest) was employed to predict PVI changes with actual patient IVUS + OCT follow-up data as the gold standard. Our prediction results showed that optimal prediction accuracies for changes in cap-PVI (C-PVI), mean cap stress PVI (meanS-PVI) and mean cap strain PVI (meanSn-PVI) were 90.3% (AUC = 0.877), 85.6% (AUC = 0.867) and 83.3% (AUC = 0.809), respectively. The improvements in prediction accuracy by the best combination predictor over the best single predictor were 6.6% for C-PVI, 10.0% for mean S-PVI and 8.0% for mean Sn-PVI. Our results demonstrated the potential using multi-modality IVUS + OCT image to accurately and efficiently predict plaque cap thickness and stress/strain index changes. Combining mechanical and morphological predictors may lead to better prediction accuracies.

Objectives: To investigate the long-term vasomotor response and inflammatory changes in Absorb bioresorbable vascular scaffold (BVS) and metallic drug-eluting stent (DES) implanted artery. Background: Clinical evidence has demonstrated that compared to DES, BVS is associated with higher rates of target lesion failure. However, it is not known whether the higher event rates observed with BVS are related to endothelial dysfunction or inflammation associated with polymer degradation. Methods: Ten Absorb BVS and six Xience V DES were randomly implanted in the main coronaries of six nonatherosclerotic swine. At 4-years, vasomotor response was evaluated in vivo by quantitative coronary angiography response to intracoronary infusion of Ach and ex vivo by the biomechanical response to prostaglandin F2-α (PGF2-α), substance P and bradykinin and gene expression analysis. Results: Absorb BVS implanted arteries showed significantly restored vasoconstrictive responses after Ach compared to in-stent Xience V. The contractility of Absorb BVS treated segments induced by PGF2-α was significantly greater compared to Xience V treated segments and endothelial-dependent vasorelaxation was greater with Absorb BVS compared to Xience V. Gene expression analyses indicated the pro-inflammatory lymphotoxin-beta receptor (LTβR) signaling pathway was significantly upregulated in arteries treated with a metallic stent compared to Absorb BVS treated arterial segments. Conclusions: At 4 years, arteries treated with Absorb BVS compared with Xience V, demonstrate significantly greater restoration of vasomotor responses. Genetic analysis suggests mechanobiologic reparation of Absorb BVS treated arteries at 4 years as opposed to Xience V treated vessels.

Accurate plaque cap thickness quantification and cap stress/strain calculations are of fundamental importance for vulnerable plaque research. To overcome uncertainties due to intravascular ultrasound (IVUS) resolution limitation, IVUS and optical coherence tomography (OCT) coronary plaque image data were combined together to obtain accurate and reliable cap thickness data, stress/strain calculations, and reliable plaque progression predictions. IVUS, OCT, and angiography baseline and follow-up data were collected from nine patients (mean age: 69; m: 5) at Cardiovascular Research Foundation with informed consent obtained. IVUS and OCT slices were coregistered and merged to form IVUS + OCT (IO) slices. A total of 114 matched slices (IVUS and OCT, baseline and follow-up) were obtained, and 3D thin-layer models were constructed to obtain stress and strain values. A generalized linear mixed model (GLMM) and least squares support vector machine (LSSVM) method were used to predict cap thickness change using nine morphological and mechanical risk factors. Prediction accuracies by all combinations (511) of those predictors with both IVUS and IO data were compared to identify optimal predictor(s) with their best accuracies. For the nine patients, the average of minimum cap thickness from IVUS was 0.17 mm, which was 26.08% lower than that from IO data (average = 0.23 mm). Patient variations of the individual errors ranged from ‒58.11 to 20.37%. For maximum cap stress between IO and IVUS, patient variations of the individual errors ranged from ‒30.40 to 46.17%. Patient variations of the individual errors of maximum cap strain values ranged from ‒19.90 to 17.65%. For the GLMM method, the optimal combination predictor using IO data had AUC (area under the ROC curve) = 0.926 and highest accuracy = 90.8%, vs. AUC = 0.783 and accuracy = 74.6% using IVUS data. For the LSSVM method, the best combination predictor using IO data had AUC = 0.838 and accuracy = 75.7%, vs. AUC = 0.780 and accuracy = 69.6% using IVUS data. This preliminary study demonstrated improved plaque cap progression prediction accuracy using accurate cap thickness data from IO slices and the differences in cap thickness, stress/strain values, and prediction results between IVUS and IO data. Large-scale studies are needed to verify our findings.