Plaque Ruptures Are Related to High Plaque Stress and Strain Conditions: Direct Verification by Using In Vivo OCT Rupture Data and FSI Models.

BACKGROUND: While it has been hypothesized that high plaque stress and strain may be related to plaque rupture, its direct verification using in vivo coronary plaque rupture data and full 3-dimensional fluid-structure interaction models is lacking in the current literature due to difficulty in obtaining in vivo plaque rupture imaging data from patients with acute coronary syndrome. This case-control study aims to use high-resolution optical coherence tomography-verified in vivo plaque rupture data and 3-dimensional fluid-structure interaction models to seek direct evidence for the high plaque stress/strain hypothesis. METHODS: In vivo coronary plaque optical coherence tomography data (5 ruptured plaques, 5 no-rupture plaques) were acquired from patients using a protocol approved by the local institutional review board with informed consent obtained. The ruptured caps were reconstructed to their prerupture morphology using neighboring plaque cap and vessel geometries. Optical coherence tomography-based 3-dimensional fluid-structure interaction models were constructed to obtain plaque stress, strain, and flow shear stress data for comparative analysis. The rank-sum test in the nonparametric test was used for statistical analysis. RESULTS: Our results showed that the average maximum cap stress and strain values of ruptured plaques were 142% (457.70 versus 189.22 kPa; P=0.0278) and 48% (0.2267 versus 0.1527 kPa; P=0.0476) higher than that for no-rupture plaques, respectively. The mean values of maximum flow shear stresses for ruptured and no-rupture plaques were 145.02 dyn/cm2 and 81.92 dyn/cm2 (P=0.1111), respectively. However, the flow shear stress difference was not statistically significant. CONCLUSIONS: This preliminary case-control study showed that the ruptured plaque group had higher mean maximum stress and strain values. Due to our small study size, larger scale studies are needed to further validate our findings.

Impact of Right Ventricular Surface Area-to-Volume Ratio on Ventricular Remodeling After Pulmonary Valve Replacement.

Optimal reverse remodeling of the right ventricle (RV), a sentinel goal of pulmonary valve replacement (PVR) in patients with repaired tetralogy of Fallot, is not fully predicted by volume-based pre-PVR parameters. Our objectives were to characterize novel geometric RV parameters in patients receiving PVR and in controls, and to identify associations between these parameters and chamber remodeling post-PVR. Secondary analysis was performed on cardiac magnetic resonance (CMR) data from 60 patients enrolled in a randomized trial of PVR with and without surgical RV remodeling. 20 healthy age-matched subjects served as controls. The primary outcome was optimal post-PVR RV remodeling (end-diastolic volume index (EDVi) ≤ 114 ml/m2 and ejection fraction (EF) ≥ 48%) vs. suboptimal remodeling (EDVi ≥ 120 ml/m2 and EF ≤ 45%). RV geometry was markedly different at baseline in PVR patients compared with controls, with lower systolic surface area-to-volume ratio (SAVR) (1.16 ± 0.26 vs.1.44 ± 0.21 cm2/mL, p < 0.001) and lower systolic circumferential curvature (0.87 ± 0.27 vs. 1.07 ± 0.30 cm- 1, p = 0.007) but similar longitudinal curvature. In the PVR cohort, higher systolic SAVR was associated with higher RVEF both pre- and post-PVR (p < 0.001). Among PVR patients, 15 had optimal and 19 had suboptimal remodeling post-PVR. Multivariable modeling showed that among the geometric parameters, higher systolic SAVR (OR 1.68 per 0.1 cm2/mL increase; p = 0.049) and shorter systolic RV long-axis length (OR 0.92 per 0.1 cm increase; p = 0.035) were independently associated with optimal remodeling. Compared with controls, PVR patients have lower SAVR and lower circumferential but not longitudinal curvature. Higher pre-PVR systolic SAVR is associated with optimal remodeling post-PVR.

Hemodynamic Mimic Shear Stress for Platelet Membrane Nanobubbles Preparation and Integrin αIIbß3 Conformation Regulation.

Platelet (PLT) membrane biomimetic nanomaterials have become promising theranostic platforms due to their good biocompatibility and effectiveness. However, in order to achieve precise regulation of cell membrane components, novel controllable construction approaches need to be developed. Inspired by the interaction mechanism among platelet production, activation, and dynamic biomechanical signals in blood circulation, here a platelet nanobubbles (PNBs) with reassembled platelet membrane with ideal echogenicity was fabricated using an adjustable pressure-induced shear stress method. The results demonstrate that the high shear stress during PNBs fabrication led to the enrichment of platelet membrane lipid rafts and proteins, as well as their reassembly on the gas-liquid interface. More importantly, the conformation of platelet integrin αIIbß3 was transformed into a shear stress-induced intermediate affinity state, which gives PNBs enhanced adhesion ability to the vascular endothelial injury. Taken together, these PNBs have great application potential in the specifically targeted ultrasound diagnosis of vascular endothelial injury.

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

[This corrects the article DOI: 10.1371/journal.pcbi.1008344.].

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.

Comparisons of simulation results between passive and active fluid structure interaction models for left ventricle in hypertrophic obstructive cardiomyopathy.

BACKGROUND: Patient-specific active fluid-structure interactions (FSI) model is a useful approach to non-invasively investigate the hemodynamics in the heart. However, it takes a lot of effort to obtain the proper external force boundary conditions for active models, which heavily restrained the time-sensitive clinical applications of active computational models. METHODS: The simulation results of 12 passive FSI models based on 6 patients' pre-operative and post-operative CT images were compared with corresponding active models to investigate the differences in hemodynamics and cardiac mechanics between these models. RESULTS: In comparing the passive and active models, it was found that there was no significant difference in pressure difference and shear stress on mitral valve leaflet (MVL) at the pre-SAM time point, but a significant difference was found in wall stress on the inner boundary of left ventricle (endocardium). It was also found that pressure difference on the coapted MVL and the shear stress on MVL were significantly decreased after successful surgery in both active and passive models. CONCLUSION: Our results suggested that the passive models may provide good approximated hemodynamic results at 5% RR interval, which is crucial for analyzing the initiation of systolic anterior motion (SAM). Comparing to active models, the passive models decrease the complexity of the modeling construction and the difficulty of convergence significantly. These findings suggest that, with proper boundary conditions and sufficient clinical data, the passive computational model may be a good substitution model for the active model to perform hemodynamic analysis of the initiation of SAM.

Predicting plaque vulnerability change using intravascular ultrasound + optical coherence tomography image-based fluid-structure interaction models and machine learning methods with patient follow-up data: a feasibility study.

BACKGROUND: Coronary plaque vulnerability prediction is difficult because plaque vulnerability is non-trivial to quantify, clinically available medical image modality is not enough to quantify thin cap thickness, prediction methods with high accuracies still need to be developed, and gold-standard data to validate vulnerability prediction are often not available. Patient follow-up intravascular ultrasound (IVUS), optical coherence tomography (OCT) and angiography data were acquired to construct 3D fluid-structure interaction (FSI) coronary models and four machine-learning methods were compared to identify optimal method to predict future plaque vulnerability. METHODS: Baseline and 10-month follow-up in vivo IVUS and OCT coronary plaque data were acquired from two arteries of one patient using IRB approved protocols with informed consent obtained. IVUS and OCT-based FSI models were constructed to obtain plaque wall stress/strain and wall shear stress. Forty-five slices were selected as machine learning sample database for vulnerability prediction study. Thirteen key morphological factors from IVUS and OCT images and biomechanical factors from FSI model were extracted from 45 slices at baseline for analysis. Lipid percentage index (LPI), cap thickness index (CTI) and morphological plaque vulnerability index (MPVI) were quantified to measure plaque vulnerability. Four machine learning methods (least square support vector machine, discriminant analysis, random forest and ensemble learning) were employed to predict the changes of three indices using all combinations of 13 factors. A standard fivefold cross-validation procedure was used to evaluate prediction results. RESULTS: For LPI change prediction using support vector machine, wall thickness was the optimal single-factor predictor with area under curve (AUC) 0.883 and the AUC of optimal combinational-factor predictor achieved 0.963. For CTI change prediction using discriminant analysis, minimum cap thickness was the optimal single-factor predictor with AUC 0.818 while optimal combinational-factor predictor achieved an AUC 0.836. Using random forest for predicting MPVI change, minimum cap thickness was the optimal single-factor predictor with AUC 0.785 and the AUC of optimal combinational-factor predictor achieved 0.847. CONCLUSION: This feasibility study demonstrated that machine learning methods could be used to accurately predict plaque vulnerability change based on morphological and biomechanical factors from multi-modality image-based FSI models. Large-scale studies are needed to verify our findings.

Optical Coherence Tomography-Based Patient-Specific Residual Multi-Thrombus Coronary Plaque Models With Fluid-Structure Interaction for Better Treatment Decisions: A Biomechanical Modeling Case Study.

Intracoronary thrombus from plaque erosion could cause fatal acute coronary syndrome (ACS). A conservative antithrombotic therapy has been proposed to treat ACS patients in lieu of stenting. It is speculated that the residual thrombus after aspiration thrombectomy would influence the prognosis of this treatment. However, biomechanical mechanisms affecting intracoronary thrombus remodeling and clinical outcome remain largely unknown. in vivo optical coherence tomography (OCT) data of a coronary plaque with two residual thrombi after antithrombotic therapy were acquired from an ACS patient with consent obtained. Three OCT-based fluid-structure interaction (FSI) models with different thrombus volumes, fluid-only, and structure-only models were constructed to simulate and compare the biomechanical interplay among blood flow, residual thrombus, and vessel wall mimicking different clinical situations. Our results showed that residual thrombus would decrease coronary volumetric flow rate by 9.3%, but elevate wall shear stress (WSS) by 29.4% and 75.5% at thrombi 1 and 2, respectively. WSS variations in a cardiac cycle from structure-only model were 12.1% and 13.5% higher at the two thrombus surfaces than those from FSI model. Intracoronary thrombi were subjected to compressive forces indicated by negative thrombus stress. Tandem intracoronary thrombus might influence coronary hemodynamics and solid mechanics differently. Computational modeling could be used to quantify biomechanical conditions under which patients could receive patient-specific treatment plan with optimized outcome after antithrombotic therapy. More patient studies with follow-up data are needed to continue the investigation and better understand mechanisms governing thrombus remodeling process.

Using optical coherence tomography and intravascular ultrasound imaging to quantify coronary plaque cap thickness and vulnerability: a pilot study.

BACKGROUND: Detecting coronary vulnerable plaques in vivo and assessing their vulnerability have been great challenges for clinicians and the research community. Intravascular ultrasound (IVUS) is commonly used in clinical practice for diagnosis and treatment decisions. However, due to IVUS limited resolution (about 150-200 µm), it is not sufficient to detect vulnerable plaques with a threshold cap thickness of 65 µm. Optical Coherence Tomography (OCT) has a resolution of 15-20 µm and can measure fibrous cap thickness more accurately. The aim of this study was to use OCT as the benchmark to obtain patient-specific coronary plaque cap thickness and evaluate the differences between OCT and IVUS fibrous cap quantifications. A cap index with integer values 0-4 was also introduced as a quantitative measure of plaque vulnerability to study plaque vulnerability. METHODS: Data from 10 patients (mean age: 70.4; m: 6; f: 4) with coronary heart disease who underwent IVUS, OCT, and angiography were collected at Cardiovascular Research Foundation (CRF) using approved protocol with informed consent obtained. 348 slices with lipid core and fibrous caps were selected for study. Convolutional Neural Network (CNN)-based and expert-based data segmentation were performed using established methods previously published. Cap thickness data were extracted to quantify differences between IVUS and OCT measurements. RESULTS: For the 348 slices analyzed, the mean value difference between OCT and IVUS cap thickness measurements was 1.83% (p = 0.031). However, mean value of point-to-point differences was 35.76%. Comparing minimum cap thickness for each plaque, the mean value of the 20 plaque IVUS-OCT differences was 44.46%, ranging from 2.36% to 91.15%. For cap index values assigned to the 348 slices, the disagreement between OCT and IVUS assignments was 25%. However, for the OCT cap index = 2 and 3 groups, the disagreement rates were 91% and 80%, respectively. Furthermore, the observation of cap index changes from baseline to follow-up indicated that IVUS results differed from OCT by 80%. CONCLUSIONS: These preliminary results demonstrated that there were significant differences between IVUS and OCT plaque cap thickness measurements. Large-scale patient studies are needed to confirm our findings.

A Multimodality Image-Based Fluid-Structure Interaction Modeling Approach for Prediction of Coronary Plaque Progression Using IVUS and Optical Coherence Tomography Data With Follow-Up.

Medical image resolution has been a serious limitation in plaque progression research. A modeling approach combining intravascular ultrasound (IVUS) and optical coherence tomography (OCT) was introduced and patient follow-up IVUS and OCT data were acquired to construct three-dimensional (3D) coronary models for plaque progression investigations. Baseline and follow-up in vivo IVUS and OCT coronary plaque data were acquired from one patient with 105 matched slices selected for model construction. 3D fluid-structure interaction (FSI) models based on IVUS and OCT data (denoted as IVUS + OCT model) were constructed to obtain stress/strain and wall shear stress (WSS) for plaque progression prediction. IVUS-based IVUS50 and IVUS200 models were constructed for comparison with cap thickness set as 50 and 200 µm, respectively. Lumen area increase (LAI), plaque area increase (PAI), and plaque burden increase (PBI) were chosen to measure plaque progression. The least squares support vector machine (LS-SVM) method was employed for plaque progression prediction using 19 risk factors. For IVUS + OCT model with LAI, PAI, and PBI, the best single predictor was plaque strain, local plaque stress, and minimal cap thickness, with prediction accuracy as 0.766, 0.838, and 0.890, respectively; the prediction accuracy using best combinations of 19 factors was 0.911, 0.881, and 0.905, respectively. Compared to IVUS + OCT model, IVUS50, and IVUS200 models had errors ranging from 1% to 66.5% in quantifying cap thickness, stress, strain and prediction accuracies. WSS showed relatively lower prediction accuracy compared to other predictors in all nine prediction studies.

Combining IVUS and Optical Coherence Tomography for More Accurate Coronary Cap Thickness Quantification and Stress/Strain Calculations: A Patient-Specific Three-Dimensional Fluid-Structure Interaction Modeling Approach.

Accurate cap thickness and stress/strain quantifications are of fundamental importance for vulnerable plaque research. Virtual histology intravascular ultrasound (VH-IVUS) sets cap thickness to zero when cap is under resolution limit and IVUS does not see it. An innovative modeling approach combining IVUS and optical coherence tomography (OCT) is introduced for cap thickness quantification and more accurate cap stress/strain calculations. In vivo IVUS and OCT coronary plaque data were acquired with informed consent obtained. IVUS and OCT images were merged to form the IVUS + OCT data set, with biplane angiography providing three-dimensional (3D) vessel curvature. For components where VH-IVUS set zero cap thickness (i.e., no cap), a cap was added with minimum cap thickness set as 50 and 180 µm to generate IVUS50 and IVUS180 data sets for model construction, respectively. 3D fluid-structure interaction (FSI) models based on IVUS + OCT, IVUS50, and IVUS180 data sets were constructed to investigate cap thickness impact on stress/strain calculations. Compared to IVUS + OCT, IVUS50 underestimated mean cap thickness (27 slices) by 34.5%, overestimated mean cap stress by 45.8%, (96.4 versus 66.1 kPa). IVUS50 maximum cap stress was 59.2% higher than that from IVUS + OCT model (564.2 versus 354.5 kPa). Differences between IVUS and IVUS + OCT models for cap strain and flow shear stress (FSS) were modest (cap strain <12%; FSS <6%). IVUS + OCT data and models could provide more accurate cap thickness and stress/strain calculations which will serve as basis for further plaque investigations.

Stiffness Properties of Adventitia, Media, and Full Thickness Human Atherosclerotic Carotid Arteries in the Axial and Circumferential Directions.

Arteries can be considered as layered composite material. Experimental data on the stiffness of human atherosclerotic carotid arteries and their media and adventitia layers are very limited. This study used uniaxial tests to determine the stiffness (tangent modulus) of human carotid artery sections containing American Heart Association type II and III lesions. Axial and circumferential oriented adventitia, media, and full thickness specimens were prepared from six human carotid arteries (total tissue strips: 71). Each artery yielded 12 specimens with two specimens in each of the following six categories; axial full thickness, axial adventitia (AA), axial media (AM), circumferential full thickness, circumferential adventitia (CA), and circumferential media (CM). Uniaxial testing was performed using Inspec 2200 controlled by software developed using labview. The mean stiffness of the adventitia was 3570 ± 667 and 2960 ± 331 kPa in the axial and circumferential directions, respectively, while the corresponding values for the media were 1070 ± 186 and 1800 ± 384 kPa. The adventitia was significantly stiffer than the media in both the axial (p = 0.003) and circumferential (p = 0.010) directions. The stiffness of the full thickness specimens was nearly identical in the axial (1540 ± 186) and circumferential (1530 ± 389 kPa) directions. The differences in axial and circumferential stiffness of media and adventitia were not statistically significant.

Effects of Residual Stress, Axial Stretch, and Circumferential Shrinkage on Coronary Plaque Stress and Strain Calculations: A Modeling Study Using IVUS-Based Near-Idealized Geometries.

Accurate stress and strain calculations are important for plaque progression and vulnerability assessment. Models based on in vivo data often need to form geometries with zero-stress/strain conditions. The goal of this paper is to use IVUS-based near-idealized geometries and introduce a three-step model construction process to include residual stress, axial shrinkage, and circumferential shrinkage and investigate their impacts on stress and strain calculations. In Vivo intravascular ultrasound (IVUS) data of human coronary were acquired for model construction. In Vivo IVUS movie data were acquired and used to determine patient-specific material parameter values. A three-step modeling procedure was used to make our model: (a) wrap the zero-stress vessel sector to obtain the residual stress; (b) stretch the vessel axially to its length in vivo; and (c) pressurize the vessel to recover its in vivo geometry. Eight models were constructed for our investigation. Wrapping led to reduced lumen and cap stress and increased out boundary stress. The model with axial stretch, circumferential shrink, but no wrapping overestimated lumen and cap stress by 182% and 448%, respectively. The model with wrapping, circumferential shrink, but no axial stretch predicted average lumen stress and cap stress as 0.76 kPa and -15 kPa. The same model with 10% axial stretch had 42.53 kPa lumen stress and 29.0 kPa cap stress, respectively. Skipping circumferential shrinkage leads to overexpansion of the vessel and incorrect stress/strain calculations. Vessel stiffness increase (100%) leads to 75% lumen stress increase and 102% cap stress increase.

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.

Material stiffness parameters as potential predictors of presence of left ventricle myocardial infarction: 3D echo-based computational modeling study.

BACKGROUND: Ventricle material properties are difficult to obtain under in vivo conditions and are not readily available in the current literature. It is also desirable to have an initial determination if a patient had an infarction based on echo data before more expensive examinations are recommended. A noninvasive echo-based modeling approach and a predictive method were introduced to determine left ventricle material parameters and differentiate patients with recent myocardial infarction (MI) from those without. METHODS: Echo data were obtained from 10 patients, 5 with MI (Infarct Group) and 5 without (Non-Infarcted Group). Echo-based patient-specific computational left ventricle (LV) models were constructed to quantify LV material properties. All patients were treated equally in the modeling process without using MI information. Systolic and diastolic material parameter values in the Mooney-Rivlin models were adjusted to match echo volume data. The equivalent Young's modulus (YM) values were obtained for each material stress-strain curve by linear fitting for easy comparison. Predictive logistic regression analysis was used to identify the best parameters for infract prediction. RESULTS: The LV end-systole material stiffness (ES-YMf) was the best single predictor among the 12 individual parameters with an area under the receiver operating characteristic (ROC) curve of 0.9841. LV wall thickness (WT), material stiffness in fiber direction at end-systole (ES-YMf) and material stiffness variation (∆YMf) had positive correlations with LV ejection fraction with correlation coefficients r = 0.8125, 0.9495 and 0.9619, respectively. The best combination of parameters WT + ∆YMf was the best over-all predictor with an area under the ROC curve of 0.9951. CONCLUSION: Computational modeling and material stiffness parameters may be used as a potential tool to suggest if a patient had infarction based on echo data. Large-scale clinical studies are needed to validate these preliminary findings.

Influence of model boundary conditions on blood flow patterns in a patient specific stenotic right coronary artery.

BACKGROUND: In literature, the effect of the inflow boundary condition was investigated by examining the impact of the waveform and the shape of the spatial profile of the inlet velocity on the cardiac hemodynamics. However, not much work has been reported on comparing the effect of the different combinations of the inlet/outlet boundary conditions on the quantification of the pressure field and flow distribution patterns in stenotic right coronary arteries. METHOD: Non-Newtonian models were used to simulate blood flow in a patient-specific stenotic right coronary artery and investigate the influence of different boundary conditions on the phasic variation and the spatial distribution patterns of blood flow. The 3D geometry of a diseased artery segment was reconstructed from a series of IVUS slices. Five different combinations of the inlet and the outlet boundary conditions were tested and compared. RESULTS: The temporal distribution patterns and the magnitudes of the velocity, the wall shear stress (WSS), the pressure, the pressure drop (PD), and the spatial gradient of wall pressure (WPG) were different when boundary conditions were imposed using different pressure/velocity combinations at inlet/outlet. The maximum velocity magnitude in a cardiac cycle at the center of the inlet from models with imposed inlet pressure conditions was about 29% lower than that from models using fully developed inlet velocity data. Due to the fact that models with imposed pressure conditions led to blunt velocity profile, the maximum wall shear stress at inlet in a cardiac cycle from models with imposed inlet pressure conditions was about 29% higher than that from models with imposed inlet velocity boundary conditions. When the inlet boundary was imposed by a velocity waveform, the models with different outlet boundary conditions resulted in different temporal distribution patterns and magnitudes of the phasic variation of pressure. On the other hand, the type of different boundary conditions imposed at the inlet and the outlet did not have significant effect on the spatial distribution patterns of the PD, the WPG and the WSS on the lumen surface, regarding the locations of the maximum and the minimum of each quantity. CONCLUSIONS: The observations from this study indicated that the ways how pressure and velocity boundary conditions are imposed in computational models have considerable impact on flow velocity and shear stress predictions. Accuracy of in vivo measurements of blood pressure and velocity is of great importance for reliable model predictions.

Magnetic microbubble-mediated ultrasound-MRI registration based on robust optical flow model.

BACKGROUND: As a dual-modality contrast agent, magnetic microbubbles (MMBs) can not only improve contrast of ultrasound (US) image, but can also serve as a contrast agent of magnetic resonance image (MRI). With the help of MMBs, a new registration method between US image and MRI is presented. METHODS: In this method, MMBs were used in both ultrasound and magnetic resonance imaging process to enhance the most important information of interest. In order to reduce the influence of the speckle noise to registration, semi-automatic segmentations of US image and MRI were carried out by using active contour model. After that, a robust optical flow model between US image segmentation (floating image) and MRI segmentation (reference image) was built, and the vector flow field was estimated by using the Coarse-to-fine Gaussian pyramid and graduated non-convexity (GNC) schemes. RESULTS: Qualitative and quantitative analyses of multiple group comparison experiments showed that registration results using all methods tested in this paper without MMBs were unsatisfactory. On the contrary, the proposed method combined with MMBs led to the best registration results. CONCLUSION: The proposed algorithm combined with MMBs contends with larger deformation and performs well not only for local deformation but also for global deformation. The comparison experiments also demonstrated that ultrasound-MRI registration using the above-mentioned method might be a promising method for obtaining more accurate image information.

Infarcted Left Ventricles Have Stiffer Material Properties and Lower Stiffness Variation: Three-Dimensional Echo-Based Modeling to Quantify In Vivo Ventricle Material Properties.

Methods to quantify ventricle material properties noninvasively using in vivo data are of great important in clinical applications. An ultrasound echo-based computational modeling approach was proposed to quantify left ventricle (LV) material properties, curvature, and stress/strain conditions and find differences between normal LV and LV with infarct. Echo image data were acquired from five patients with myocardial infarction (I-Group) and five healthy volunteers as control (H-Group). Finite element models were constructed to obtain ventricle stress and strain conditions. Material stiffening and softening were used to model ventricle active contraction and relaxation. Systolic and diastolic material parameter values were obtained by adjusting the models to match echo volume data. Young's modulus (YM) value was obtained for each material stress-strain curve for easy comparison. LV wall thickness, circumferential and longitudinal curvatures (C- and L-curvature), material parameter values, and stress/strain values were recorded for analysis. Using the mean value of H-Group as the base value, at end-diastole, I-Group mean YM value for the fiber direction stress-strain curve was 54% stiffer than that of H-Group (136.24 kPa versus 88.68 kPa). At end-systole, the mean YM values from the two groups were similar (175.84 kPa versus 200.2 kPa). More interestingly, H-Group end-systole mean YM was 126% higher that its end-diastole value, while I-Group end-systole mean YM was only 29% higher that its end-diastole value. This indicated that H-Group had much greater systole-diastole material stiffness variations. At beginning-of-ejection (BE), LV ejection fraction (LVEF) showed positive correlation with C-curvature, stress, and strain, and negative correlation with LV volume, respectively. At beginning-of-filling (BF), LVEF showed positive correlation with C-curvature and strain, but negative correlation with stress and LV volume, respectively. Using averaged values of two groups at BE, I-Group stress, strain, and wall thickness were 32%, 29%, and 18% lower (thinner), respectively, compared to those of H-Group. L-curvature from I-Group was 61% higher than that from H-Group. Difference in C-curvature between the two groups was not statistically significant. Our results indicated that our modeling approach has the potential to determine in vivo ventricle material properties, which in turn could lead to methods to infer presence of infarct from LV contractibility and material stiffness variations. Quantitative differences in LV volume, curvatures, stress, strain, and wall thickness between the two groups were provided.

Human coronary plaque wall thickness correlated positively with flow shear stress and negatively with plaque wall stress: an IVUS-based fluid-structure interaction multi-patient study.

BACKGROUND: Atherosclerotic plaque progression and rupture are believed to be associated with mechanical stress conditions. In this paper, patient-specific in vivo intravascular ultrasound (IVUS) coronary plaque image data were used to construct computational models with fluid-structure interaction (FSI) and cyclic bending to investigate correlations between plaque wall thickness and both flow shear stress and plaque wall stress conditions. METHODS: IVUS data were acquired from 10 patients after voluntary informed consent. The X-ray angiogram was obtained prior to the pullback of the IVUS catheter to determine the location of the coronary artery stenosis, vessel curvature and cardiac motion. Cyclic bending was specified in the model representing the effect by heart contraction. 3D anisotropic FSI models were constructed and solved to obtain flow shear stress (FSS) and plaque wall stress (PWS) values. FSS and PWS values were obtained for statistical analysis. Correlations with p < 0.05 were deemed significant. RESULTS: Nine out of the 10 patients showed positive correlation between wall thickness and flow shear stress. The mean Pearson correlation r-value was 0.278 ± 0.181. Similarly, 9 out of the 10 patients showed negative correlation between wall thickness and plaque wall stress. The mean Pearson correlation r-value was -0.530 ± 0.210. CONCLUSION: Our results showed that plaque vessel wall thickness correlated positively with FSS and negatively with PWS. The patient-specific IVUS-based modeling approach has the potential to be used to investigate and identify possible mechanisms governing plaque progression and rupture and assist in diagnosis and intervention procedures. This represents a new direction of research. Further investigations using more patient follow-up data are warranted.