Search

Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis, prevention, and treatment. Magnetic resonance image (MRI) data of carotid atherosclerotic plaques were acquired from 20 patients with consent obtained. 3D thin-layer models were constructed to calculate plaque stress and strain. Data for ten morphological and biomechanical risk factors were extracted for analysis. Wall thickness increase (WTI), plaque burden increase (PBI) and plaque area increase (PAI) were chosen as three measures for plaque progression. Generalized linear mixed models (GLMM) with 5-fold cross-validation strategy were used to calculate prediction accuracy and identify optimal predictor. The optimal predictor for PBI was the combination of lumen area (LA), plaque area (PA), lipid percent (LP), wall thickness (WT), maximum plaque wall stress (MPWS) and maximum plaque wall strain (MPWSn) with prediction accuracy = 1.4146 (area under the receiver operating characteristic curve (AUC) value is 0.7158), while PA, plaque burden (PB), WT, LP, minimum cap thickness, MPWS and MPWSn was the best for WTI (accuracy = 1.3140, AUC = 0.6552), and a combination of PA, PB, WT, MPWS, MPWSn and average plaque wall strain (APWSn) was the best for PAI with prediction accuracy = 1.3025 (AUC = 0.6657). The combinational predictors improved prediction accuracy by 9.95%, 4.01% and 1.96% over the best single predictors for PAI, PBI and WTI (AUC values improved by 9.78%, 9.45%, and 2.14%), respectively. This suggests that combining both morphological and biomechanical risk factors could lead to better patient screening strategies., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Accurate calculation of ventricular stress and strain is critical for cardiovascular investigations. Sarcomere shortening in active contraction leads to change of ventricular zero-stress configurations during the cardiac cycle. A new model using different zero-load diastole and systole geometries was introduced to provide more accurate cardiac stress/strain calculations with potential to predict post pulmonary valve replacement (PVR) surgical outcome., Methods: Cardiac magnetic resonance (CMR) data were obtained from 16 patients with repaired tetralogy of Fallot prior to and 6 months after pulmonary valve replacement (8 male, 8 female, mean age 34.5 years). Patients were divided into Group 1 (n = 8) with better post PVR outcome and Group 2 (n = 8) with worse post PVR outcome based on their change in RV ejection fraction (EF). CMR-based patient-specific computational RV/LV models using one zero-load geometry (1G model) and two zero-load geometries (diastole and systole, 2G model) were constructed and RV wall thickness, volume, circumferential and longitudinal curvatures, mechanical stress and strain were obtained for analysis. Pairwise T-test and Linear Mixed Effect (LME) model were used to determine if the differences from the 1G and 2G models were statistically significant, with the dependence of the pair-wise observations and the patient-slice clustering effects being taken into consideration. For group comparisons, continuous variables (RV volumes, WT, C- and L- curvatures, and stress and strain values) were summarized as mean ± SD and compared between the outcome groups by using an unpaired Student t-test. Logistic regression analysis was used to identify potential morphological and mechanical predictors for post PVR surgical outcome., Results: Based on results from the 16 patients, mean begin-ejection stress and strain from the 2G model were 28% and 40% higher than that from the 1G model, respectively. Using the 2G model results, RV EF changes correlated negatively with stress (r = -0.609, P = 0.012) and with pre-PVR RV end-diastole volume (r = -0.60, P = 0.015), but did not correlate with WT, C-curvature, L-curvature, or strain. At begin-ejection, mean RV stress of Group 2 was 57.4% higher than that of Group 1 (130.1±60.7 vs. 82.7±38.8 kPa, P = 0.0042). Stress was the only parameter that showed significant differences between the two groups. The combination of circumferential curvature, RV volume and the difference between begin-ejection stress and end-ejection stress was the best predictor for post PVR outcome with an area under the ROC curve of 0.855. The begin-ejection stress was the best single predictor among the 8 individual parameters with an area under the ROC curve of 0.782., Conclusion: The new 2G model may be able to provide more accurate ventricular stress and strain calculations for potential clinical applications. Combining morphological and mechanical parameters may provide better predictions for post PVR outcome., Competing Interests: Dr. Geva is a consultant to Medtronic.

Atherosclerotic plaques may rupture without warning and cause acute cardiovascular events such as heart attack and stroke. Current clinical screening tools are insufficient to identify those patients with risks early and prevent the adverse events from happening. Medical imaging and image-based modeling have made considerable progress in recent years in identifying plaque morphological and mechanical risk factors which may be used in developing improved patient screening strategies. The key steps and factors in image-based models for human carotid and coronary plaques were illustrated, as well as grand challenges facing the researchers in the field to develop more accurate screening tools.

Objective: Patients with repaired tetralogy of Fallot account for most cases of late-onset right ventricle failure. The current surgical approach, which includes pulmonary valve replacement/insertion, has yielded mixed results. A new surgical option of placing an elastic band in the right ventricle is proposed to improve right ventricular cardiac function as measured by the ejection fraction., Methods: A total of 20 computational right ventricular/left ventricular/patch/band combination models using cardiac magnetic resonance imaging from a patient with tetralogy of Fallot were constructed to investigate the effect of band material stiffness variations, band length, and active contraction. These models included 4 different band material properties, 3 band length, 3 active contracting band materials, and models with patch and scar replaced by contracting tissue., Results: Our results indicated that the band insertion, combined with active band contraction and tissue regeneration techniques that restore right ventricular myocardium, has the potential to improve right ventricular ejection fraction by 7.5% (41.63% ejection fraction from the best active band model to more than 34.10% ejection fraction from baseline passive band model) and 4.2% (41.63% from the best active band model compared with cardiac magnetic resonance imaging-measured ejection fraction of 37.45%)., Conclusions: The cardiac magnetic resonance imaging-based right ventricular/left ventricular/patch/band model provides a proof of concept for using elastic bands to improve right ventricular cardiac function. Band insertion, combined with myocardium regeneration techniques and right ventricular remodeling surgical procedures, has the potential to improve ventricular function in patients with repaired tetralogy of Fallot and other similar forms of right ventricular dysfunction after surgery. Additional investigations using in vitro experiments, animal models, and, finally, patient studies are warranted., (Copyright © 2013 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.)

In vivo magnetic resonance image (MRI)-based computational models have been introduced to calculate atherosclerotic plaque stress and strain conditions for possible rupture predictions. However, patient-specific vessel material properties are lacking in those models, which affects the accuracy of their stress/strain predictions. A noninvasive approach of combining in vivo Cine MRI, multicontrast 3D MRI, and computational modeling was introduced to quantify patient-specific carotid artery material properties and the circumferential shrinkage rate between vessel in vivo and zero-pressure geometries. In vivo Cine and 3D multicontrast MRI carotid plaque data were acquired from 12 patients after informed consent. For each patient, one nearly-circular slice and an iterative procedure were used to quantify parameter values in the modified Mooney-Rivlin model for the vessel and the vessel circumferential shrinkage rate. A sample artery slice with and without a lipid core and three material parameter sets representing stiff, median, and soft materials from our patient data were used to demonstrate the effect of material stiffness and circumferential shrinkage process on stress/strain predictions. Parameter values of the Mooney-Rivlin models for the 12 patients were quantified. The effective Young's modulus (YM, unit: kPa) values varied from 137 (soft), 431 (median), to 1435 (stiff), and corresponding circumferential shrinkages were 32%, 12.6%, and 6%, respectively. Using the sample slice without the lipid core, the maximum plaque stress values (unit: kPa) from the soft and median materials were 153.3 and 96.2, which are 67.7% and 5% higher than that (91.4) from the stiff material, while the maximum plaque strain values from the soft and median materials were 0.71 and 0.293, which are about 700% and 230% higher than that (0.089) from the stiff material, respectively. Without circumferential shrinkages, the maximum plaque stress values (unit: kPa) from the soft, median, and stiff models were inflated to 330.7, 159.2, and 103.6, which were 116%, 65%, and 13% higher than those from models with proper shrinkage. The effective Young's modulus from the 12 human carotid arteries studied varied from 137 kPa to 1435 kPa. The vessel circumferential shrinkage to the zero-pressure condition varied from 6% to 32%. The inclusion of proper shrinkage in models based on in vivo geometry is necessary to avoid over-estimating the stresses and strains by up 100%. Material stiffness had a greater impact on strain (up to 700%) than on stress (up to 70%) predictions. Accurate patient-specific material properties and circumferential shrinkage could considerably improve the accuracy of in vivo MRI-based computational stress/strain predictions.

Patient-specific vessel material properties are in general lacking in image-based computational models. Carotid plaque stress and strain conditions with in vivo material and old material models were investigated (8 patients, 16 plaques). Plaque models using patient-specific in vivo vessel material properties showed significant differences from models using old material properties from the literature on stress and strain calculations. These differences demonstrated that models using in vivo material properties could improve the accuracy of stress and strain calculations which could potentially lead to more accurate plaque vulnerability assessment. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases are closely linked to atherosclerotic plaque development and rupture. Assessment of plaque vulnerability is of fundamental significance to cardiovascular research and disease diagnosis, prevention, treatment and management. Magnetic resonance image (MRI) data of carotid atherosclerotic plaques from 8 patients (5 male, 3 female; age: 62-83, mean=71) were acquired at the University of Washington (UW), Seattle by the Vascular Imaging Laboratory (VIL) with written informed consent obtained. Patient-specific vessel material properties were quantified using Cine MRI data for modeling use. 3D thin-layer models were used to obtain plaque stress and strain for plaque assessment. A stress-based plaque vulnerability index (SPVI) was proposed to combine mechanical analysis, plaque morphology and composition for more complete carotid plaque vulnerability assessment. The five intervals (unit: kPa) [0, 46.8), [46.8, 80), [80, 92), [92, 103), and [103, +8) from in vivo material models were used for SPVI values of 0, 1, 2, 3 and 4, respectively. The optimized agreement rate was 85.19%. The use of patient-specific material properties in plaque models could potentially improve the accuracy of model stress/strain calculations. SPVI has the potential to improve the current image-based screening and plaque vulnerability assessment schemes. [ABSTRACT FROM AUTHOR]

Background: Image-based computational models are widely used to determine atherosclerotic plaque stress/strain conditions and investigate their association with plaque progression and rupture. However, patient-specific vessel material properties are in general lacking in those models, limiting the accuracy of their stress/strain measurements. A noninvasive approach of combining in vivo 3D multi-contrast and Cine magnetic resonance imaging (MRI) and computational modeling was introduced to quantify patient-specific carotid plaque material properties for potential plaque model improvements. Vessel material property variation in patients, along vessel segment, and between baseline and follow up were investigated. Methods: In vivo 3D multi-contrast and Cine MRI carotid plaque data were acquired from 8 patients with follow-up (18 months) with written informed consent obtained. 3D thin-layer models and an established iterative procedure were used to determine parameter values of the Mooney-Rivlin models for the 81slices from 16 plaque samples. Effective Young’s Modulus (YM) values were calculated for comparison and analysis. Results: Average Effective Young’s Modulus (YM) and circumferential shrinkage rate (C-Shrink) value of the 81 slices was 411kPa and 5.62%, respectively. Slice YM value varied from 70 kPa (softest) to 1284 kPa (stiffest), a 1734% difference. Average slice YM values by vessel varied from 109 kPa (softest) to 922 kPa (stiffest), a 746% difference. Location-wise, the maximum slice YM variation rate within a vessel was 311% (149 kPa vs. 613 kPa). The average slice YM variation rate for the 16 vessels was 134%. The average variation of YM values for all patients from baseline to follow up was 61.0%. The range of the variation of YM values was [-28.4%, 215%]. For plaque progression study, YM at follow-up showed negative correlation with plaque progression measured by wall thickness increase (WTI) (r = -0.7764, p = 0.0235). Wall thickness at baseline correlated with WTI negatively, with r = -0.5253 (p = 0.1813). Plaque burden at baseline correlated with YM change between baseline and follow-up, with r = 0.5939 (p = 0.1205). Conclusion: In vivo carotid vessel material properties have large variations from patient to patient, along the diseased segment within a patient, and with time. The use of patient-specific, location specific and time-specific material properties in plaque models could potentially improve the accuracy of model stress/strain calculations. [ABSTRACT FROM AUTHOR]

The article discusses research which examined the vulnerability of carotid atherosclerotic plaque with the use of three-dimensional (3D) thin-layer model with patient-specific material properties. Topics discussed include the accuracy of image-based computational models and combining in vivo 3D multi-contrast and Cine magnetic resonance imaging (MRI) and computational models. It cited the improved accuracy of model stress/strain calculations with patient-specific material properties.

Plaque morphology and biomechanics are believed to be closely associated with plaque progression. In this paper, we test the hypothesis that integrating morphological and biomechanical risk factors would result in better predictive power for plaque progression prediction. A sample size of 374 intravascular ultrasound (IVUS) slices was obtained from 9 patients with IVUS follow-up data. 3D fluid-structure interaction models were constructed to obtain both structural stress/strain and fluid biomechanical conditions. Data for eight morphological and biomechanical risk factors were extracted for each slice. Plaque area increase (PAI) and wall thickness increase (WTI) were chosen as two measures for plaque progression. Progression measure and risk factors were fed to generalized linear mixed models and linear mixed-effect models to perform prediction and correlation analysis, respectively. All combinations of eight risk factors were exhausted to identify the optimal predictor(s) with highest prediction accuracy defined as sum of sensitivity and specificity. When using a single risk factor, plaque wall stress (PWS) at baseline was the best predictor for plaque progression (PAI and WTI). The optimal predictor among all possible combinations for PAI was PWS + PWSn + Lipid percent + Min cap thickness + Plaque Area (PA) + Plaque Burden (PB) (prediction accuracy = 1.5928) while Wall Thickness (WT) + Plaque Wall Strain (PWSn) + Plaque Area (PA) was the best for WTI (1.2589). This indicated that PAI was a more predictable measure than WTI. The combination including both morphological and biomechanical parameters had improved prediction accuracy, compared to predictions using only morphological features. [ABSTRACT FROM AUTHOR]

In vivo magnetic resonance image (MRI)-based computational models have been introduced to calculate atherosclerotic plaque stress and strain conditions for possible rupture predictions. However, patient-specific vessel material properties are lacking in those models, which affects the accuracy of their stress/strain predictions. A noninvasive approach of combining in vivo Cine MRI, multicontrast 3D MRI, and computational modeling was introduced to quantify patient-specific carotid artery material properties and the circumferential shrinkage rate between vessel in vivo and zero-pressure geometries. In vivo Cine and 3D multicontrast MRI carotid plaque data were acquired from 12 patients after informed consent. For each patient, one nearly-circular slice and an iterative procedure were used to quantify parameter values in the modified Mooney-Rivlin model for the vessel and the vessel circumferential shrinkage rate. A sample artery slice with and without a lipid core and three material parameter sets representing stiff, median, and soft materials from our patient data were used to demonstrate the effect of material stiffness and circumferential shrinkage process on stress/strain predictions. Parameter values of the Mooney-Rivlin models for the 12 patients were quantified. The effective Young's modulus (YM, unit: kPa) values varied from 137 (soft), 431 (median), to 1435 (stiff), and corresponding circumferential shrinkages were 32%, 12.6%, and 6%, respectively. Using the sample slice without the lipid core, the maximum plaque stress values (unit: kPa) from the soft and median materials were 153.3 and 96.2, which are 67.7% and 5% higher than that (91.4)from the stiff material, while the maximum plaque strain values from the soft and median materials were 0.71 and 0.293. which are about 700% and 230% higher than that (0.089) from the stiff material, respectively. Without circumferential shrinkages, the maximum plaque stress values (unit. kPa) from the soft, median, and stiff models were inflated to 330.7, 159.2, and 103.6, which were 116%, 65%, and 13% higher than those front models with proper shrinkage. The effective Young's modulus from the 12 human carotid arteries studied varied from 137 kPa to 1435 kPa. The vessel circumferential shrinkage to the zero-pressure condition varied from 6% to 32%. The inclusion of proper shrinkage in models based on in vivo geometry is necessary to avoid over-estimating the stresses and strains by up 100%. Material stiffness had a greater impact on strain (up to 700%) than on stress (up to 70%) predictions. Accurate patient-specific material properties and circumferential shrinkage could considerably improve the accuracy of in vivo MRI-based computational stress/strain predictions. [ABSTRACT FROM AUTHOR]

Heart attack and stroke are often caused by atherosclerotic plaque rupture, which happens without warning most of the time. Magnetic resonance imaging (MRI)-based atherosclerotic plaque models with fluid-structure interactions (FSIs) have been introduced to perform flow and stress/strain analysis and identify possible mechanical and morphological indices for accurate plaque vulnerability assessment. For coronary arteries, cyclic bending associated with heart motion and anisotropy of the vessel walls may have significant influence on flow and stress/strain distributions in the plaque. FSI models with cyclic bending and anisotropic vessel properties for coronary plaques are lacking in the current literature. In this paper, cyclic bending and anisotropic vessel properties were added to 3D FSI coronary plaque models so that the models would be more realistic for more accurate computational flow and stress/strain predictions. Six computational models using one ex vivo MRI human coronary plaque specimen data were constructed to assess the effects of cyclic bending, anisotropic vessel properties, pulsating pressure, plaque structure, and axial stretch on plaque stress/strain distributions. Our results indicate that cyclic bending and anisotropic properties may cause 50-800% increase in maximum principal stress (Stress-P1) values at selected locations. The stress increase varies with location and is higher when bending is coupled with axial stretch, nonsmooth plaque structure, and resonant pressure conditions (zero phase angle shift). Effects of cyclic bending on flow behaviors are more modest (9.8% decrease in maximum velocity, 2.5% decrease in flow rate, 15% increase in maximum flow shear stress). Inclusion of cyclic bending, anisotropic vessel material properties, accurate plaque structure, and axial stretch in computational FSI models should lead to a considerable improvement of accuracy of computational stress/strain predictions for coronary plaque vulnerability assessment. Further studies incorporating additional mechanical property data and in vivo MRI data are needed to obtain more complete and accurate knowledge about flow and stress/strain behaviors in coronary plaques and to identify critical indicators for better plaque assessment and possible rupture predictions. [ABSTRACT FROM AUTHOR]

Heart attack and stroke are often caused by atherosclerotic plaque rupture, which happens without warning most of the time. Magnetic resonance imaging (MRI)-based atherosclerotic plaque models with fluid-structure interactions (FSIs) have been introduced to perform flow and stress/strain analysis and identify possible mechanical and morphological indices for accurate plaque vulnerability assessment. For coronary arteries, cyclic bending associated with heart motion and anisotropy of the vessel walls may have significant influence on flow and stress/strain distributions in the plaque. FSI models with cyclic bending and anisotropic vessel properties for coronary plaques are lacking in the current literature. In this paper, cyclic bending and anisotropic vessel properties were added to 3D FSI coronary plaque models so that the models would be more realistic for more accurate computational flow and stress/strain predictions. Six computational models using one ex vivo MRI human coronary plaque specimen data were constructed to assess the effects of cyclic bending, anisotropic vessel properties, pulsating pressure, plaque structure, and axial stretch on plaque stress/strain distributions. Our results indicate that cyclic bending and anisotropic properties may cause 50-800% increase in maximum principal stress (Stress-P1) values at selected locations. The stress increase varies with location and is higher when bending is coupled with axial stretch, nonsmooth plaque structure, and resonant pressure conditions (zero phase angle shift). Effects of cyclic bending on flow behaviors are more modest (9.8% decrease in maximum velocity, 2.5% decrease in flow rate, 15% increase in maximum flow shear stress). Inclusion of cyclic bending, anisotropic vessel material properties, accurate plaque structure, and axial stretch in computational FSI models should lead to a considerable improvement of accuracy of computational stress/strain predictions for coronary plaque vulnerability assessment. Further studies incorporating additional mechanical property data and in vivo MRI data are needed to obtain more complete and accurate knowledge about flow and stress/strain behaviors in coronary plaques and to identify critical indicators for better plaque assessment and possible rupture predictions. [ABSTRACT FROM AUTHOR]