Impact of Patient-Specific In Vivo Vessel Material Properties on Carotid Atherosclerotic Plaque Stress/Strain Calculations

2019 ◽  
Vol 16 (03) ◽  
pp. 1842002 ◽  
Author(s):  
Qingyu Wang ◽  
Dalin Tang ◽  
Gador Canton ◽  
Thomas S. Hatsukami ◽  
Kristen L. Billiar ◽  
...  
Keyword(s):  
Material Properties ◽  
Carotid Plaque ◽  
Computational Models ◽  
Patient Specific ◽  
Stress And Strain ◽  
Carotid Atherosclerotic Plaque ◽  
Plaque Vulnerability ◽  
Material Models ◽  
Vessel Material

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 562: Human Carotid Atherosclerosis Plaque Progression and Vessel Material Stiffness at Follow Up Had Positive Correlation: An in vivo Vessel Stiffness MRI Follow Up Study

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Qingyu Wang ◽  
Dalin Tang ◽  
Gador Canton ◽  
Jian Guo ◽  
Xiaoya Guo ◽  
...  
Keyword(s):  
Negative Correlation ◽  
Material Properties ◽  
Stretch Ratio ◽  
Patient Specific ◽  
Plaque Progression ◽  
Material Stiffness ◽  
Variation Rate ◽  
Vessel Material

It is hypothesized that artery stiffness may be associated with plaque progression. However, in vivo vessel material stiffness follow-up data is lacking in the literature. In vivo 3D multi-contrast and Cine magnetic resonance imaging (MRI) carotid plaque data were acquired from 8 patients with follow-up (18 months) with written informed consent obtained. Cine MRI and 3D thin-layer models were used to determine parameter values of the Mooney-Rivlin models for the 81slices from 16 plaques (2 scans/patient) using our established iterative procedures. Effective Young’s Modulus (YM) values for stretch ratio [1.0,1.3] were calculated for each slice for analysis. Stress-stretch ratio curves from Mooney-Rivlin models for the 16 plaques and 81 slices are given in Fig. 1. Average YM value of the 81 slices was 411kPa. Slice YM values 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 306% (139 kPa vs. 564 kPa). Average slice YM variation rate within a vessel for the 16 vessels was 134%. Average variation of YM values from baseline (T1) to follow up (T2) for all patients was 61.0%. The range of the variation of YM values was [-28.4%, 215%]. For progression study, YM increase (YMI=YM T2 -TM T1 ) showed negative correlation with plaque progression measured by wall thickness increase (WTI), (r= -0.6802, p=0.0634). YM T2 showed strong negative correlation with WTI (r= -0.7764, p=0.0235). Correlation between YM T1 and WTI was not significant (r= -0.4353, p= 0.2811). Conclusion In vivo carotid vessel material properties have large variations from patient to patient, along the vessel segment within a patient, and from baseline to follow up. Use of patient-specific, location specific and time-specific material properties could potentially improve the accuracy of model stress/strain calculations.

Computational Plaque Vulnerability Index for Atherosclerotic Carotid Plaque Assessment Based on In Vivo MR-Image

2008 ◽  
Author(s):  
Zhongzhao Teng ◽  
Xueying Huang ◽  
Chun Yuan ◽  
Gador Canton ◽  
Fei Liu ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Carotid Plaque ◽  
Vulnerability Index ◽  
Carotid Atherosclerotic Plaque ◽  
Plaque Vulnerability ◽  
Mr Image ◽  
Noninvasive Methods ◽  
Screening And Diagnosis

Carotid atherosclerotic plaque (CAP) may rupture without warning and cause acute cardiovascular syndromes such as stroke, which is the No.3 killer in USA and a leading cause of serious disabilities. Available screening and diagnosis techniques are insufficient to identify those victims before the event occurs. Noninvasive methods to identify new and emerging biomarkers to assess plaque vulnerability and predict possible rupture before the fatal event are urgently called for.

Determination of Human Carotid Atherosclerotic Plaque Material Properties Non-Invasively Using In Vivo Cine and 3D Magnetic Resonance Imaging and Image-Based Modeling Techniques

2011 ◽  
Author(s):  
Haofei Liu ◽  
Gador Canton ◽  
Chun Yuan ◽  
Marina Ferguson ◽  
Chun Yang ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Atherosclerotic Plaque ◽  
Material Properties ◽  
Computational Models ◽  
Plaque Rupture ◽  
Patient Specific ◽  
Material Strength ◽  
Modeling Techniques ◽  
Human Carotid

Atherosclerotic plaque rupture is believed to be associated with high critical stress exceeding plaque cap material strength. In vivo magnetic resonance image (MRI)-based computational models have been introduced to calculate critical plaque stress and assess plaque vulnerability [1–5]. However, accuracy of computational stress predictions is heavily dependent on the data used by the models. Patient-specific plaque material properties are desirable for accurate stress predictions but are not currently available. In this paper, non-invasive in vivo Cine and 3D multicontrast MRI data and modeling techniques were combined to obtain patient-specific plaque material properties to improve model prediction accuracies. A 2D human carotid plaque model was used to demonstrate impact of material stiffness on computational stress predictions.

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

2015 ◽  
Vol 137 (8) ◽  
Author(s):  
Longling Fan ◽  
Jing Yao ◽  
Chun Yang ◽  
Dalin Tang ◽  
Di Xu
Keyword(s):  
Wall Thickness ◽  
Material Properties ◽  
Strain Curve ◽  
Stress And Strain ◽  
Stress Strain ◽  
Material Stiffness ◽  
The Mean ◽  
Lv Volume ◽  
Parameter Values

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.

scholarly journals Can we obtain in vivo transmural mean hoop stress of the aortic wall without knowing patient-specific material properties and residual deformations?

2018 ◽  
Author(s):  
Minliang Liu ◽  
Liang Liang ◽  
Haofei Liu ◽  
Ming Zhang ◽  
Caitlin Martin ◽  
...  
Keyword(s):  
Material Properties ◽  
Hoop Stress ◽  
Aortic Wall ◽  
Patient Specific ◽  
Membrane Stress ◽  
Penalty Approach ◽  
Thin Walled ◽  
Specific Material ◽  
Residual Deformations

AbstractIt is well known that residual deformations/stresses alter the mechanical behavior of arteries, e.g. the pressure-diameter curves. In an effort to enable personalized analysis of the aortic wall stress, approaches have been developed to incorporate experimentally-derived residual deformations into in vivo loaded geometries in finite element simulations using thick-walled models. Solid elements are typically used to account for “bending-like” residual deformations. Yet, the difficulty in obtaining patient-specific residual deformations and material properties has become one of the biggest challenges of these thick-walled models. In thin-walled models, fortunately, static determinacy offers an appealing prospect that allows for the calculation of the thin-walled membrane stress without patient-specific material properties. The membrane stress can be computed using forward analysis by enforcing an extremely stiff material property as penalty treatment, which is referred to as the forward penalty approach. However, thin-walled membrane elements, which have zero bending stiffness, are incompatible with the residual deformations, and therefore, it is often stated as a limitation of thin-walled models. In this paper, by comparing the predicted stresses from thin-walled models and thick-walled models, we demonstrate that the transmural mean hoop stress is the same for the two models and can be readily obtained from in vivo clinical images without knowing the patient-specific material properties and residual deformations. Computation of patient-specific mean hoop stress can be greatly simplified by using membrane model and the forward penalty approach, which may be clinically valuable.

scholarly journals Validating Patient-Specific Finite Element Models of Direct Electrocortical Stimulation

2021 ◽  
Vol 15 ◽  
Author(s):  
Chantel M. Charlebois ◽  
David J. Caldwell ◽  
Sumientra M. Rampersad ◽  
Andrew P. Janson ◽  
Jeffrey G. Ojemann ◽  
...  
Keyword(s):  
Computational Models ◽  
Projection Methods ◽  
Patient Specific ◽  
Clinical Effects ◽  
Cortical Surface ◽  
Brain Shift ◽  
Model Errors ◽  
Computer Interfaces ◽  
Electrode Localization

Direct electrocortical stimulation (DECS) with electrocorticography electrodes is an established therapy for epilepsy and an emerging application for stroke rehabilitation and brain-computer interfaces. However, the electrophysiological mechanisms that result in a therapeutic effect remain unclear. Patient-specific computational models are promising tools to predict the voltages in the brain and better understand the neural and clinical response to DECS, but the accuracy of such models has not been directly validated in humans. A key hurdle to modeling DECS is accurately locating the electrodes on the cortical surface due to brain shift after electrode implantation. Despite the inherent uncertainty introduced by brain shift, the effects of electrode localization parameters have not been investigated. The goal of this study was to validate patient-specific computational models of DECS against in vivo voltage recordings obtained during DECS and quantify the effects of electrode localization parameters on simulated voltages on the cortical surface. We measured intracranial voltages in six epilepsy patients during DECS and investigated the following electrode localization parameters: principal axis, Hermes, and Dykstra electrode projection methods combined with 0, 1, and 2 mm of cerebral spinal fluid (CSF) below the electrodes. Greater CSF depth between the electrode and cortical surface increased model errors and decreased predicted voltage accuracy. The electrode localization parameters that best estimated the recorded voltages across six patients with varying amounts of brain shift were the Hermes projection method and a CSF depth of 0 mm (r = 0.92 and linear regression slope = 1.21). These results are the first to quantify the effects of electrode localization parameters with in vivo intracranial recordings and may serve as the basis for future studies investigating the neuronal and clinical effects of DECS for epilepsy, stroke, and other emerging closed-loop applications.

3D In Vivo IVUS-Based Anisotropic FSI Models With Cyclic Bending for Human Coronary Atherosclerotic Plaque Mechanical Analysis

2009 ◽  
Author(s):  
Dalin Tang ◽  
Chun Yang ◽  
Jie Zheng ◽  
Pamela K. Woodard ◽  
Kristen Billiar ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Computational Models ◽  
Material Model ◽  
3D Models ◽  
Mechanical Analysis ◽  
Intraplaque Hemorrhage ◽  
Plaque Vulnerability ◽  
Cardiovascular Research ◽  
Cyclic Bending

Assessing atherosclerotic plaque vulnerability based on limited in vivo patient data has been a major challenge in cardiovascular research and clinical practice. Considerable advances in medical imaging technology have been made in recent years to identify vulnerable atherosclerotic carotid plaques in vivo with information about plaque components including lipid-rich necrotic pools, calcification, intraplaque hemorrhage, loose matrix, thrombosis, and ulcers, subject to resolution limitations of current technology [1]. Image-based computational models have also been developed which combine mechanical analysis with image technology aiming for more accurate assessment of plaque vulnerability and better diagnostic and treatment decisions [2]. However, 3D models with fluid-structure interactions (FSI), cyclic bending and anisotropic properties based on in vivo IVUS images for human coronary atherosclerotic plaques are lacking in the current literature. In this paper, we introduce 3D FSI models based on in vivo IVUS images to perform mechanical analysis for human coronary plaques. Cyclic bending is included to represent deformation caused by cardiac motion. An anisotropic material model was used for the vessel so that the models would be more realistic for more accurate computational flow and stress/strain predictions.

scholarly journals Evaluation of a modified Cheatham-Platinum stent for the treatment of aortic coarctation by finite element modelling

2018 ◽  
Vol 7 ◽  
pp. 204800401877395 ◽  
Author(s):  
Barbara EU Burkhardt ◽  
Nicholas Byrne ◽  
Marí Nieves Velasco Forte ◽  
Francesco Iannaccone ◽  
Matthieu De Beule ◽  
...  
Keyword(s):  
Finite Element ◽  
Aortic Coarctation ◽  
Computational Models ◽  
Three Dimensional ◽  
Computational Modelling ◽  
Patient Specific ◽  
Stent Design ◽  
Initial Length ◽  
Element Analysis

Objectives Stent implantation for the treatment of aortic coarctation has become a standard approach for the management of older children and adults. Criteria for optimal stent design and construction remain undefined. This study used computational modelling to compare the performance of two generations of the Cheatham-Platinum stent (NuMED, Hopkinton, NY, USA) deployed in aortic coarctation using finite element analysis. Design Three-dimensional models of both stents, reverse engineered from microCT scans, were implanted in the aortic model of one representative patient. They were virtually expanded in the vessel with a 16 mm balloon and a pressure of 2 atm. Results The conventional stent foreshortened to 96.5% of its initial length, whereas the new stent to 99.2% of its initial length. Diameters in 15 slices across the conventional stent were 11.6–15 mm (median 14.2 mm) and slightly higher across the new stent: 10.7–15.3 mm (median 14.5 mm) (p= 0.021). Apposition to the vessel wall was similar: conventional stent 31.1% and new stent 28.6% of total stent area. Conclusions The new design Cheatham-Platinum stent showed similar deployment results compared to the conventional design. The new stent design showed slightly higher expansion, using the same delivery balloon. Patient-specific computational models can be used for virtual implantation of new aortic stents and promise to inform subsequent in vivo trials.

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