An experimental and computational investigation of the material behaviour of discrete homogenous iliofemoral and carotid atherosclerotic plaque constituents

Local Characterization of Collagen Architecture and Mechanical Failure Properties of Fibrous Plaque Tissue of Atherosclerotic Human Carotid Arteries

Atherosclerotic plaque rupture in carotid arteries is a major cause of cerebrovascular events. Plaque rupture is the mechanical failure of the heterogeneous fibrous plaque tissue. Local characterization of the tissue's failure properties and the collagen architecture are of great importance to have insights in plaque rupture for clinical event prevention. Previous studies were limited to average rupture properties and global structural characterization, and did not provide the necessary local information. In this study, we assessed the local collagen architecture and failure properties of fibrous plaque tissue, by analyzing 30 tissue strips from 18 carotid plaques. Our study framework entailed second harmonic generation imaging for local collagen orientation and dispersion, and uniaxial tensile testing and digital image correlation for local tissue mechanics. The results showed that 87% of the imaged locations had collagen orientation close to the circumferential direction (0°) of the artery, and substantial dispersion locally. All regions combined, median [Q1:Q3] of the predominant angle measurements was -2° [-16°:16°]. The stretch ratio measurements clearly demonstrated a nonuniform stretch ratio distribution in the tissue under uniaxial loading. The rupture initiation regions had significantly higher stretch ratios (1.26 [1.15-1.40]) than the tissue average stretch ratio (1.11 [1.10-1.16]). No significant difference in collagen direction and dispersion was identified between the rupture regions and the rest of the tissue. The presented study forms an initial step towards gaining better insights into the characterization of local structural and mechanical fingerprints of fibrous plaque tissue in order to aid improved assessment of plaque rupture risk. STATEMENT OF SIGNIFICANCE: Plaque rupture risk assessment, critical to prevent cardiovascular events, requires knowledge on local failure properties and structure of collagenous plaque tissue. Our current knowledge is unfortunately limited to tissue's overall ultimate failure properties with scarce information on collagen architecture. In this study, local failure properties and collagen architecture of fibrous plaque tissue were obtained. We found predominant circumferential alignment of collagen fibers with substantial local dispersion. The tissue showed nonuniform stretch distribution under uniaxial tensile loading, with high stretches at rupture spots. This study highlights the significance of local mechanical and structural assessment for better insights into plaque rupture and the potential use of local stretches as risk marker for plaque rupture for patient-specific clinical applications.

Fluid structure interaction analysis to stratify the behavior of different atheromatous carotid plaques

BACKGROUND

In asymptomatic carotid stenosis (ACS), different plaque types, i.e. lipidic (LP), fibrous (FP), and calcific (CP), could have different hemodynamic and structural behaviors.

METHODS

Different carotid plaques, reconstructed from medical imaging of ACS >70%, were analyzed by computing fluid structure interaction (FSI), modeling the spatial distribution of wall shear stresses (WSS), plaque displacements (D), von Mises stresses (VMS), and absorbed elastic energy (AEE) together with their maximum-in-space values at the systole (WSS<inf>syst</inf>, D<inf>syst</inf>, VMS<inf>syst</inf> and AEE<inf>syst</inf>).

RESULTS

WSS resulted significantly higher in CP, whereas D and VMS showed the highest values for LP. Regarding AEE<inf>syst</inf> stored by the plaques, LP absorbed in average 2320 J/m³, FP 408 J/m³ (470%) and CP 99 J/m³ (2240%), (P<0.01, P<0.01, and P<0.01, respectively).

CONCLUSIONS

Depending upon their nature, plaques store different deformations and inner distributions of forces, thus potentially influencing their vulnerability.

Coronary artery properties in atherosclerosis: A deep learning predictive model

In this work an Artificial Neural Network (ANN) was developed to help in the diagnosis of plaque vulnerability by predicting the Young modulus of the core (E _core ) and the plaque (E _plaque ) of atherosclerotic coronary arteries. A representative in silico database was constructed to train the ANN using Finite Element simulations covering the ranges of mechanical properties present in the bibliography. A statistical analysis to pre-process the data and determine the most influential variables was performed to select the inputs of the ANN. The ANN was based on Multilayer Perceptron architecture and trained using the developed database, resulting in a Mean Squared Error (MSE) in the loss function under 10^-7, enabling accurate predictions on the test dataset for E _core and E _plaque . Finally, the ANN was applied to estimate the mechanical properties of 10,000 realistic plaques, resulting in relative errors lower than 3%.

Constitutive models and failure properties of fibrous tissues of carotid artery atheroma based on their uniaxial testing

To obtain an experimental background for the description of mechanical properties of fibrous tissues of carotid atheroma, a cohort of 141 specimens harvested from 44 patients during endarterectomies, were tested. Uniaxial stress-strain curves and ultimate stress and strain at rupture were recorded. With this cohort, the impact of the direction of load, presence of calcifications, specimen location, patient's age and sex were investigated. A significant impact of sex was revealed for the stress-strain curves and ultimate strains. The response was significantly stiffer for females than for males but, in contrast to ultimate strain, the strength was not significantly different. The differences in strength between calcified and non-calcified atheromas have reached statistical significance in the female group. At most of the analysed stress levels, the loading direction was found significant for the male cohort which was also confirmed by large differences in ultimate strains. The representative uniaxial stress-strain curves (given by median values of strains at chosen stress levels) were fitted with an isotropic hyperelastic model for different groups specified by the investigated factors while the observed differences between circumferential and longitudinal direction were captured by an anisotropic hyperelastic model. The obtained results should be valid also for the tissue of the fibrous cap, the rupture of which is to be predicted in clinics using computational modelling because it may induce arterial thrombosis and consequently a brain stroke.

Multicomponent material property characterization of atherosclerotic human carotid arteries through a Bayesian Optimization based inverse finite element approach

OBJECTIVE

Plaque rupture in atherosclerotic carotid arteries is a main cause of ischemic stroke and it is correlated with high plaque stresses. Hence, analyzing stress patterns is essential for plaque specific rupture risk assessment. However, the critical information of the multicomponent material properties of atherosclerotic carotid arteries is still lacking greatly. This work aims to characterize component-wise material properties of atherosclerotic human carotid arteries under (almost) physiological loading conditions.

METHODS

An inverse finite element modeling (iFEM) framework was developed to characterize fibrous intima and vessel wall material properties of 13 cross sections from five carotids. The novel pipeline comprised ex-vivo inflation testing, pre-clinical high frequency ultrasound for deriving plaque deformations, pre-clinical high-magnetic field magnetic resonance imaging, finite element modeling, and a sample efficient machine learning based Bayesian Optimization.

RESULTS

The nonlinear Yeoh constants for the fibrous intima and wall layers were successfully obtained. The optimization scheme of the iFEM reached the global minimum with a mean error of 3.8% in 133 iterations on average. The uniqueness of the results were confirmed with the inverted Gaussian Process (GP) model trained during the iFEM protocol.

CONCLUSION

The developed iFEM approach combined with the inverted GP model successfully predicted component-wise material properties of intact atherosclerotic human carotids ex-vivo under physiological-like loading conditions.

SIGNIFICANCE

We developed a novel iFEM framework for the nonlinear, component-wise material characterization of atherosclerotic arteries and utilized it to obtain human atherosclerotic carotid material properties. The developed iFEM framework has great potential to be advanced for patient-specific in-vivo application.

A Computational Fluid-Structure Interaction Study for Carotids With Different Atherosclerotic Plaques

Atherosclerosis is a systemic disease that leads to accumulation of deposits, known as atherosclerotic plaques, within the walls of the carotids. In particular, three types of plaque can be distinguished: soft, fibrous, and calcific. Most of the computational studies who investigated the interplay between the plaque and the blood flow on patient-specific geometries used nonstandard medical images to directly delineate and segment the plaque and its components. However, these techniques are not so widely available in the clinical practice. In this context, the aim of our work was twofold: (i) to propose a new geometric tool that allowed to reconstruct a plausible plaque in the carotids from standard images and (ii) to perform three-dimensional (3D) fluid-structure interaction (FSI) simulations where we compared some fluid-dynamic and structural quantities among 15 patients characterized by different typologies of plaque. Our results highlighted that both the morphology and the mechanical properties of different plaque components play a crucial role in determining the vulnerability of the plaque.