Noninvasive Vascular Modulography Method for Imaging the Local Elasticity of Atherosclerotic Plaques: Simulation and In Vitro Vessel Phantom Study

Simulating atherosclerotic plaque mechanics using polyvinyl alcohol (PVA) cryogel artery phantoms, ultrasound imaging and inverse finite element analysis

The clinical decision to establish if a patient with carotid disease should undergo surgical intervention is primarily based on the percent stenosis. Whilst this applies for high-grade stenosed vessels (>70%), it falls short for other cases. Due to the heterogeneity of plaque tissue, probing the mechanics of the tissue would likely provide further insights into why some plaques are more prone to rupture. Mechanical characterization of such tissue is nontrivial, however, due to the difficulties in collecting fresh, intact plaque tissue and using physiologically relevant mechanical testing of such material. The use of polyvinyl alcohol (PVA) cryogel is thus highly convenient because of its acoustic properties and tunable mechanical properties.Methods.The aim of this study is to demonstrate the potential of PVA phantoms to simulate atherosclerotic features. In addition, a testing and simulation framework is developed for full PVA vessel material characterization using ring tensile testing and inflation testing combined with non-invasive ultrasound imaging and computational modeling.Results.Strain stiffening behavior was observed in PVA through ring tensile tests, particularly at high (n= 6) freeze-thaw cycles (FTCs). Inflation testing of bi-layered phantoms featuring lipid pool inclusions demonstrated high strains at shoulder regions. The application of an inverse finite element framework successfully recovered boundaries and determined the shear moduli for the PVA wall to lie within the range 27-53 kPa.Conclusion.The imaging-modeling framework presented facilitates the use and characterization of arterial mimicking phantoms to further explore plaque rupture. It also shows translational potential for non-invasive mechanical characterization of atherosclerotic plaques to improve the identification of clinically relevant metrics of plaque vulnerability.

Development of an Artificial Soft Solid Gel Using Gelatin Material for High-Quality Ultrasound Diagnosis

For ultrasound diagnosis, a gel is applied to the skin. Ultrasound gel serves to block air exposure and match impedance between the skin and the probe, enhancing imaging efficiency. However, if use of the ultrasound gel exceeds a certain period of time, it may dry out and be exposed to air, causing impedance mismatch and reducing imaging resolution. In such cases, the use of a soft, solid gel proves advantageous, as it can be employed for an extended period without succumbing to the drying phenomenon and can be reused after disinfection. Its soft consistency ensures excellent skin adhesion. Our soft solid gel demonstrated approximately 1.2 times better performance than water, silicone, and traditional ultrasound gels. When comparing the dimensions of grayscale, dead zone, vertical, and horizontal regions, the measurements for the traditional ultrasound gel were 93.79 mm, 45.32 mm, 103.13 mm, 83.86 mm, and 83.86 mm, respectively. In contrast, the proposed soft solid gel exhibited dimensions of 105.64 mm, 34.48 mm, 141.1 mm, and 102.8 mm.

Characterizing atherosclerotic tissues: in silico analysis of mechanical properties using intravascular ultrasound and inverse finite element methods

Atherosclerosis is a prevalent cause of acute coronary syndromes that consists of lipid deposition inside the artery wall, creating an atherosclerotic plaque. Early detection may prevent the risk of plaque rupture. Nowadays, intravascular ultrasound (IVUS) is the most common medical imaging technology for atherosclerotic plaque detection. It provides an image of the section of the coronary wall and, in combination with new techniques, can estimate the displacement or strain fields. From these magnitudes and by inverse analysis, it is possible to estimate the mechanical properties of the plaque tissues and their stress distribution. In this paper, we presented a methodology based on two approaches to characterize the mechanical properties of atherosclerotic tissues. The first approach estimated the linear behavior under particular pressure. In contrast, the second technique yielded the non-linear hyperelastic material curves for the fibrotic tissues across the complete physiological pressure range. To establish and validate this method, the theoretical framework employed in silico models to simulate atherosclerotic plaques and their IVUS data. We analyzed different materials and real geometries with finite element (FE) models. After the segmentation of the fibrotic, calcification, and lipid tissues, an inverse FE analysis was performed to estimate the mechanical response of the tissues. Both approaches employed an optimization process to obtain the mechanical properties by minimizing the error between the radial strains obtained from the simulated IVUS and those achieved in each iteration. The second methodology was successfully applied to five distinct real geometries and four different fibrotic tissues, getting median R 2 of 0.97 and 0.92, respectively, when comparing the real and estimated behavior curves. In addition, the last technique reduced errors in the estimated plaque strain field by more than 20% during the optimization process, compared to the former approach. The findings enabled the estimation of the stress field over the hyperelastic plaque tissues, providing valuable insights into its risk of rupture.

Matrix stiffness regulates macrophage polarization in atherosclerosis

Atherosclerosis is a chronic inflammatory disease and the pathological basis of many fatal cardiovascular diseases. Macrophages, the main inflammatory cells in atherosclerotic plaque, have a paradox role in disease progression. In response to different microenvironments, macrophages mainly have two polarized directions: pro-inflammatory macrophages and anti-inflammatory macrophages. More and more evidence shows that macrophage is mechanosensitive and matrix stiffness regulate macrophage phenotypes in atherosclerosis. However, the molecular mechanism of matrix stiffness regulating macrophage polarization still lacks in-depth research, which hinders the development of new anti-atherosclerotic therapies. In this review, we discuss the important role of matrix stiffness in regulating macrophage polarization through mechanical signal transduction (Hippo, Piezo, cytoskeleton, and integrin) and epigenetic mechanisms (miRNA, DNA methylation, and histone). We hope to provide a new perspective for atherosclerosis therapy by targeting matrix stiffness and macrophage polarization.

An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging

The increasing prevalence of finite element (FE) simulations in the study of atherosclerosis has spawned numerous inverse FE methods for the mechanical characterization of diseased tissue in vivo. Current approaches are however limited to either homogenized or simplified material representations. This paper presents a novel method to account for tissue heterogeneity and material nonlinearity in the recovery of constitutive behavior using imaging data acquired at differing intravascular pressures by incorporating interfaces between various intra-plaque tissue types into the objective function definition. Method verification was performed in silico by recovering assigned material parameters from a pair of vessel geometries: one derived from coronary optical coherence tomography (OCT); one generated from in silico-based simulation. In repeated tests, the method consistently recovered 4 linear elastic (0.1 ± 0.1% error) and 8 nonlinear hyperelastic (3.3 ± 3.0% error) material parameters. Method robustness was also highlighted in noise sensitivity analysis, where linear elastic parameters were recovered with average errors of 1.3 ± 1.6% and 8.3 ± 10.5%, at 5% and 20% noise, respectively. Reproducibility was substantiated through the recovery of 9 material parameters in two more models, with mean errors of 3.0 ± 4.7%. The results highlight the potential of this new approach, enabling high-fidelity material parameter recovery for use in complex cardiovascular computational studies.

Parameterized Strain Estimation for Vascular Ultrasound Elastography With Sparse Representation

Ultrasound vascular strain imaging has shown its potential to interrogate the motion of the vessel wall induced by the cardiac pulsation for predicting plaque instability. In this study, a sparse model strain estimator (SMSE) is proposed to reconstruct a dense strain field at a high resolution, with no spatial derivatives, and a high computation efficiency. This sparse model utilizes the highly-compacted property of discrete cosine transform (DCT) coefficients, thereby allowing to parameterize displacement and strain fields with truncated DCT coefficients. The derivation of affine strain components (axial and lateral strains and shears) was reformulated into solving truncated DCT coefficients and then reconstructed with them. Moreover, an analytical solution was derived to reduce estimation time. With simulations, the SMSE reduced estimation errors by up to 50% compared with the state-of-the-art window-based Lagrangian speckle model estimator (LSME). The SMSE was also proven to be more robust than the LSME against global and local noise. For in vitro and in vivo tests, residual strains assessing cumulated errors with the SMSE were 2 to 3 times lower than with the LSME. Regarding computation efficiency, the processing time of the SMSE was reduced by 4 to 25 times compared with the LSME, according to simulations, in vitro and in vivo results. Finally, phantom studies demonstrated the enhanced spatial resolution of the proposed SMSE algorithm against LSME.

Bidirectional Ultrasound Elastographic Imaging Framework for Non-invasive Assessment of the Non-linear Behavior of a Physiologically Pressurized Artery

Studies of non-destructive bidirectional ultrasound assessment of non-linear mechanical behavior of the artery are scarce in the literature. We hereby propose derivation of a strain-shear modulus relationship as a new graphical diagnostic index using an ultrasound elastographic imaging framework, which encompasses our in-house bidirectional vascular guided wave imaging (VGWI) and ultrasound strain imaging (USI). This framework is used to assess arterial non-linearity in two orthogonal (i.e., longitudinal and circumferential) directions in the absence of non-invasive pressure measurement. Bidirectional VGWI estimates longitudinal (μ_L) and transverse (μ_T) shear moduli, whereas USI estimates radial strain (ɛ_r). Vessel-mimicking phantoms (with and without longitudinal pre-stretch) and in vitro porcine aortas under static and/or dynamic physiologic intraluminal pressure loads were examined. ɛ_r was found to be a suitable alternative to intraluminal pressure for representation of cyclic loading on the artery wall. Results revealed that μ_T values of all samples examined increased non-linearly with ε_r magnitude and more drastically than μ_L, whereas μ_L values of only the pre-stretched phantoms and aortas increased with ɛ_r magnitude. As a new graphical representation of arterial non-linearity and function, strain-shear modulus loops derived by the proposed framework over two consecutive dynamic loading cycles differentiated sample pre-conditions and corroborated direction-dependent non-linear mechanical behaviors of the aorta with high estimation repeatability.

Intraluminal Ultrasonic Palpation Imaging Technique Revisited for Anisotropic Characterization of Healthy and Atherosclerotic Coronary Arteries: A Feasibility Study

Accurate mechanical characterization of coronary atherosclerotic lesions remains essential for the in vivo detection of vulnerable plaques. Using intravascular ultrasound strain measurements and based on the mechanical response of a circular and concentric vascular model, E. I. Céspedes, C. L. de Korte and A. F. van der Steen developed an elasticity-palpography technique in 2000 to estimate the apparent stress-strain modulus palpogram of the thick subendoluminal arterial wall layer. More recently, this approach was improved by our group to consider the real anatomic shape of the vulnerable plaque. Even though these two studies highlighted original and promising approaches for improving the detection of vulnerable plaques, they did not overcome a main limitation related to the anisotropic mechanical behavior of the vascular tissue. The present study was therefore designed to extend these previous approaches by considering the orthotropic mechanical properties of the arterial wall and lesion constituents. Based on the continuum mechanics theory prescribing the strain field, an elastic anisotropy index was defined. This new anisotropic elasticity-palpography technique was successfully applied to characterize ten coronary plaque and one healthy vessel geometries of patients imaged in vivo with intravascular ultrasound. The results revealed that the anisotropy index-palpograms were estimated with a good accuracy (with a mean relative error of 26.8 ± 48.8%) compared with ground true solutions.

Two-dimensional affine model-based estimators for principal strain vascular ultrasound elastography with compound plane wave and transverse oscillation beamforming

Polar strain (radial and circumferential) estimations can suffer from artifacts because the center of a nonsymmetrical carotid atherosclerotic artery, defining the coordinate system in cross-sectional view, can be misregistered. Principal strains are able to remove coordinate dependency to visualize vascular strain components (i.e., axial and lateral strains and shears). This paper presents two affine model-based estimators, the affine phase-based estimator (APBE) developed in the framework of transverse oscillation (TO) beamforming, and the Lagrangian speckle model estimator (LSME). These estimators solve simultaneously the translation (axial and lateral displacements) and deformation (axial and lateral strains and shears) components that were then used to compute principal strains. To improve performance, the implemented APBE was also tested by introducing a time-ensemble estimation approach. Both APBE and LSME were tested with and without the plane strain incompressibility assumption. These algorithms were evaluated on coherent plane wave compounded (CPWC) images considering TO. LSME without TO but implemented with the time-ensemble and incompressibility constraint (Porée et al., 2015) served as benchmark comparisons. The APBE provided better principal strain estimations with the time-ensemble and incompressibility constraint, for both simulations and in vitro experiments. With a few exceptions, TO did not improve principal strain estimates for the LSME. With simulations, the smallest errors compared with ground true measures were obtained with the LSME considering time-ensemble and the incompressibility constraint. This latter estimator also provided the highest elastogram signal-to-noise ratios (SNRs) for in vitro experiments on a homogeneous vascular phantom without any inclusion, for applied strains varying from 0.07% to 4.5%. It also allowed the highest contrast-to-noise ratios (CNRs) for a heterogeneous vascular phantom with a soft inclusion, at applied strains from 0.07% to 3.6%. In summary, the LSME outperformed the implemented APBE, and the incompressibility constraint improved performances of both estimators.