BUSCADOR RECOLECTA

Background and objective: in this work, the analysis of the importance of hemodynamic updates on a mechanobiological model of atheroma plaque formation is proposed. Methods: for that, we use an idealized and axisymmetric model of carotid artery. In addition, the behavior of endothelial cells depending on hemodynamical changes is analyzed too. A total of three computational simulations are carried out and their results are compared: an uncoupled model and two models that consider the opposite behavior of endothelial cells caused by hemodynamic changes. The model considers transient blood flow using the Navier-Stokes equation. Plasma flow across the endothelium is determined with Darcy's law and the Kedem-Katchalsky equations, considering the three-pore model, which is also employed for the flow of substances across the endothelium. The behavior of the considered substances in the arterial wall is modeled with convection¿diffusion¿reaction equations, and the arterial wall is modeled as a hyperelastic Yeoh's material. Results: significant variations are noted in both the morphology and stenosis ratio of the plaques when comparing the uncoupled model to the two models incorporating updates for geometry and hemodynamic stimuli. Besides, the phenomenon of double-stenosis is naturally reproduced in the models that consider both geometric and hemodynamical changes due to plaque growth, whereas it cannot be predicted in the uncoupled model. Conclusions: the findings indicate that integrating the plaque growth model with geometric and hemodynamic settings is essential in determining the ultimate shape and dimensions of the carotid plaque., Support was obtained from the Spanish Ministry of Science and Technology through the research projects PID2019-107517RB-I00 and PID2022-140219OB-I00 and financial support to P. Hernández-López from the grant BES-2017-080239, and the regional Government of Aragón support for the funding of the research project T24-20R. Myriam Cilla is supported by Grant Ramón Cajal grant 171562 funded by MICIU/AEI/ 10.13039/501100011033 and the European Social Fund Plus (FSE+) . M. Malvé is supported by grant PID2021-125731OB-C31 from the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033/ and FEDER ("Away to build Europe").; The authors thank the research support from the CIBER initiative, whose actions are financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund .

Background: Atherosclerotic plaque detection is a clinical and technological problem that has been approached by different studies. Nowadays, intravascular ultrasound (IVUS) is the standard used to capture images of the coronary walls and to detect plaques. However, IVUS images are difficult to segment, which complicates obtaining geometric measurements of the plaque. Objective: IVUS, in combination with new techniques, allows estimation of strains in the coronary section. In this study, we have proposed the use of estimated strains to develop a methodology for plaque segmentation. Methods: The process is based on the representation of strain gradients and the combination of the Watershed and Gradient Vector Flow algorithms. Since it is a theoretical framework, the methodology was tested with idealized and real IVUS geometries. Results: We achieved measurements of the lipid area and fibrous cap thickness, which are essential clinical information, with promising results. The success of the segmentation depends on the plaque geometry and the strain gradient variable (SGV) that was selected. However, there are some SGV combinations that yield good results regardless of plaque geometry such as ▽εvMises+▽εrθ, ▽εyy+▽εrr or ▽εmin+▽εTresca. These combinations of SGVs achieve good segmentations, with an accuracy between 97.10% and 94.39% in the best pairs. Conclusions: The new methodology provides fast segmentation from different strain variables, without an optimization step.

Proper characterisation of biological tissue is key to understanding the effect of the biomechanical environment in the physiology and pathology of the cardiovascular system. Aortic dissection in particular is a prevalent and sometimes fatal disease that still lacks a complete comprehension of its progression. Its development and outcome, however, depend on the location in the vessel. Dissection properties of arteries are frequently studied via delamination tests, such as the T-peel test and the mixed-mode peel test. So far, a study that performs both tests throughout different locations of the aorta, as well as dissecting several interfaces, is missing. This makes it difficult to extract conclusions in terms of vessel heterogeneity, as a standardised experimental procedure cannot be assured for different studies in literature. Therefore, both dissection tests have been here performed on healthy porcine aortas, dissecting three interfaces of the vessels, i.e., the intima-media, the media-adventitia and the media within itself, considering different locations of the aorta, the ascending thoracic aorta (ATA), the descending thoracic aorta and the infrarenal abdominal aorta (IAA). Significant differences were found for both, layers and location. In particular, dissection forces in the ATA were the highest and the separation of the intima-media interface required significantly the lowest force. Moreover, dissection in the longitudinal direction of the vessel generally required more force than in the circumferential one. These results emphasise the need to characterise aortic tissue considering the specific location and dissected layer of the vessel.

In this work, we analyse the influence of the parameters of a mathematical model, previously proposed by the authors, for reproducing atheroma plaque in arteries. The model uses Navier–Stokes equations to calculate the blood flow along the lumen in a transient mode. It also uses Darcy’s law, Kedem–Katchalsky equations, and the three-pore model to simulate plasma and substance flows across the endothelium. The behaviours of all substances in the arterial wall are modelled with convection–diffusion–reaction equations, and finally, plaque growth is calculated. We consider a 2D geometry of a carotid artery, but the model can be extrapolated to other geometries or arteries, such as the coronaries or the aorta. A mono-variant sensitivity analysis of the model parameters was performed, with values of ±25% and ±10%, with respect to the values of the previous model. The results were analysed with respect to the volume in the plaque of foam cells (FC), synthetic smooth muscle cells (SSMC), and collagen fibre. It was observed that the volume in the plaque of the different substances (FC, SSMC, and collagen) has a strong influence on the results, so it could be used to analyse the vulnerability of plaque. The stenosis ratio of the plaque was also analysed, showing a strong influence on the results as well. Parameters that influence all the results considered when ranged ±10% are the rate of LDL degradation and the diffusion coefficients of LDL and monocytes in the arterial wall. Furthermore, it was observed that the change in the volume of foam cells in the plaque has a greater influence on the stenosis ratio than the change of synthetic smooth muscle cells or collagen fibre.

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 (Ecore) and the plaque (Eplaque) 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 Ecore and Eplaque. Finally, the ANN was applied to estimate the mechanical properties of 10,000 realistic plaques, resulting in relative errors lower than 3%.

To test the capability of the multilayer model, we used previously published layer-specific experimental data relating to the axial pre-stretch, the opening angle, the fiber distribution obtained by polarized light microscopy measurements, and the uniaxial and biaxial response of the porcine descending and abdominal aorta. We fitted the mechanical behavior of each arterial layer using Gasser, Holzapfel and Ogden strain energy function using the dispersion parameter ¿ as phenomenological parameter obtained during the fitting procedure or computed from the experimental fiber distribution. A multilayer finite element model of the whole aorta with the dimensions of the circumferential and longitudinal strips were then built using layer-specific material parameters previously fitted. This model was used to capture the whole aorta response under uniaxial and biaxial stress states and to reproduce the response of the whole aorta to internal pressure. Our results show that a model based on a multilayer structure without residual stresses is unable to render the uniaxial and biaxial mechanical response of the aorta (R2=0.6954 and R2=0.8582 for descending thoracic aorta (DTA) and infrarenal abdominal aorta (IAA), respectively). Only an appropriate multilayer model that includes layer-specific residual stresses can reproduce the response of the whole aorta (R2=0.9787 and R2=0.9636 for DTA and IAA respectively). In addition, a multilayer model without residual stresses produces the same stress distribution as a monolayer model without residual stresses where the maximal value of circumferential and longitudinal stresses appears at the inner radius of the intima. Finally, if layer-specific residual stresses are not available, there is less error the stress distribution using a monolayer model with residual stresses that a multilayer model without residual stresses.

We analyze the residual stresses and mechanical properties of layer-dissected infrarenal abdominal aorta (IAA). We measured the axial pre-stretch and opening angle and performed uniaxial tests to study and compare the mechanical behavior of both intact and layer-dissected porcine IAA samples under physiological loads. Finally, some of the most popular anisotropic hyperelastic constitutive models (GOH and microfiber models) were proposed to estimate the mechanical properties of the abdominal aorta by least-square fitting of the recorded in-vitro uniaxial test results. The results show that the residual stresses are layer dependent. In all cases, we found that the OA in the media layer is lower than in the whole artery, the intima and the adventitia. For the axial pre-stretch, we found that the adventitia and the media were slightly stretched in the environment of the intact arterial strip, whereas the intima appears to be compressed. Regarding the mechanical properties, the media seems to be the softest layer over the whole deformation domain showing high anisotropy, while the intima and adventitia exhibit considerable stiffness and a lower anisotropy response. Finally, all the hyperelastic anisotropic models considered in this study provided a reasonable approximation of the experimental data. The GOH model showed the best fitting.

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 R2 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.

Myocardium passive mechanical response has been a major topic of study for decades due to its major impact on cardiac physiology. Here, we propose a novel modeling methodology that integrates both in vivo and in vitro data to estimate the tissue mechanical parameters for a particular orthotropic hyperelastic model as those proposed by Costa and by Holzapfel & Ogden, although it can be easily extended to any other. In vitro biaxial and triaxial shear extension tests were conducted in biopsied samples and in vivo pressure-volume recordings were obtained. Left ventricle (LV) geometry was reconstructed using magnetic resonance imaging (MRI) and pressure gradients during ventricular inflation were recorded with the Catheter Conductance Method (CCM). Finally, a Finite Element (FE) in vivo LV model was implemented to get the material model parameters using an inverse approach that uses a minimization process combining both the in vivo and in vitro available data. Our results demonstrate that the parameters obtained solely from in vitro testing (IVT), or from in vivo passive inflation (IVV) do not provide satisfactory fits for both responses simultaneously ([Fórmula] and [Fórmula]). On the contrary, the proposed combined in vitro & in vivo optimization process (MIN) converges to a solution that effectively captures both the in vivo and in vitro behaviors [Fórmula]). Thus, this novel combined approach offers a comprehensive framework for accurately characterizing myocardial mechanical behavior. The obtained parameters can serve as a basis for further cardiac simulations and contribute to a better understanding of cardiac mechanics and function.

Background and Objective: In this work, the analysis of the importance of hemodynamic updates on a mechanobiological model of atheroma plaque formation is proposed. Methods: For that, we use an idealized and axisymmetric model of carotid artery. In addition, the behavior of endothelial cells depending on hemodynamical changes is analyzed too. A total of three computational simulations are carried out and their results are compared: an uncoupled model and two models that consider the opposite behavior of endothelial cells caused by hemodynamic changes. The model considers transient blood flow using the Navier–Stokes equation. Plasma flow across the endothelium is determined with Darcy’s law and the Kedem–Katchalsky equations, considering the three-pore model, which is also employed for the flow of substances across the endothelium. The behavior of the considered substances in the arterial wall is modeled with convection–diffusion–reaction equations, and the arterial wall is modeled as a hyperelastic Yeoh’s material. Results:Significant variations are noted in both the morphology and stenosis ratio of the plaques when comparing the uncoupled model to the two models incorporating updates for geometry and hemodynamic stimuli. Besides, the phenomenon of double-stenosis is naturally reproduced in the models that consider both geometric and hemodynamical changes due to plaque growth, whereas it cannot be predicted in the uncoupled model. Conclusions: The findings indicate that integrating the plaque growth model with geometric and hemodynamic settings is essential in determining the ultimate shape and dimensions of the carotid plaque.

This study explored the impact of hypertension on atheroma plaque formation through a mechanobiological model. The model incorporates blood flow via the Navier–Stokes equation. Plasma flow through the endothelium is determined by Darcy’s law and the Kedem–Katchalsky equations, which consider the three-pore model utilized for substance flow across the endothelium. The behaviour of these substances within the arterial wall is described by convection–diffusion–reaction equations, while the arterial wall itself is modelled as a hyperelastic material using Yeoh’s model. To accurately evaluate hypertension’s influence, adjustments were made to incorporate wall compression-induced wall compaction by radial compression. This compaction impacts three key variables of the transport phenomena: diffusion, porosity, and permeability. Based on the obtained findings, we can conclude that hypertension significantly augments plaque growth, leading to an over 400% increase in plaque thickness. This effect persists regardless of whether wall mechanics are considered. Tortuosity, arterial wall permeability, and porosity have minimal impact on atheroma plaque growth under normal arterial pressure. However, the atheroma plaque growth changes dramatically in hypertensive cases. In such scenarios, the collective influence of all factors—tortuosity, permeability, and porosity—results in nearly a 20% increase in plaque growth. This emphasizes the importance of considering wall compression due to hypertension in patient studies, where elevated blood pressure and high cholesterol levels commonly coexist.

The most common treatment for obstructive coronary artery disease (CAD) is the implantation of a permanent drug-eluting stent (DES). Not only has this permanency been associated with delayed healing of the artery, but it also poses challenges when treating subsequent re-narrowing due to in-stent restenosis (ISR). Drug-coated balloons (DCBs) provide a potential solution to each of these issues. While their use has been primarily limited to treating ISR, in recent years, DCBs have emerged as an attractive potential alternative to DESs for the treatment of certain de novo lesions. However, there remain a number of concerns related to the safety and efficacy of these devices. Firstly, unlike DESs, DCBs necessitate a very short drug delivery window, favouring a higher drug loading. Secondly, while the majority of coronary DCBs in Europe are coated with paclitaxel, the potential mortality signal raised with paclitaxel DCBs in peripheral interventions has shifted efforts towards the development of limus-eluting balloons. The purpose of this paper is to provide a computational model that allows drug delivery from DCBs and DESs to be investigated and compared. We present a comprehensive computational framework that employs a 2D-axisymmetric geometry, incorporates two nonlinear phases of drug binding (specific and non-specific) and includes the influence of diffusion and advection, within a multilayer arterial wall. We utilise this framework to (i) simulate drug delivery from different types of balloon platform; (ii) explore the influence of DCB application time; (iii) elucidate the importance on release kinetics of elevated pressure during DCB application; (iv) compare DCB delivery of two different drugs (sirolimus and paclitaxel) and; (v) compare simulations of DESs versus DCBs. Key measures of comparison are related to safety (drug content in tissue, DC) and efficacy (specific binding site saturation, %SBSS) markers. Our results highlight the pros and cons of each device in terms of DC and %SBSS levels achieved and, moreover, indicate the potential for designing a DCB that gives rise to sufficiently similar safety and efficacy indicators as current commercial DESs.