Eduardo Soudah

CFD Modelling of Abdominal Aortic Aneurysm on Hemodynamic Loads Using a Realistic Geometry with CT

The objective of this study is to find a correlation between the abdominal aortic aneurysm (AAA) geometric parameters, wall stress shear (WSS), abdominal flow patterns, intraluminal thrombus (ILT), and AAA arterial wall rupture using computational fluid dynamics (CFD). Real AAA 3D models were created by three-dimensional (3D) reconstruction of in vivo acquired computed tomography (CT) images from 5 patients. Based on 3D AAA models, high quality volume meshes were created using an optimal tetrahedral aspect ratio for the whole domain. In order to quantify the WSS and the recirculation inside the AAA, a 3D CFD using finite elements analysis was used. The CFD computation was performed assuming that the arterial wall is rigid and the blood is considered a homogeneous Newtonian fluid with a density of 1050 kg/m3 and a kinematic viscosity of 4 × 10−3 Pa·s. Parallelization procedures were used in order to increase the performance of the CFD calculations. A relation between AAA geometric parameters (asymmetry index (β), saccular index (γ), deformation diameter ratio (χ), and tortuosity index (ε)) and hemodynamic loads was observed, and it could be used as a potential predictor of AAA arterial wall rupture and potential ILT formation.

Validation of numerical flow simulations against in vitro phantom measurements in different type B aortic dissection scenarios

An aortic dissection (AD) is a serious condition defined by the splitting of the arterial wall, thus generating a secondary lumen [the false lumen (FL)]. Its management, treatment and follow-up are clinical challenges due to the progressive aortic dilatation and potentially severe complications during follow-up. It is well known that the direction and rate of dilatation of the artery wall depend on haemodynamic parameters such as the local velocity profiles, intra-luminal pressures and resultant wall stresses. These factors act on the FL and true lumen, triggering remodelling and clinical worsening. In this study, we aimed to validate a computational fluid dynamic (CFD) tool for the haemodynamic characterisation of chronic (type B) ADs. We validated the numerical results, for several dissection geometries, with experimental data obtained from a previous in vitro study performed on idealised dissected physical models. We found a good correlation between CFD simulations and experimental measurements as long as the tear size was large enough so that the effect of the wall compliance was negligible.

A multi-method approach towards understanding the pathophysiology of aortic dissections: the complementary role of in-silico, in-vitro and in-vivo information

Management and follow-up of chronic aortic dissections continues to be a clinical challenge due to progressive aortic dilatation. To predict dilatation, guidelines suggest follow-up of the aortic diameter. However, dilatation is triggered by haemodynamic parameters (pressure and wall shear stresses (WSS)), and geometry of false (FL) and true lumen (TL). We aimed at a better understanding of TL and FL haemodynamics by performing in-silico (CFD) and invitro studies on an idealized dissected aorta and compared this to a typical patient. We observed an increase in diastolic pressure and wall stress in the FL and the presence of diastolic retrograde flow. The inflow jet increased WSS at the proximal FL while a large variability in WSS was induced distally, all being risk factors for wall weakening. In-silico, in-vitro and in-vivo findings were very similar and complementary, showing that their combination can help in a more integrated and extensive assessment of aortic dissections, improving understanding of the haemodynamic conditions and related clinical evolution.

Influence of tear configuration on false and true lumen haemodynamics in type B aortic dissection

The management and follow-up of chronic type B aortic dissections continues being a clinical challenge. Patients with chronic type B dissection have high mid/long term mortality mainly due to progressive aortic dilatation and subsequent rupture.

MECHANICAL STRESS IN ABDOMINAL AORTIC ANEURYSMS USING ARTIFICIAL NEURAL NETWORKS

Combination of numerical modeling and artificial intelligence (AI) in bioengineering processes are a promising pathway for the further development of bioengineering sciences. The objective of this work is to use Artificial Neural Networks (ANN) to reduce the long computational times needed in the analysis of shear stress in the Abdominal Aortic Aneurysm (AAA) by finite element methods (FEM). For that purpose two different neural networks are created. The first neural network (Mesh Neural Network, MNN) creates the aneurysm geometry in terms of four geometrical factors (asymmetry factor, aneurism diameter, aneurism thickness, aneurism length). The second neural network (Tension Neural Network, TNN) combines the results of the first neural network with the arterial pressure (new factor) to obtain the maximum stress distribution (output variable) in the aneurysm wall. The use of FEM for the analysis and design of bioengineering processes often requires high computational costs, but if this technique is combined with artificial intelligence, such as neural networks, the simulation time is significantly reduced. The shear stress obtained by the artificial neural models developed in this work achieved 95% of accuracy respect to the wall stress obtained by the FEM. On the other hand, the computational time is significantly reduced compared to the FEM.

Medical-GiD: From Medical Images to Simulations, 4D MRI Flow Analysis

Medical imaging techniques, such as MRI and CT scanning, are valuable tools for getting a lot of information non-invasively and it is useful for reconstructing the geometry of complex objects about the patients. Medical-GiD is a medical image platform that incorporates a module to read directly the blood velocity profile from the MR scan, in particular for deformable registration of 4D MRI images, Electrocardiography (ECG)-synchronized and respiration controlled 3D magnetic resonance (MR) velocity mapping (flow-sensitive 4D MRI), 3D morphologic and three-directional blood flow data. Furthermore, Medical-GiD is focus in the medical image processing in the biomechanical research field to generating meshes from the medical images, to apply in Computational Fluid Dynamics (CFD) or structural mechanics (stress analysis). To date, these techniques have largely been applied to compute meshes for numerical simulations, but with Medical-GiD, we will have the integration between the real data and numerical simulations.

Advanced Medical Expert Support Tool (A-MEST): EHR-Based Integration of Multiple Risk Assessment Solutions for Congestive Heart Failure Patients

More and more the continuum of care is replacing the traditional way of treating the subjects of care putting people in the centre of the healthcare process. Currently clinicians start treatment after a problem occurs due to the low adoption of Clinical Decision Support Systems (CDSS) integrated with standardised Electronic Health Record (EHR) systems; The volume to value revolution in the healthcare (from stakeholder-centric to patient-centric) will allow doctors to follow the evolution of the individual before a medical episode happens, treating the patient based on statistical trends to forecast the future. The CDSS techniques applied on tele-monitoring tools permit the doctors to predict forthcoming events, improve the diagnosis and avoid continuous visits to the hospital, therefore saving costs. Advanced Medical Expert Support Tool is a step towards achieving the patient-centric approach by incorporating the health information into the EHR using European standards (ISO/EN 13606) to provide semantic interoperability by means of the dual model approach (reference model and archetypes). Three different CDSS modules have been implemented and contextualised publications are provided to the cardiologist to facilitate their daily work. A person-centric Graphical User Interface (GUI) facilitates the visualization of the health status of the patients providing meaningful information to the cardiologists. The use of archetypes allows scalability, transparency and efficiency to the hospital environment.

MODELING HUMAN TISSUES: AN EFFICIENT INTEGRATED METHODOLOGY

Geometric models of human body organs are obtained from imaging techniques like computed tomography (CT) and magnetic resonance image (MRI) that oallow an accurate visualization of the inner body, thus providing relevant information about their its structure and pathologies. Next, these models are used to generate surface and volumetric meshes, which can be used further for visualization, measurement, biomechanical simulation, rapid prototyping and prosthesis design. However, going from geometric models to numerical models is not an easy task, being necessary to apply image-processing techniques to solve the complexity of human tissues and to get more simplified geometric models, thus reducing the complexity of the subsequent numerical analysis. In this work, an integrated and efficient methodology to obtain models of soft tissues like gray and white matter of brain and hard tissues like jaw and spine bones is proposed. The methodology is based on image-processing algorithms chosen according to some characteristics of the tissue: type, intensity profiles and boundaries quality. First, low-quality images are improved by using enhancement algorithms to reduce image noise and to increase structures contrast. Then, hybrid segmentation for tissue identification is applied through a multi-stage approach. Finally, the obtained models are resampled and exported in formats readable by computer aided design (CAD) tools. In CAD environments, this data is used to generate discrete models using finite element methed (FEM) or other numerical methods like the boundary element method (BEM). Results have shown that the proposed methodology is useful and versatile to obtain accurate geometric models that can be used in several clinical cases to obtain relevant quantitative and qualitative information.

Numerical Methods and Applications in Biomechanical Modeling 2014.

Numerical methods and applications in biomechanical modeling have continued to play increasingly important roles in biomedical research and applications. This special issue, following the very successful one in 2013, provides a snapshot of the emerging biomedical applications and research. The main focus of this special issue was on the interface between numerical methods and biomedical applications especially for cardiovascular dynamics and biomechanics problem in the human body. The goal of this special issue was to bring together experts in related fields of computational biomedical engineering like multiscale flow modeling (3D, 1D, and 0D models), blood flow propagation, boundary conditions, fluid-solid coupling, inverse problems in biomechanics, high-performance computing of multiphysics discretization schemes, cardiovascular biomechanics, and porous media. Then, the details of these papers are summarized as follows. The work of M. Klous et al. attempts to compare ankle and knee joint loading at the steering leg between carved ski and snowboard turns. The authors showed higher forces along the longitudinal axis in skiing and similar forces for skiing and snowboarding in anterior-posterior and mediolateral direction. This study can help the clinician to improve understanding of how forces are distributed in the ankle and knee joint when these sports are done. X. Liu et al. present the deformation and haptic feedback of soft tissue in virtual surgery based on a liver model by using a force feedback device. This paper introduces a kind of mesh-free method for deformation simulation of soft tissue and force computation based on viscoelastic mechanical model and smoothed particle hydrodynamics (SPH). The results reveal that SPH methodology is suitable for simulating soft tissue deformation and force feedback calculation, and SPH based on dynamic local interaction area has a higher computational efficiency significantly compared with the usual SPH. A. Belwadi and K. H. Yang show an interesting paper about how the occupant-seating position, bumper profile height, and the principal direction of force of impact play a crucial role in the generation of strain and pressure in the aorta and a potential injury mechanism responsible for traumatic rupture of the aorta in automobile crashes. In their study, 16 design of computer experiments were carried out with varying levels of principal direction of force, impact velocity, impact height, and impact position of the bullet vehicle combined with occupant-seating positions in the case vehicle to determine the effects of these factors on aortic injury. Simulation results showed that, in simulated near side left lateral crashes, peak average maximum principal strain mainly took place in the isthmus of the aorta. Their design of computer experiments using finite element vehicle models has identified the key factors responsible for aortic injury. N. Mijailovic et al. combine within biomechanical model different sensor measurements to determine the knee cartilage deformation ratio and the knee cartilage stress distribution to predict when it is necessary to perform surgery on a patient. The model includes the impact of ground reaction forces, contact force between femur and tibia, patient body weight, ligaments, and muscle forces. Despite introduction of a new approach and presentation of some preliminary findings, their proposed method shows great potential for preoperative and postoperative surgical planning and treatment of patients with knee injuries. The paper by M. Jahangiri et al. compares different turbulent models over a stenosed artery considering an elastic wall. The results were compared with those of the laminar flow assumption and the rigid artery wall and show the effects of turbulent blood flow over the velocity profiles. F. Schellenberg et al. present a review of existing computational techniques to determine muscle forces in the lower limbs during strength exercises in vivo and discuss their potential for uptake into sports training and rehabilitation. The review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercises in vivo are expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve 20 training guidelines. R. Rockenfeller et al. compare two models of mammalian striated muscle activation dynamics proposed by Hatze and Zajac and perform a sensitivity analysis for investigating the influence of model parameters on the solution of the mathematical equations. The authors also used a global sensitivity analysis approach to factor in finite ranges of parameter values. The authors demonstrate that the findings of global sensitivity analysis must be treated with caution because the whole dynamics of a system is condensed to a single average function per whole parameter range. The work of S. Khalafvand et al. studies the blood flow characteristics in the normal left ventricle. The authors show the vortices produced (generation and growth) and their correlation with flow acceleration and deceleration during the mitral valve opening and closing. This work can help the cardiologist to understand how the vortices are produced in the heart movement, thus contributing to understanding of pathogenesis of cardiac disease. The objective of the work by Þ. Petursson et al. describes a novel preliminary methodology for patient evaluation before total hip replacement surgery as a first step towards creating a patient-specific, presurgical application for determining the optimal prosthesis procedure. Ten patients were studied using finite element analysis and bone mineral density to estimate the status of hip before surgery; after that a fracture risk index is defined and compared with the patients age, sex, and average proximal bone mineral density. Findings of this study showed a high degree of variability between patients grouped according to implant procedure, with age and gender being the poor indicators for determining total hip replacement procedure. Their results could be used as a basis to develop a clinical database for correlating bone mineral density and fracture risk index to total hip replacement patient outcomes. G. Saborit and A. Casinos present a mathematical model to predict the optimum gradient for a minimum energetic cost. The model focuses on the variation in mechanical energy during gradient walking. The authors show that kinetic energy plays a marginal role in low speed gradient walking. Consequently, the optimal negative gradient depends on the individual step length. In this special issue, we have provided examples of recent progress in computational and mathematical methods in biomedicine, for the benefit of students, researchers, healthcare professionals, and teachers.

Preliminary Correlations for Characterizing the Morphology of Abdominal Aortic Aneurysms as Predictor of Rupture

The morphology of abdominal aortic aneurysms (AAA) has been recognized as a factor that may predispose their rupture. The time variation of the AAA morphology induces hemodynamic changes in morphological behavior that, in turn, alters the distribution of hemodynamic stress on the arterial wall. This behavior can influence the phenomenon of rupture. In order to evaluate the relationship between the main geometric parameters characterizing the AAA and the hemodynamic stresses, 6 AAA models were reconstructed and characterized. The models were characterized using thirteen geometrical factors based on the lumen center line: eight 1D indices, three 3D indices, and two 0D indices. The temporal and spatial distributions of hemodynamic stresses were computed using computational fluid dynamics. The results showed that the hemodynamic stresses are modified by the time variations of the AAA morphology, and therefore, the hemodynamic stresses, in combination with other parameters, could be a criterion for improved rupture risk prediction. Statistical correlations between hemodynamic stresses and geometric indices have confirmed the influence by the AAA morphometry on the prediction of the rupture risks, although higher reliability of these correlations is required.