Maurizio Bordone

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.

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.

Data analisis of 4D phase contrast MRI in healthy and non-healthy patients

Time-resolved, 3-dimensional phase-contrast magnetic resonance imaging (3D+t PCMRI) is employed to obtain complete spatial and temporal coverage of the vessels blood combined with spatially registered 3-directional pulsatile blood flow velocities[1][2]. Recent studies have reported that Wall Shear Stress (WSS) quantification from PCMRI are able to use the WSS as biomarkers for different aortas pathologies [3]. Figure [1] shows the pathline visualization of blood flow during one cardiac cycle in the heart of a healthy patient at peak early LV filling, diastasis, peak atrial contraction, and peak systole.

Supervised learning modelization and segmentation of cardiac scar in delayed enhanced MRI

Delayed Enhancement Magnetic Resonance Imaging can be used to non-invasively differentiate viable from non-viable myocardium within the Left Ventricle in patients suffering from myocardial diseases. Automated segmentation of scarified tissue can be used to accurately quantify the percentage of myocardium affected. This paper presents a method for cardiac scar detection and segmentation based on supervised learning and level set segmentation. First, a model of the appearance of scar tissue is trained using a Support Vector Machines classifier on image-derived descriptors. Based on the areas detected by the classifier, an accurate segmentation is performed using a segmentation method based on level sets.

A 1d lumped-parameter/3d CFD approach for pressure drop in the aortic coarctation

Aortic Coarctation is a congenital constriction of the aorta that increases blood pressure above the constriction and hinders the flow below it. Based on a 3D surface mesh of a moderate thoracic coarctation, a high quality volume mesh is created using an optimal tetrahedral aspect ratio for whole domain. In order to quantify the severity of this constriction, a coupled 1D lumped-parameter/3D CFD approach is used to calculate the pressure drop through the coarctation. The CFD computation is performed assuming that the arterial wall is rigid and the blood is considered a homogeneous Newtonian fluid with density r = 0.001 gr/mm3 and a dynamic viscosity m = 0.004 gr/mm/sec in laminar flow. The boundary conditions of the 3D model (inlet and outlet conditions) have been calculated using a 1D model. Parallelization procedures will be used in order to increase the performance of the CFD calculations.

HEMODYNAMIC FEATURES ASSOCIATED WITH ABDOMINAL AORTIC ANEURYSM (AAA) GEOMETRY

Recent findings have shown that maximum diameter of abdominal aortic aneurysm (AAA) and its growth rate are not entirely reliable indicators of rupture potential. The AAA geometrical shape and size may be related to the rupture risk which is a clinical manifestation of the balance between the forces generated by blood flow within the AAA and its strength. This study aims at assessing the hemodynamic features associated with the geometry of AAAs.