Estimation of wall shear stress using 4D flow cardiovascular MRI and computational fluid dynamics

Electronic version of an article published as Journal of mechanics in medicine and biology, 0, 1750046 (2016), 16 pages. DOI:10.1142/S0219519417500464 © World Scientific Publishing CompanyIn the last few years, wall shear stress (WSS) has arisen as a new diagnostic indicator in patients with arterial disease. There is a substantial evidence that the WSS plays a significant role, together with hemodynamic indicators, in initiation and progression of the vascular diseases. Estimation of WSS values, therefore, may be of clinical significance and the methods employed for its measurement are crucial for clinical community. Recently, four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) has been widely used in a number of applications for visualization and quantification of blood flow, and although the sensitivity to blood flow measurement has increased, it is not yet able to provide an accurate three-dimensional (3D) WSS distribution. The aim of this work is to evaluate the aortic blood flow features and the associated WSS by the combination of 4D flow cardiovascular magnetic resonance (4D CMR) and computational fluid dynamics technique. In particular, in this work, we used the 4D CMR to obtain the spatial domain and the boundary conditions needed to estimate the WSS within the entire thoracic aorta using computational fluid dynamics. Similar WSS distributions were found for cases simulated. A sensitivity analysis was done to check the accuracy of the method. 4D CMR begins to be a reliable tool to estimate the WSS within the entire thoracic aorta using computational fluid dynamics. The combination of both techniques may provide the ideal tool to help tackle these and other problems related to wall shear estimation.Peer ReviewedPostprint (author's final draft

Fluid–structure interaction simulations outperform computational fluid dynamics in the description of thoracic aorta haemodynamics and in the differentiation of progressive dilation in Marfan syndrome patients

Abnormal fluid dynamics at the ascending aorta may be at the origin of aortic aneurysms. This study was aimed at comparing the performance of computational fluid dynamics (CFD) and fluid–structure interaction (FSI) simulations against four-dimensional (4D) flow magnetic resonance imaging (MRI) data; and to assess the capacity of advanced fluid dynamics markers to stratify aneurysm progression risk. Eight Marfan syndrome (MFS) patients, four with stable and four with dilating aneurysms of the proximal aorta, and four healthy controls were studied. FSI and CFD simulations were performed with MRI-derived geometry, inlet velocity field and Young's modulus. Flow displacement, jet angle and maximum velocity evaluated from FSI and CFD simulations were compared to 4D flow MRI data. A dimensionless parameter, the shear stress ratio (SSR), was evaluated from FSI and CFD simulations and assessed as potential correlate of aneurysm progression. FSI simulations successfully matched MRI data regarding descending to ascending aorta flow rates (R2 = 0.92) and pulse wave velocity (R2 = 0.99). Compared to CFD, FSI simulations showed significantly lower percentage errors in ascending and descending aorta in flow displacement (−46% ascending, −41% descending), jet angle (−28% ascending, −50% descending) and maximum velocity (−37% ascending, −34% descending) with respect to 4D flow MRI. FSI- but not CFD-derived SSR differentiated between stable and dilating MFS patients. Fluid dynamic simulations of the thoracic aorta require fluid–solid interaction to properly reproduce complex haemodynamics. FSI- but not CFD-derived SSR could help stratifying MFS patients.This study was funded by Ministerio de Economía y Competitividad (grant no. RTC-2016-5152-1), Fundació la Marató de TV3 (grant no. 20151330), FP7 People: Marie-Curie Actions (grant no. 267128), Instituto de Salud Carlos III (grant nos PI14/0106 and PI17/00381) and ‘la Caixa’ Foundation. M.V. was funded by CompBioMed2, grant agreement ID: 823712, funded under: H2020-EU.1.4.1.3; and SILICOFCM, grant agreement ID: 777204, funded under: H2020-EU.3.1.5.Peer ReviewedPostprint (published version

A Systematic Review and Discussion of the Clinical Potential

Funding Information: Funding by Portuguese Foundation for Science and Technology (FCT-MCTES) under the following projects: PTDC/EMD-EMD/1230/2021—Fluid-structure interaction for functional assessment of ascending aortic aneurysms: a biomechanical-based approach toward clinical practice ; UNIDEMI UIDB/00667/2020; A. Mourato PhD grant UI/BD/151212/2021; R. Valente PhD grant 2022.12223.BD. Publisher Copyright: © 2022 by the authors.Aortic aneurysm is a cardiovascular disease related to the alteration of the aortic tissue. It is an important cause of death in developed countries, especially for older patients. The diagnosis and treatment of such pathology is performed according to guidelines, which suggest surgical or interventional (stenting) procedures for aneurysms with a maximum diameter above a critical threshold. Although conservative, this clinical approach is also not able to predict the risk of acute complications for every patient. In the last decade, there has been growing interest towards the development of advanced in silico aortic models, which may assist in clinical diagnosis, surgical procedure planning or the design and validation of medical devices. This paper details a comprehensive review of computational modelling and simulations of blood vessel interaction in aortic aneurysms and dissection, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). In particular, the following questions are addressed: “What mathematical models were applied to simulate the biomechanical behaviour of healthy and diseased aortas?” and “Why are these models not clinically implemented?”. Contemporary evidence proves that computational models are able to provide clinicians with additional, otherwise unavailable in vivo data and potentially identify patients who may benefit from earlier treatment. Notwithstanding the above, these tools are still not widely implemented, primarily due to low accuracy, an extensive reporting time and lack of numerical validation.publishersversionpublishe

Including Aortic Valve Morphology in Computational Fluid Dynamics Simulations: Initial Findings and Application to Aortic Coarctation

Computational fluid dynamics (CFD) simulations quantifying thoracic aortic flow patterns have not included disturbances from the aortic valve (AoV). 80% of patients with aortic coarctation (CoA) have a bicuspid aortic valve (BAV) which may cause adverse flow patterns contributing to morbidity. Our objectives were to develop a method to account for the AoV in CFD simulations, and quantify its impact on local hemodynamics. The method developed facilitates segmentation of the AoV, spatiotemporal interpolation of segments, and anatomic positioning of segments at the CFD model inlet. The AoV was included in CFD model examples of a normal (tricuspid AoV) and a post-surgical CoA patient (BAV). Velocity, turbulent kinetic energy (TKE), time-averaged wall shear stress (TAWSS), and oscillatory shear index (OSI) results were compared to equivalent simulations using a plug inlet profile. The plug inlet greatly underestimated TKE for both examples. TAWSS differences extended throughout the thoracic aorta for the CoA BAV, but were limited to the arch for the normal example. OSI differences existed mainly in the ascending aorta for both cases. The impact of AoV can now be included with CFD simulations to identify regions of deleterious hemodynamics thereby advancing simulations of the thoracic aorta one step closer to reality

Deciphering ascending thoracic aortic aneurysm hemodynamics in relation to biomechanical properties

The degeneration of the arterial wall at the basis of the ascending thoracic aortic aneurysm (ATAA) is a complex multifactorial process, which may lead to clinical complications and, ultimately, death. Individual genetic, biological or hemodynamic factors are inadequate to explain the heterogeneity of ATAA development/progression mechanisms, thus stimulating the analysis of their complex interplay. Here the disruption of the hemodynamic environment in the ATAA is investigated integrating patient-specific computational hemodynamics, CT-based in vivo estimation of local aortic stiffness and advanced fluid mechanics methods of analysis. The final aims are (1) deciphering the ATAA spatiotemporal hemodynamic complexity and its link to near-wall topological features, and (2) identifying the existing links between arterial wall degeneration and hemodynamic insult. Technically, two methodologies are applied to computational hemodynamics data, the wall shear stress (WSS) topological skeleton analysis, and the Complex Networks theory. The same analysis was extended to the healthy aorta. As main findings of the study, we report that: (1) different spatiotemporal heterogeneity characterizes the ATAA and healthy hemodynamics, that markedly reflect on their WSS topological skeleton features; (2) a link (stronger than canonical WSS-based descriptors) emerges between the variation of contraction/expansion action exerted by WSS on the endothelium along the cardiac cycle, and ATAA wall stiffness. The findings of the study suggest the use of advanced methods for a deeper understanding of the hemodynamics disruption in ATAA, and candidate WSS topological skeleton features as promising indicators of local wall degeneration

Computational analysis of fluid dynamics at the asceding thoracic aorta in Marfan syndrome patients

Els aneurismes aòrtics són una dilatació progressiva i irreversible de la paret aòrtica, que pot causar la ruptura o dissecció dels vasos, el que resulta en una pèrdua catastròfica de sang que condueix a la mort. El tractament farmacològic inicial se centra en aturar el creixement per prevenir la ruptura, però requereix una reparació invasiva oberta o una reparació endovascular en pacients en risc. El maneig del pacient i l'estratificació de risc després del diagnòstic són crítics, especialment en l'aorta ascendent, ja que actualment no hi ha tractaments endovasculars disponibles. Segons les directrius actuals, el diàmetre aòrtic màxim és l'únic criteri geomètric o fluidodinàmic específic del pacient acceptat com a predictor clínic del risc de ruptura. No obstant això, l'anormal fluidodinàmica en l'aorta ascendent s'ha reportat àmpliament com una possible font d'aneurismes aòrtics i la seva comprensió podria millorar l'avaluació del risc del pacient. En aquest estudi, es va avaluar la fluidodinàmica en aortes de controls sans i pacients amb síndrome de Marfan. Per fer això, hem comparat el rendiment de les simulacions de dinàmica de fluids computacional i d'interacció fluid-estructura utilitzant imatges clíniques com a condicions específiques del pacient. També hem dissenyat un sistema in vitro que podria exposar les cèl·lules endotelials aòrtiques humanes a un entorn fluidodinàmic que imita el de les simulacions aòrtiques. L'estudi ha revelat, en pacients Marfan, que considerà l'elasticitat de la paret en les simulacions és essencial per obtenir amb precisió els valors fluidodinàmics que tenen el potencial d'estratificar aquests pacients. En aquest sentit, les simulacions d'interacció fluid-estructura han superat la fluidodinàmica computacional clàssica a un cost computacional moderat. Com a resultat d'aquest estudi, un paràmetre adimensional, la relació d'esforç tallant, ha determinat el seu potencial com a marcador de progressió d'aneurisma en pacients amb Marfan.Los aneurismas aórticos son una dilatación progresiva e irreversible de la pared aórtica, que puede causar la ruptura o disección de los vasos, lo que resulta en una pérdida catastrófica de sangre que conduce a la muerte. El tratamiento farmacológico inicial se centra en detener el crecimiento para prevenir la ruptura, pero se requiere una reparación invasiva abierta o una reparación endovascular en pacientes en riesgo. El manejo del paciente y la estratificación del riesgo después del diagnóstico son críticos, especialmente en la aorta ascendente, ya que actualmente no hay tratamientos endovasculares disponibles. Según las directrices actuales, el diámetro aórtico máximo es el único criterio geométrico o fluidodinámico específico del paciente aceptado como predictor clínico del riesgo de ruptura. Sin embargo, la anormal fluidodinámica en la aorta ascendente se ha reportado ampliamente como una posible fuente de aneurismas aórticos y su comprensión podría mejorar la evaluación del riesgo del paciente. En este estudio, se evaluó la fluidodinámica en aortas de controles sanos y pacientes con síndrome de Marfan. Para hacer esto, hemos comparado el rendimiento de las simulaciones de dinámica de fluidos computacional y de interacción fluido-estructura utilizando imágenes clínicas como condiciones específicas del paciente. También hemos diseñado un sistema in vitro que podría exponer las células endoteliales aórticas humanas a un entorno fluidodinámico que imita el de las simulaciones aórticas. El estudio ha revelado, en pacientes Marfan, que considerar la elasticidad de la pared en las simulaciones es esencial para obtener con precisión los valores dinámicos de los fluidos que tienen el potencial de estratificar a estos pacientes. En este sentido, las simulaciones de interacción fluido-estructura han superado la fluidodinámica computacional clásica a un costo computacional moderado. Como resultado de este estudio, un parámetro adimensional, la relación de esfuerzo cortante, ha demostrado su potencial como marcador de progresión de aneurisma en pacientes con Marfan.Aortic aneurysms are a progressive and irreversible dilation of the aortic wall, which can lead to vessel rupture or dissection, resulting in catastrophic blood loss leading to death. Initial pharmacological treatment is focused on growth arrest to prevent rupture, but invasive open repair or endovascular repair are required in patients at risk. Patient management and risk stratification after diagnosis are critical, especially in the ascending aorta since no endovascular treatments are currently available. According to current guidelines, maximum aortic diameter is the only patient-specific geometrical or fluidodynamic criterion accepted as clinical rupture risk predictor. However, abnormal fluid dynamics at the ascending aorta have been widely reported as potential origin of aortic aneurysms and their understanding could improve the risk assessment of patients. In this study, the fluid dynamics of aortae from healthy controls and patients with Marfan syndrome have been evaluated. To do so, we have compared the performance of computational fluid dynamics and fluid-structure interaction simulations using clinical imaging as patient-specific inputs. We have also designed an in vitro system that could expose human aortic endothelial cells to a fluidodynamic environment that mimics that of aortic simulations. The study has revealed, in Marfan patients, that considering the wall elasticity in simulations is critical to derive precisely fluid dynamic values that hold the potential to stratify such patients. In this sense, fluid-structure interaction simulations have outperformed classic computational fluid dynamics at a moderate computational cost. As a result of this study, a dimensionless parameter, the shear stress ratio, has shown its potential as marker of aneurysm progression in Marfan patients

Patient-specific computational fluid dynamics-assessment of aortic hemodynamics in a spectrum of aortic valve pathologies.

OBJECTIVES: The complexity of aortic disease is not fully exposed by aortic dimensions alone, and morbidity or mortality can occur before intervention thresholds are met. Patient-specific computational fluid dynamics (CFD) were used to assess the effect of different aortic valve morphologies on velocity profiles, flow patterns, helicity, wall shear stress (WSS), and oscillatory shear index (OSI) in the thoracic aorta. METHODS: A total of 45 subjects were divided into 5 groups: volunteers, aortic regurgitation-tricuspid aortic valve (AR-TAV), aortic stenosis-tricuspid aortic valve (AS-TAV), aortic stenosis-bicuspid aortic valve right-left cusp fusion (BAV[RL]), and aortic stenosis-right-non cusp fusion (AS-BAV[RN]). Subjects underwent magnetic resonance angiography, with phase-contrast magnetic resonance imaging at the sino-tubular junction to define patient-specific inflow velocity profiles. Hemodynamic recordings were used alongside magnetic resonance imaging angiographic data to run patient-specific CFD. RESULTS: The BAV groups had larger mid-ascending aorta diameters (P < .05). Ascending aorta flow was more eccentric in BAV (flow asymmetry = 78.9% ± 6.5% for AS-BAV(RN), compared with 4.7% ± 2.1% for volunteers, P < .05). Helicity was greater in AS-BAV(RL) (P < .05). Mean WSS was elevated in AS groups, greatest in AS-BAV(RN) (37.1 ± 4.0 dyn/cm2, compared with 9.8 ± 5.4 for volunteers, P < .05). The greater curvature of the ascending aorta experienced highest WSS and lowest OSI in AS patients, most significant in AS-BAV(RN) (P < .05). CONCLUSIONS: BAV displays eccentric flow with high helicity. The presence of AS, particularly in BAV-RN, led to greater WSS and lower OSI in the greater curvature of the ascending aorta. Patient-specific CFD provides noninvasive functional assessment of the thoracic aorta, and may enable development of a personalized approach to diagnosis and management of aortic disease beyond traditional guidelines

Computational fluid dynamics indicators to improve cardiovascular pathologies

In recent years, the study of computational hemodynamics within anatomically complex vascular regions has generated great interest among clinicians. The progress in computational fluid dynamics, image processing and high-performance computing haveallowed us to identify the candidate vascular regions for the appearance of cardiovascular diseases and to predict how this disease may evolve. Medicine currently uses a paradigm called diagnosis. In this thesis we attempt to introduce into medicine the predictive paradigm that has been used in engineering for many years. The objective of this thesis is therefore to develop predictive models based on diagnostic indicators for cardiovascular pathologies. We try to predict the evolution of aortic abdominal aneurysm, aortic coarctation and coronary artery disease in a personalized way for each patient. To understand how the cardiovascular pathology will evolve and when it will become a health risk, it is necessary to develop new technologies by merging medical imaging and computational science. We propose diagnostic indicators that can improve the diagnosis and predict the evolution of the disease more efficiently than the methods used until now. In particular, a new methodology for computing diagnostic indicators based on computational hemodynamics and medical imaging is proposed. We have worked with data of anonymous patients to create real predictive technology that will allow us to continue advancing in personalized medicine and generate more sustainable health systems. However, our final aim is to achieve an impact at a clinical level. Several groups have tried to create predictive models for cardiovascular pathologies, but they have not yet begun to use them in clinical practice. Our objective is to go further and obtain predictive variables to be used practically in the clinical field. It is to be hoped that in the future extremely precise databases of all of our anatomy and physiology will be available to doctors. These data can be used for predictive models to improve diagnosis or to improve therapies or personalized treatments.En els últims anys, l'estudi de l'hemodinàmica computacional en regions vasculars anatòmicament complexes ha generat un gran interès entre els clínics. El progrés obtingut en la dinàmica de fluids computacional, en el processament d'imatges i en la computació d'alt rendiment ha permès identificar regions vasculars on poden aparèixer malalties cardiovasculars, així com predir-ne l'evolució. Actualment, la medicina utilitza un paradigma anomenat diagnòstic. En aquesta tesi s'intenta introduir en la medicina el paradigma predictiu utilitzat des de fa molts anys en l'enginyeria. Per tant, aquesta tesi té com a objectiu desenvolupar models predictius basats en indicadors de diagnòstic de patologies cardiovasculars. Tractem de predir l'evolució de l'aneurisma d'aorta abdominal, la coartació aòrtica i la malaltia coronària de forma personalitzada per a cada pacient. Per entendre com la patologia cardiovascular evolucionarà i quan suposarà un risc per a la salut, cal desenvolupar noves tecnologies mitjançant la combinació de les imatges mèdiques i la ciència computacional. Proposem uns indicadors que poden millorar el diagnòstic i predir l'evolució de la malaltia de manera més eficient que els mètodes utilitzats fins ara. En particular, es proposa una nova metodologia per al càlcul dels indicadors de diagnòstic basada en l'hemodinàmica computacional i les imatges mèdiques. Hem treballat amb dades de pacients anònims per crear una tecnologia predictiva real que ens permetrà seguir avançant en la medicina personalitzada i generar sistemes de salut més sostenibles. Però el nostre objectiu final és aconseguir un impacte en l¿àmbit clínic. Diversos grups han tractat de crear models predictius per a les patologies cardiovasculars, però encara no han començat a utilitzar-les en la pràctica clínica. El nostre objectiu és anar més enllà i obtenir variables predictives que es puguin utilitzar de forma pràctica en el camp clínic. Es pot preveure que en el futur tots els metges disposaran de bases de dades molt precises de tota la nostra anatomia i fisiologia. Aquestes dades es poden utilitzar en els models predictius per millorar el diagnòstic o per millorar teràpies o tractaments personalitzats.Postprint (published version

Aortic Coarctation: Recent Developments in Experimental and Computational Methods to Assess Treatments for this Simple Condition

Coarctation of the aorta (CoA) is often considered a relatively simple disease, but long-term outcomes suggest otherwise as life expectancies are decades less than in the average population and substantial morbidity often exists. What follows is an expanded version of collective work conducted by the authors\u27 and numerous collaborators that was presented at the 1st International Conference on Computational Simulation in Congenital Heart Disease pertaining to recent advances for CoA. The work begins by focusing on what is known about blood flow, pressure and indices of wall shear stress (WSS) in patients with normal vascular anatomy from both clinical imaging and the use of computational fluid dynamics (CFD) techniques. Hemodynamic alterations observed in CFD studies from untreated CoA patients and those undergoing surgical or interventional treatment are subsequently discussed. The impact of surgical approach, stent design and valve morphology are also presented for these patient populations. Finally, recent work from a representative experimental animal model of CoA that may offer insight into proposed mechanisms of long-term morbidity in CoA is presented