Illustrative Flow Visualization of 4D PC-MRI Blood Flow and CFD Data

Das zentrale Thema dieser Dissertation ist die Anwendung illustrativer Methoden auf zwei bisher ungelöste Probleme der Strömungsvisualisierung. Das Ziel der Strömungsvisualisierung ist die Bereitstellung von Software, die Experten beim Auswerten ihrer Strömungsdaten und damit beim Erkenntnisgewinn unterstützt. Bei der illustrativen Visualisierung handelt es sich um einen Zweig der Visualisierung, der sich an der künstlerischen Arbeit von Illustratoren orientiert. Letztere sind darauf spezialisiert komplizierte Zusammenhänge verständlich und ansprechend zu vermitteln. Die angewendeten Techniken werden in der illustrativen Visualisierung auf reale Daten übertragen, um die Effektivität der Darstellung zu erhöhen. Das erste Problem, das im Rahmen dieser Dissertation bearbeitet wurde, ist die eingeschränkte Verständlichkeit von komplexen Stromflächen. Selbstverdeckungen oder Aufrollungen behindern die Form- und Strömungswahrnehmung und machen diese Flächen gerade in interessanten Strömungssituationen wenig nützlich. Auf Basis von handgezeichneten Strömungsdarstellungen haben wir ein Flächenrendering entwickelt, das Silhouetten, nicht-photorealistische Beleuchtung und illustrative Stromlinien verwendet. Interaktive Flächenschnitte erlauben die Exploration der Flächen und der Strömungen, die sie repräsentieren. Angewendet auf verschiedene Stromflächen ließ sich zeigen, dass die Methoden die Verständlichkeit erhöhen, v.a. in Bereichen komplexer Strömung mit Aufwicklungen oder Singularitäten. Das zweite Problem ist die Strömungsanalyse des Blutes aus 4D PC-MRI-Daten. An diese relativ neue Datenmodalität werden hohe Erwartungen für die Erforschung und Behandlung kardiovaskulärer Krankheiten geknüpft, da sie erstmals ein dreidimensionales, zeitlich aufgelöstes Abbild der Hämodynamik liefert. Bisher werden 4D PC-MRI-Daten meist mit Werkzeugen der klassischen Strömungsvisualisierung verarbeitet. Diese werden den besonderen Ansprüchen der medizinischen Anwender jedoch nicht gerecht, die in kurzer Zeit eine übersichtliche Darstellung der relevanten Strömungsaspekte erhalten möchten. Wir haben ein Werkzeug zur visuellen Analyse der Blutströmung entwickelt, welches eine einfache Detektion von markanten Strömungsmustern erlaubt, wie z.B. Jets, Wirbel oder Bereiche mit hoher Blutverweildauer. Die Grundidee ist hierbei aus vorberechneten Integrallinien mit Hilfe speziell definierter Linienprädikate die relevanten, d.h. am gefragten Strömungsmuster, beteiligten Linien ausgewählt werden. Um eine intuitive Darstellung der Resultate zu erreichen, haben wir uns von Blutflußillustrationen inspirieren lassen und präsentieren eine abstrakte Linienbündel- und Wirbeldarstellung. Die Linienprädikatmethode sowie die abstrakte Darstellung der Strömungsmuster wurden an 4D PC-MRI-Daten von gesunden und pathologischen Aorten- und Herzdaten erfolgreich getestet. Auch die Evaluierung durch Experten zeigt die Nützlichkeit der Methode und ihr Potential für den Einsatz in der Forschung und der Klinik.This thesis’ central theme is the use of illustrative methods to solve flow visualization problems. The goal of flow visualization is to provide users with software tools supporting them analyzing and extracting knowledge from their fluid dynamics data. This fluid dynamics data is produced in large amounts by simulations or measurements to answer diverse questions in application fields like engineering or medicine. This thesis deals with two unsolved problems in flow visualization and tackles them with methods of illustrative visualization. The latter is a subbranch of visualization whose methods are inspired by the art work of professional illustrators. They are specialized in the comprehensible and esthetic representation of complex knowledge. With illustrative visualization, their techniques are applied to real data to enhance their representation. The first problem dealt with in this thesis is the limited shape and flow perception of complex stream surfaces. Self-occlusion and wrap-ups hinder their effective use in the most interesting flow situations. On the basis of hand-drawn flow illustrations, a surface rendering method was designed that uses silhouettes, non-photorealistic shading, and illustrative surface stream lines. Additionally, geometrical and flow-based surface cuts allow the user an interactive exploration of the surface and the flow it represents. By applying this illustrative technique to various stream surfaces and collecting expert feedback, we could show that the comprehensibility of the stream surfaces was enhanced – especially in complex areas with surface wrap-ups and singularities. The second problem tackled in this thesis is the analysis of blood flow from 4D PC-MRI data. From this rather young data modality, medical experts expect many advances in the research of cardiovascular diseases because it delivers a three-dimensional and time-resolved image of the hemodynamics. However, 4D PC-MRI data are mainly processed with standard flow visualizaton tools, which do not fulfill the requirements of medical users. They need a quick and easy-to-understand display of the relevant blood flow aspects. We developed a tool for the visual analysis of blood flow that allows a fast detection of distinctive flow patterns, such as high-velocity jets, vortices, or areas with high residence times. The basic idea is to precalculate integral lines and use specifically designed line predicates to select and display only lines involved in the pattern of interest. Traditional blood flow illustrations inspired us to an abstract and comprehensible depiction of the resulting line bundles and vortices. The line predicate method and the illustrative flow pattern representation were successfully tested with 4D PC-MRI data of healthy and pathological aortae and hearts. Also, the feedback of several medical experts confirmed the usefulness of our methods and their capabilities for a future application in the clinical research and routine

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

An optimal control approach to determine resistance-type boundary conditions from in-vivo data for cardiovascular simulations

The choice of appropriate boundary conditions is a fundamental step in computational fluid dynamics (CFD) simulations of the cardiovascular system. Boundary conditions, in fact, highly affect the computed pressure and flow rates, and consequently haemodynamic indicators such as wall shear stress (WSS), which are of clinical interest. Devising automated procedures for the selection of boundary conditions is vital to achieve repeatable simulations. However, the most common techniques do not automatically assimilate patient-specific data, relying instead on expensive and time-consuming manual tuning procedures. In this work, we propose a technique for the automated estimation of outlet boundary conditions based on optimal control. The values of resistive boundary conditions are set as control variables and optimized to match available patient-specific data. Experimental results on four aortic arches demonstrate that the proposed framework can assimilate 4D-Flow MRI data more accurately than two other common techniques based on Murray's law and Ohm's law

A tomographic microscopy-compatible Langendorff system for the dynamic structural characterization of the cardiac cycle

ntroduction: Cardiac architecture has been extensively investigated ex vivo using a broad spectrum of imaging techniques. Nevertheless, the heart is a dynamic system and the structural mechanisms governing the cardiac cycle can only be unveiled when investigating it as such. Methods: This work presents the customization of an isolated, perfused heart system compatible with synchrotron-based X-ray phase contrast imaging (X-PCI). Results: Thanks to the capabilities of the developed setup, it was possible to visualize a beating isolated, perfused rat heart for the very first time in 4D at an unprecedented 2.75 μm pixel size (10.6 μm spatial resolution), and 1 ms temporal resolution. Discussion: The customized setup allows high-spatial resolution studies of heart architecture along the cardiac cycle and has thus the potential to serve as a tool for the characterization of the structural dynamics of the heart, including the effects of drugs and other substances able to modify the cardiac cycle

Dynamic Image Processing for Guidance of Off-pump Beating Heart Mitral Valve Repair

Compared to conventional open heart procedures, minimally invasive off-pump beating heart mitral valve repair aims to deliver equivalent treatment for mitral regurgitation with reduced trauma and side effects. However, minimally invasive approaches are often limited by the lack of a direct view to surgical targets and/or tools, a challenge that is compounded by potential movement of the target during the cardiac cycle. For this reason, sophisticated image guidance systems are required in achieving procedural efficiency and therapeutic success. The development of such guidance systems is associated with many challenges. For example, the system should be able to provide high quality visualization of both cardiac anatomy and motion, as well as augmenting it with virtual models of tracked tools and targets. It should have the capability of integrating pre-operative images to the intra-operative scenario through registration techniques. The computation speed must be sufficiently fast to capture the rapid cardiac motion. Meanwhile, the system should be cost effective and easily integrated into standard clinical workflow. This thesis develops image processing techniques to address these challenges, aiming to achieve a safe and efficient guidance system for off-pump beating heart mitral valve repair. These techniques can be divided into two categories, using 3D and 2D image data respectively. When 3D images are accessible, a rapid multi-modal registration approach is proposed to link the pre-operative CT images to the intra-operative ultrasound images. The ultrasound images are used to display the real time cardiac motion, enhanced by CT data serving as high quality 3D context with annotated features. I also developed a method to generate synthetic dynamic CT images, aiming to replace real dynamic CT data in such a guidance system to reduce the radiation dose applied to the patients. When only 2D images are available, an approach is developed to track the feature of interest, i.e. the mitral annulus, based on bi-plane ultrasound images and a magnetic tracking system. The concept of modern GPU-based parallel computing is employed in most of these approaches to accelerate the computation in order to capture the rapid cardiac motion with desired accuracy. Validation experiments were performed on phantom, animal and human data. The overall accuracy of registration and feature tracking with respect to the mitral annulus was about 2-3mm with computation time of 60-400ms per frame, sufficient for one update per cardiac cycle. It was also demonstrated in the results that the synthetic CT images can provide very similar anatomical representations and registration accuracy compared to that of the real dynamic CT images. These results suggest that the approaches developed in the thesis have good potential for a safer and more effective guidance system for off-pump beating heart mitral valve repair

NOVEL STRATEGIES FOR THE MORPHOLOGICAL AND BIOMECHANICAL ANALYSIS OF THE CARDIAC VALVES BASED ON VOLUMETRIC CLINICAL IMAGES

This work was focused on the morphological and biomechanical analysis of the heart valves exploiting the volumetric data. Novel methods were implemented to perform cardiac valve structure and sub-structure segmentation by defining long axis planes evenly rotated around the long axis of the valve. These methods were exploited to successfully reconstruct the 3D geometry of the mitral, tricuspid and aortic valve structures. Firstly, the reconstructed models were used for the morphological analysis providing a detailed description of the geometry of the valve structures, also computing novel indexes that could improve the description of the valvular apparatus and help their clinical assessment. Additionally, the models obtained for the mitral valve complex were adopted for the development of a novel biomechanical approach to simulate the systolic closure of the valve, relying on highly-efficient mass-spring models thus obtaining a good trade-off between the accuracy and the computational cost of the numerical simulations. In specific: \u2022 First, an innovative and semi-automated method was implemented to generate the 3D model of the aortic valve and of its calcifications, to quantitively describe its 3D morphology and to compute the anatomical aortic valve area (AVA) based on multi-detector computed tomography images. The comparison of the obtained results vs. effective AVA measurements showed a good correlation. Additionally, these methods accounted for asymmetries or anatomical derangements, which would be difficult to correctly capture through either effective AVA or planimetric AVA. \u2022 Second, a tool to quantitively assess the geometry of the tricuspid valve during the cardiac cycle using multidetector CT was developed, in particular focusing on the 3D spatial relationship between the tricuspid annulus and the right coronary artery. The morphological analysis of the annulus and leaflets confirmed data reported in literature. The qualitative and quantitative analysis of the spatial relationship could standardize the analysis protocol and be pivotal in the procedure planning of the percutaneous device implantation that interact with the tricuspid annulus. \u2022 Third, we simulated the systolic closure of three patient specific mitral valve models, derived from CMR datasets, by means of the mass spring model approach. The comparison of the obtained results vs. finite element analyses (considered as the gold-standard) was performed tuning the parameters of the mass spring model, so to obtain the best trade-off between computational expense and accuracy of the results. A configuration mismatch between the two models lower than two times the in-plane resolution of starting imaging data was yielded using a mass spring model set-up that requires, on average, only ten minutes to simulate the valve closure. \u2022 Finally, in the last chapter, we performed a comprehensive analysis which aimed at exploring the morphological and mechanical changes induced by the myxomatous pathologies in the mitral valve tissue. The analysis of mitral valve thickness confirmed the data and patterns reported in literature, while the mechanical test accurately described the behavior of the pathological tissue. A preliminary implementation of this data into finite element simulations suggested that the use of more reliable patient-specific and pathology-specific characterization of the model could improve the realism and the accuracy of the biomechanical simulations

Improved 3D MR Image Acquisition and Processing in Congenital Heart Disease

Congenital heart disease (CHD) is the most common type of birth defect, affecting about 1% of the population. MRI is an essential tool in the assessment of CHD, including diagnosis, intervention planning and follow-up. Three-dimensional MRI can provide particularly rich visualization and information. However, it is often complicated by long scan times, cardiorespiratory motion, injection of contrast agents, and complex and time-consuming postprocessing. This thesis comprises four pieces of work that attempt to respond to some of these challenges. The first piece of work aims to enable fast acquisition of 3D time-resolved cardiac imaging during free breathing. Rapid imaging was achieved using an efficient spiral sequence and a sparse parallel imaging reconstruction. The feasibility of this approach was demonstrated on a population of 10 patients with CHD, and areas of improvement were identified. The second piece of work is an integrated software tool designed to simplify and accelerate the development of machine learning (ML) applications in MRI research. It also exploits the strengths of recently developed ML libraries for efficient MR image reconstruction and processing. The third piece of work aims to reduce contrast dose in contrast-enhanced MR angiography (MRA). This would reduce risks and costs associated with contrast agents. A deep learning-based contrast enhancement technique was developed and shown to improve image quality in real low-dose MRA in a population of 40 children and adults with CHD. The fourth and final piece of work aims to simplify the creation of computational models for hemodynamic assessment of the great arteries. A deep learning technique for 3D segmentation of the aorta and the pulmonary arteries was developed and shown to enable accurate calculation of clinically relevant biomarkers in a population of 10 patients with CHD