Etude de la méthode de Boltzmann sur réseau pour la segmentation d'anévrismes cérébraux

Cerebral aneurysm is a fragile area on the wall of a blood vessel in the brain, which can rupture and cause major bleeding and cerebrovascular accident. The segmentation of cerebral aneurysm is a primordial step for diagnosis assistance, treatment and surgery planning. Unfortunately, manual segmentation is still an important part in clinical angiography but has become a burden given the huge amount of data generated by medical imaging systems. Automatic image segmentation techniques provides an essential way to easy and speed up clinical examinations, reduce the amount of manual interaction and lower inter operator variability. The main purpose of this PhD work is to develop automatic methods for cerebral aneurysm segmentation and measurement. The present work consists of three main parts. The first part deals with giant aneurysm segmentation containing lumen and thrombus. The methodology consists of first extracting the lumen and thrombus using a two-step procedure based on the LBM, and then refining the shape of the thrombus using level set technique. In this part the proposed method is also compared with manual segmentation, demonstrating its good segmentation accuracy. The second part concerns a LBM approach to vessel segmentation in 2D+t images and to cerebral aneurysm segmentation in 3D medical images through introducing a LBM D3Q27 model, which allows achieving a good segmentation and high robustness to noise. The last part investigates a true 4D segmentation model by considering the 3D+t data as a 4D hypervolume and using a D4Q81 lattice in LBM where time is considered in the same manner as for other three dimensions for the definition of particle moving directions in the LBM model.L'anévrisme cérébral est une région fragile de la paroi d'un vaisseau sanguin dans le cerveau, qui peut se rompre et provoquer des saignements importants et des accidents vasculaires cérébraux. La segmentation de l'anévrisme cérébral est une étape primordiale pour l'aide au diagnostic, le traitement et la planification chirurgicale. Malheureusement, la segmentation manuelle prend encore une part importante dans l'angiographie clinique et elle est devenue couteuse en temps de traitement étant donné la gigantesque quantité de données générées par les systèmes d'imagerie médicale. Les méthodes de segmentation automatique d'image constituent un moyen essentiel pour faciliter et accélérer l'examen clinique et pour réduire l'interaction manuelle et la variabilité inter-opérateurs. L'objectif principal de ce travail de thèse est de développer des méthodes automatiques pour la segmentation et la mesure des anévrismes. Le présent travail de thèse est constitué de trois parties principales. La première partie concerne la segmentation des anévrismes géants qui contiennent à la fois la lumière et le thrombus. La méthode consiste d'abord à extraire la lumière et le thrombus en utilisant une procédure en deux étapes, puis à affiner la forme du thrombus à l'aide de la méthode des courbes de niveaux. Dans cette partie, la méthode proposée est également comparée à la segmentation manuelle, démontrant sa bonne précision. La deuxième partie concerne une approche LBM pour la segmentation des vaisseaux dans des images 2D+t et de l'anévrisme cérébral dans les images en 3D. La dernière partie étudie un modèle de segmentation 4D en considérant les images 3D+t comme un hypervolume 4D et en utilisant un réseau LBM D4Q81, dans lequel le temps est considéré de la même manière que les trois autres dimensions pour la définition des directions de mouvement des particules dans la LBM, considérant les données 3D+t comme un hypervolume 4D et en utilisant un réseau LBM D4Q81. Des expériences sont réalisées sur des images synthétiques d'hypercube 4D et d'hypersphere 4D. La valeur de Dice sur l'image de l'hypercube avec et sans bruit montre que la méthode proposée est prometteuse pour la segmentation 4D et le débruitage

Automated Segmentation of Cerebral Aneurysm Using a Novel Statistical Multiresolution Approach

Cerebral Aneurysm (CA) is a vascular disease that threatens the lives of many adults. It a ects almost 1:5 - 5% of the general population. Sub- Arachnoid Hemorrhage (SAH), resulted by a ruptured CA, has high rates of morbidity and mortality. Therefore, radiologists aim to detect it and diagnose it at an early stage, by analyzing the medical images, to prevent or reduce its damages. The analysis process is traditionally done manually. However, with the emerging of the technology, Computer-Aided Diagnosis (CAD) algorithms are adopted in the clinics to overcome the traditional process disadvantages, as the dependency of the radiologist's experience, the inter and intra observation variability, the increase in the probability of error which increases consequently with the growing number of medical images to be analyzed, and the artifacts added by the medical images' acquisition methods (i.e., MRA, CTA, PET, RA, etc.) which impedes the radiologist' s work. Due to the aforementioned reasons, many research works propose di erent segmentation approaches to automate the analysis process of detecting a CA using complementary segmentation techniques; but due to the challenging task of developing a robust reproducible reliable algorithm to detect CA regardless of its shape, size, and location from a variety of the acquisition methods, a diversity of proposed and developed approaches exist which still su er from some limitations. This thesis aims to contribute in this research area by adopting two promising techniques based on the multiresolution and statistical approaches in the Two-Dimensional (2D) domain. The rst technique is the Contourlet Transform (CT), which empowers the segmentation by extracting features not apparent in the normal image scale. While the second technique is the Hidden Markov Random Field model with Expectation Maximization (HMRF-EM), which segments the image based on the relationship of the neighboring pixels in the contourlet domain. The developed algorithm reveals promising results on the four tested Three- Dimensional Rotational Angiography (3D RA) datasets, where an objective and a subjective evaluation are carried out. For the objective evaluation, six performance metrics are adopted which are: accuracy, Dice Similarity Index (DSI), False Positive Ratio (FPR), False Negative Ratio (FNR), speci city, and sensitivity. As for the subjective evaluation, one expert and four observers with some medical background are involved to assess the segmentation visually. Both evaluations compare the segmented volumes against the ground truth data

Virtual endovascular treatment of intracranial aneurysms: models and uncertainty

Virtual endovascular treatment models (VETMs) have been developed with the view to aid interventional neuroradiologists and neurosurgeons to pre-operatively analyze the comparative efficacy and safety of endovascular treatments for intracranial aneurysms. Based on the current state of VETMs in aneurysm rupture risk stratification and in patient-specific prediction of treatment outcomes, we argue there is a need to go beyond personalized biomechanical flow modeling assuming deterministic parameters and error-free measurements. The mechanobiological effects associated with blood clot formation are important factors in therapeutic decision making and models of post-treatment intra-aneurysmal biology and biochemistry should be linked to the purely hemodynamic models to improve the predictive power of current VETMs. The influence of model and parameter uncertainties associated to each component of a VETM is, where feasible, quantified via a random-effects meta-analysis of the literature. This allows estimating the pooled effect size of these uncertainties on aneurysmal wall shear stress. From such meta-analyses, two main sources of uncertainty emerge where research efforts have so far been limited: (1) vascular wall distensibility, and (2) intra/intersubject systemic flow variations. In the future, we suggest that current deterministic computational simulations need to be extended with strategies for uncertainty mitigation, uncertainty exploration, and sensitivity reduction techniques. WIREs Syst Biol Med 2017, 9:e1385. doi: 10.1002/wsbm.138

In-silico clinical trials for assessment of intracranial flow diverters

In-silico trials refer to pre-clinical trials performed, entirely or in part, using individualised computer models that simulate some aspect of drug effect, medical device, or clinical intervention. Such virtual trials reduce and optimise animal and clinical trials, and enable exploring a wider range of anatomies and physiologies. In the context of endovascular treatment of intracranial aneurysms, in-silico trials can be used to evaluate the effectiveness of endovascular devices over virtual populations of patients with different aneurysm morphologies and physiologies. However, this requires (i) a virtual endovascular treatment model to evaluate device performance based on a reliable performance indicator, (ii) models that represent intra- and inter-subject variations of a virtual population, and (iii) creation of cost-effective and fully-automatic workflows to enable a large number of simulations at a reasonable computational cost and time. Flow-diverting stents have been proven safe and effective in the treatment of large wide-necked intracranial aneurysms. The presented thesis aims to provide the ingredient models of a workflow for in-silico trials of flow-diverting stents and to enhance the general knowledge of how the ingredient models can be streamlined and accelerated to allow large-scale trials. This work contributed to the following aspects: 1) To understand the key ingredient models of a virtual treatment workflow for evaluation of the flow-diverter performance. 2) To understand the effect of input uncertainty and variability on the workflow outputs, 3) To develop generative statistical models that describe variability in internal carotid artery flow waveforms, and investigate the effect of uncertainties on quantification of aneurysmal wall shear stress, 4) As part of a metric to evaluate success of flow diversion, to develop and validate a thrombosis model to assess FD-induced clot stability, and 5) To understand how a fully-automatic aneurysm flow modelling workflow can be built and how computationally inexpensive models can reduce the computational costs

Lattice-Boltzmann simulations of cerebral blood flow

Computational haemodynamics play a central role in the understanding of blood behaviour in the cerebral vasculature, increasing our knowledge in the onset of vascular diseases and their progression, improving diagnosis and ultimately providing better patient prognosis. Computer simulations hold the potential of accurately characterising motion of blood and its interaction with the vessel wall, providing the capability to assess surgical treatments with no danger to the patient. These aspects considerably contribute to better understand of blood circulation processes as well as to augment pre-treatment planning. Existing software environments for treatment planning consist of several stages, each requiring significant user interaction and processing time, significantly limiting their use in clinical scenarios. The aim of this PhD is to provide clinicians and researchers with a tool to aid in the understanding of human cerebral haemodynamics. This tool employs a high performance fluid solver based on the lattice-Boltzmann method (coined HemeLB), high performance distributed computing and grid computing, and various advanced software applications useful to efficiently set up and run patient-specific simulations. A graphical tool is used to segment the vasculature from patient-specific CT or MR data and configure boundary conditions with ease, creating models of the vasculature in real time. Blood flow visualisation is done in real time using in situ rendering techniques implemented within the parallel fluid solver and aided by steering capabilities; these programming strategies allows the clinician to interactively display the simulation results on a local workstation. A separate software application is used to numerically compare simulation results carried out at different spatial resolutions, providing a strategy to approach numerical validation. This developed software and supporting computational infrastructure was used to study various patient-specific intracranial aneurysms with the collaborating interventionalists at the National Hospital for Neurology and Neuroscience (London), using three-dimensional rotational angiography data to define the patient-specific vasculature. Blood flow motion was depicted in detail by the visualisation capabilities, clearly showing vortex fluid ow features and stress distribution at the inner surface of the aneurysms and their surrounding vasculature. These investigations permitted the clinicians to rapidly assess the risk associated with the growth and rupture of each aneurysm. The ultimate goal of this work is to aid clinical practice with an efficient easy-to-use toolkit for real-time decision support

Towards patient-speci�fic modelling of cerebral blood flow using lattice-Boltzmann methods

Patient-specifi�c Computational fluid dynamics (CFD) studies of cerebral blood flow have the potential to help plan neurosurgery, but developing realistic simulation methods that deliver results quickly enough presents a major challenge. The majority of CFD studies assume that the arterial walls are rigid. Since the lattice-Boltzmann method (LBM) is computationally efficient on multicore machines, some methods for carrying out lattice-Boltzmann simulations of time-dependent fluid flow in elastic vessels are developed. They involve integrating the equations of motion for a number of points on the wall. The calculations at every lattice site and point on the wall depend only on information from neighbouring lattice sites or wall points, so they are suitable for efficient computation on multicore machines. The �first method is suitable for three-dimensional axisymmetric vessels. The steady-state solutions for the wall displacement and flow �fields in a cylinder at realistic parameters for cerebral blood ow agree closely with the analytical solutions. Compared to simulations with rigid walls, simulations with elastic walls require 13% more computational e�ffort at the parameters chosen in this study. A scheme is then developed for a more complex geometry in two dimensions, which applies the full theory of linear elasticity. The steady-state wall pro�files obtained from simulations of a Starling resistor agree closely with those from existing computational studies. I �find that it is essential to change the lattice sites from solid to fluid and vice versa if the wall crosses any of them during the simulation. Simple tests of the dynamics show that when the mass of the wall is much greater than that of the fluid, the period of oscillation of the wall agrees within 7% of the expected period. This method could be extended to three dimensions for use in cerebral blood ow simulations

Approximation anatomischer Strukturen und biomedizinischer Prozesse zur rechnergestützten Untersuchung der Hämodynamik in Aneurysmen

Arterien des Menschen können Aneurysmen aufweisen, deren Ruptur zu lebensbedrohenden inneren Blutungen wie Schlaganfällen führen kann. Ein Therapieansatz ist das Einsetzen von sogenannten Stents. Eine Ruptur oder der Einfluss eines Stents kann mit dem momentanen Stand der Technik nicht exakt vorhergesagt werden. Für eine optimale Behandlung von Patienten wäre dies allerdings eine wichtige Zusatzinformation für den behandelnden Arzt. Zur Bestimmung dieser Zusatzinformation sollen zukünftig Simulationen der Hämodynamik in pathologischen Arterien eingesetzt werden. In dieser Arbeit werden Strömungsgeschwindigkeiten in Arterien ohne beziehungsweise mit Einbringung von Einbauten wie Stents berechnet und die entstehenden Wandscherspannungen im Hinblick auf eine Rupturvorhersage untersucht. Weiterhin wird der Massentransfer zwischen Arterie und Aneurysma charakterisiert und eine Analyse des Thrombosierungsverhaltens unter Strömungseinfluss vorgenommen. Bei letztgenanntem Thema werden insbesondere der Verschluss von Aneurysmen durch Thromben, die Ortseindämmung der Thrombenbildung und das Verhalten von wandanhaftenden Thromben auch in Bezug auf eine Ablösung untersucht. Um hierfür geeignete Simulationen durchführen zu können, wird eine Analyse der biomedizinischen Grundlagen durchgeführt. Für die Untersuchung der komplexen Dynamik sind aus methodischer Sicht zwei grundlegende Aspekte zu bearbeiten: die geometrische und die funktionelle Approximation. Die funktionelle Approximation biomedizinischer Prozesse umfasst die Untersuchung der Blutströmung, des Transports von passiven Stoffen und der Thrombosierung. Hierfür werden entsprechende Modelle identifiziert, in entsprechende Lattice-Boltzmann-Verfahren umgewandelt, simuliert und untersucht. Durch die Erarbeitung geeigneter Konzepte für eine Umsetzung der hier beschriebenen Simulationen auf einzelnen oder mehreren, miteinander kommunizierenden Grafikprozessoren kann eine effiziente Simulation der gekoppelten Multi-Physik-Probleme mit Lattice-Boltzmann-Verfahren erreicht werden. Insgesamt stellt diese Vorgehensweise ein Novum dar und unterstreicht die Praktikabilität der Methode. Die geometrische Approximation anatomischer Strukturen wird in dieser Arbeit mit Level-Set-Darstellungen gelöst. Mit ihnen können vielfältige Problemstellungen im Umfeld der Simulation bearbeitet werden, dies umfasst beispielsweise die Konstruktion einer Simulationsdomäne aus unterschiedlichen Tomographiedaten und die Einbringung von Einbauten wie Stents in das Untersuchungsgebiet. Durch die Kombination mit der Lattice-Boltzmann-Methode können Vorteile gegenüber dem Stand der Technik erreicht werden, etwa bei der effizienten Berechnung der Wandscherspannungen. Eine Validierung der Strömungs- und Transportsimulationen wird mit hochaufgelöster Magnetresonanztomographie vorgenommen. Dazu wird ein Modell des Aufnahmevorgangs unter Einfluss von Radiofrequenz-Magnetfeldern und Gradienten erstellt und der Magnetisierungstransport sowie die Relaxation simuliert. Die bestimmten Abweichungen zwischen Simulation und Messung sind insgesamt gering. Für die Messexperimente werden erstmals 3D-Druckverfahren für die Konstruktion von physischen Modellen eingesetzt und deren Güte untersucht. Durch die Ergebnisse dieser Arbeit steht eine effiziente und umfassende Verarbeitungspipeline für Blutströmungs-, Transport- und Thrombosierungsprozesse für weitere Untersuchungen bereit. Sie kann ebenfalls leicht um neue Modelle erweitert werden. Die Simulation der Magnetresonanztomographie für Flussbildgebung ermöglicht ebenfalls zukünftige Anwendungen im Bereich der Sequenzentwicklung