There is a remarkable relationship between an organism's metabolic rate (resting power consumption) and the organism's mass. It may be a universal law of nature that an organism's resting metabolic rate is proportional to its mass to the power of 3/4. This relationship, known as Kleiber's Law, appears to be valid for both plants and animals. This law is important because it implies that larger organisms are more efficient than smaller organisms, and knowledge regarding metabolic rates are essential to a multitude of other fields in ecology and biology. This includes modeling the interactions of many species across multiple trophic levels, distributions of species abundances across large spatial landscapes, and even medical diagnostics for respiratory and cardiovascular pathologies. Previous models of vascular networks that seek to identify the origin of metabolic scaling have all been based on the unrealistic assumption of perfectly symmetric branching. In this dissertation I will present a theory of asymmetric branching in self-similar vascular networks (published by Brummer et al. in [9]). The theory shows that there can exist a suite of vascular forms that result in the often observed 3/4 metabolic scaling exponent of Kleiber's Law. Furthermore, the theory makes predictions regarding major morphological features related to vascular branching patterns and their relationships to metabolic scaling. These predictions are suggestive of evolutionary convergence in vascular branching. To test these predictions, I will present an analysis of real mammalian and plant vascular data that shows: (i) broad patterns in vascular networks across entire animal kingdoms and (ii) within these patterns, plant and mammalian vascular networks can be uniquely distinguished from one another (publication in preparation by Brummer et al.). I will also present results from a computational study in support of point (i). Namely, that asymmetric branching may be the optimal strategy to balance the simultaneous demands of maximizing the number of nutrient exchange sites (capillaries or leaves) versus hydraulic resistance to resource transport (publication in preparation by Brummer et al.). Finally, I report on improved methods of estimating whole organism metabolism based solely on measurements of vasculature.

Vascularization is essential for living tissue and remains a major challenge in the field of tissue engineering. A lack of a perfusable channel network within a large and densely populated tissue engineered construct leads to necrotic core formation, preventing fabrication of functional tissues and organs. While many approaches have been reported for forming vascular networks, including materials processing techniques, such those involving lithography, bioprinting, and sacrificial templating; and cell-based approaches, in which cellular self-organization processes form vessels; all are deficient in their ability to form a vessel system of sufficient complexity for supporting a large cellular construct. What is missing from the literature is a method for forming a fully three-dimensional vascular network over the full range of length-scales found in native vessel systems, which can be used alongside cells and perfused with fluids to support their function. A large number of research groups are thus pursuing novel methods for fabricating vascular systems in order that new tissues and organs can be fabricated in the lab. In this project, a 3D printing-based approach was used to form vascular networks which are hierarchical, three-dimensional, and perfusable. This was performed in thick, cellularized hydrogels similar in composition to native tissue; these being collagen (ECM-like) and fibrin (woundlike), both of which are highly capable of supporting cellular activities, such as cell seeding, cell spreading, and capillary morphogenesis. In order to make use of 3D printed network templates in cellularized hydrogel environments, it was necessary to develop a new approach in which standard 3D printed materials were converted into a gelatin template, via an alginate intermediary, which can be removed quickly in physiologic conditions and which does not reduce cell viability. This multi-casting approach enables a hierarchical channel network to be formed in three-dimensions, capable of being perfused with cell medium to maintain the viability of a cell population, thereby addressing the fundamental problem. Using standard cell staining and immuno-histochemistry techniques, we showed good endothelial cell seeding and the presence of tight junctions between the channel endothelial cells. When fibroblasts were seeded into the bulk of the hydrogel, a high degree of cell viability and cell spreading was observed when a threshold flow rate is met. By counting the number of live and dead cells in a sample regions of the gel, we were able to show a dependency of cell viability upon the perfusion flow rate and further determine a regime in which the vast majority of cells are alive and spreading. This data informs future cellular experiments using this platform technology. The limits of existing 3D printing technology meant that the micro-scale vasculature needed to be formed by other means. Cellular co-culture of endothelial and stromal cell types has been shown to be capable of forming capillary-like structures in vitro. For inclusion with the 3D printed channel system, we investigated the use of an angiogenic method for capillary formation, using multi-cellular spheroids, and a vasculogenic approach, using individual cells, in order that the full vascular system could be constructed. Endothelial and mesenchymal stromal cells were encapsulated in small fibrin and collagen gels and maintained under static culture conditions in order to form capillaries by the above approaches. The aim here was to find a particular gel composition and cell concentration which would support capillary morphogenesis while being suitably robust to handle the mechanical stresses associated with perfusion. As future work, the next step will be to incorporate the vasculogenic co-culture technique, used to form capillary-sized vessels, into a perfusable gel containing the large templated channels, formed via the multi-casting approach. The challenge here is to anastomose the capillary-sized vessels to the large templated channels and thereby enable perfusion of the capillary vessels. This step would be a highly significant development in the field as it would mean large constructs could be fabricated with physiological densities of cells, which could lead to a range of potential therapeutic applications.

One of the ways that a vascular network grows is through the process of angiogenesis, wherebya new blood vessel forms as a branch from an existing vessel towards an area which isstimulating vascular growth. Due to the demands for nutrients and waste transport, growingtumour cells will access the surrounding vascular network by inducing angiogenesis. Once thetumour is connected with the vascular system it can grow further and colonize distant organs.Given the critical nature of this step in tumour development, there is a demand for mathematicaland computational models to provide an understanding of the process for treatment in predictivemedicine. These models allow us to generate vascular networks that demonstrate similarbehaviour to that of the observed networks; however, there is a lack of quantifiable measures ofsimilarity between generated networks, or, of a generated and real network. Furthermore, thereis not an established way to determine which measures hold the most relevance todistinguishing similarity. To construct such a measure we transform our generated vascularnetworks into an abstract graph representation which allows exploration of the plethora of graphcentralities. We propose to determine the relevance of a centrality by finding one that acts as asynthetic likelihood function for estimating the model's parameters with minimal error.Evaluating the relevance of many centralities, it is then possible to suggest which centralitiesshould be used to quantitatively determine similarity. This allows for a way to measure howrealistic a model's growth is, and if given sufficient data, to distinguish between regular andtumour-induced angiogenesis and use it within cancer screening.

Understanding the perfusion of blood and drugs in tumours is fundamental to foreseeing the efficacy of treatment regimes and predicting tumour growth. In particular, the dependence of these processes on the tumour vascular structure is poorly established. The objective of this thesis is to derive effective equations describing blood, and drug perfusion in vascular tumours, and specifically to determine the dependence of these on the tumour vascular structure. This dependence occurs through the interaction between two different length scales - that which characterizes the structure of the vascular network, and that which characterizes the tumour as a whole. Our method throughout is to use homogenization as a tool to evaluate this interaction. In Chapter 1 we introduce the problem. In Chapter 2 we develop a theoretical model to describe fluid flow in solid tumours through both the vasculature and the interstitium, at a number of length scales. Ultimately we homogenize over a network of capillaries to form a coupled porous medium model in terms of a vascular density. Whereas in Chapter 2 it is necessary to specify the vascular structure to derive the effective equations, in Chapter 3 we employ asymptotic homogenization through multiple scales to derive the coupled equations for an arbitrary periodic vascular network. In Chapter 4, we extend this analysis to account for advective and diffusive transport of anticancer drugs delivered intravenously; we consider a range of reaction properties in the interstitium and boundary conditions on the vascular wall. The models derived in Chapters 2–4 could be applied to any drug type and treatment regime; to demonstrate their potential, we simulate the delivery of vinblastine in dorsal skinfold chambers in Chapter 5 and make quantitative predictions regarding the optimal treatment regime. In the final Chapter we summarize the main results and indicate directions for further work.

As atividades de teste automatizado contribuem significativamente para a redução de custos e a produtividade do projeto durante o processo de desenvolvimento de software. O teste automatizado reduz o esforço humano e aumenta a qualidade do produto final. No entanto, a alta complexidade da saída produzida pelos SUT (do inglês, System Under Test) contemporâneos limita, em alguns casos, a aplicação de estratégias de teste automatizadas. Sistemas com saídas gráficas/áudio, imagens tridimensionais, interfaces gráficas com o usuário e alguns aplicativos da Web são exemplos de sistemas com saídas complexas. A falta de oráculos automatizados de teste leva à aplicação de testes executados manualmente pelo próprio testador (oráculo humano), de modo informal, ad-hoc e improdutivo. Uma possível contribuição para aliviar esforços do testador é a implementação de oráculos de teste baseados na extração de características das saídas do SUT. Resultados de trabalhos anteriores mostram que tal abordagem contribui para o aumento da produtividade do teste, mitigando e complementando os esforços manuais. Este trabalho de mestrado propõe e avalia oráculos de teste automatizados para sistemas cujas saídas consistem em imagens médicas tridimensionais. Para tanto, é explorado o framework O-FIm/CO (do inglês, Oracle for Images and Complex Outputs) que utiliza conceitos de Recuperação de Imagens Baseada em Conteúdo (do inglês, Content-Based Image Retrieval CBIR) como uma forma de automatizar oráculos de teste. Além de adaptações e extensões do framework, desenvolveram-se plug-ins que representam extratores de características de imagens médicas tridimensionais de vasos sanguíneos. Para evidenciar a eficácia da abordagem, foram conduzidos dois estudos experimentais objetivando avaliar a eficácia e a precisão dos oráculos de teste baseados em características na avaliação desse tipo de imagem. Além disso, realizou-se um estudo experimental comparando os oráculos de teste baseados em características e oráculos humanos. Os resultados evidenciam a eficácia da abordagem como uma estratégia promissora para automatizar atividades de teste, contribuindo para a redução de tempo e esforços gerados por abordagens manuais durante a avaliação da qualidade de sistemas geradores de imagens médicas tridimensionais. / Automated testing activities significantly contribute to cost reduction and project productivity during the software development process. Automated testing reduces human effort and increases the quality of the final product. However, the high complexity of contemporary SUT outputs limits, in some cases, the application of automated test strategies. Systems with graphical/audio outputs, three-dimensional imaging, graphical user interfaces and some web applications are examples of systems with complex outputs. The lack of automated test oracles leads to the application of manual tests performed by the tester (human oracle) in an informal, ad-hoc and unproductive manner. One possible contribution to alleviate the testers efforts is to implement test oracles based on the extraction of characteristics from the SUT outputs. Results from previous work show that such an approach contributes to increase test productivity, mitigating and complementing manual efforts. This dissertation proposes and evaluates automated test oracles for systems whose outputs consist of three-dimensional medical images. To do so, the framework O-FIm/CO (Oracle for Images and Complex Outputs) that uses CBIR (Content-Based Image Retrieval) concepts is explored as a strategy to automate test oracles. In addition to adaptations and extensions of the framework, plug-ins were developed which represent extractors of three-dimensional medical image characteristics of blood vessels. To demonstrate the efficacy of the approach, two experimental studies were conducted to evaluate the efficacy and accuracy of feature-based test oracles in the evaluation of such images. Moreover, an experimental study was conducted to compare feature-based test oracles with human oracles. The results show the efficacy of the approach as a promising strategy to automate testing activities, contributing to the reduction of time and effort generated by manual approaches during the quality assessment of three-dimensional medical imaging systems.

As atividades de teste automatizado contribuem significativamente para a redução de custos e a produtividade do projeto durante o processo de desenvolvimento de software. O teste automatizado reduz o esforço humano e aumenta a qualidade do produto final. No entanto, a alta complexidade da saída produzida pelos SUT (do inglês, System Under Test) contemporâneos limita, em alguns casos, a aplicação de estratégias de teste automatizadas. Sistemas com saídas gráficas/áudio, imagens tridimensionais, interfaces gráficas com o usuário e alguns aplicativos da Web são exemplos de sistemas com saídas complexas. A falta de oráculos automatizados de teste leva à aplicação de testes executados manualmente pelo próprio testador (oráculo humano), de modo informal, ad-hoc e improdutivo. Uma possível contribuição para aliviar esforços do testador é a implementação de oráculos de teste baseados na extração de características das saídas do SUT. Resultados de trabalhos anteriores mostram que tal abordagem contribui para o aumento da produtividade do teste, mitigando e complementando os esforços manuais. Este trabalho de mestrado propõe e avalia oráculos de teste automatizados para sistemas cujas saídas consistem em imagens médicas tridimensionais. Para tanto, é explorado o framework O-FIm/CO (do inglês, Oracle for Images and Complex Outputs) que utiliza conceitos de Recuperação de Imagens Baseada em Conteúdo (do inglês, Content-Based Image Retrieval CBIR) como uma forma de automatizar oráculos de teste. Além de adaptações e extensões do framework, desenvolveram-se plug-ins que representam extratores de características de imagens médicas tridimensionais de vasos sanguíneos. Para evidenciar a eficácia da abordagem, foram conduzidos dois estudos experimentais objetivando avaliar a eficácia e a precisão dos oráculos de teste baseados em características na avaliação desse tipo de imagem. Além disso, realizou-se um estudo experimental comparando os oráculos de teste baseados em características e oráculos humanos. Os resultados evidenciam a eficácia da abordagem como uma estratégia promissora para automatizar atividades de teste, contribuindo para a redução de tempo e esforços gerados por abordagens manuais durante a avaliação da qualidade de sistemas geradores de imagens médicas tridimensionais. / Automated testing activities significantly contribute to cost reduction and project productivity during the software development process. Automated testing reduces human effort and increases the quality of the final product. However, the high complexity of contemporary SUT outputs limits, in some cases, the application of automated test strategies. Systems with graphical/audio outputs, three-dimensional imaging, graphical user interfaces and some web applications are examples of systems with complex outputs. The lack of automated test oracles leads to the application of manual tests performed by the tester (human oracle) in an informal, ad-hoc and unproductive manner. One possible contribution to alleviate the testers efforts is to implement test oracles based on the extraction of characteristics from the SUT outputs. Results from previous work show that such an approach contributes to increase test productivity, mitigating and complementing manual efforts. This dissertation proposes and evaluates automated test oracles for systems whose outputs consist of three-dimensional medical images. To do so, the framework O-FIm/CO (Oracle for Images and Complex Outputs) that uses CBIR (Content-Based Image Retrieval) concepts is explored as a strategy to automate test oracles. In addition to adaptations and extensions of the framework, plug-ins were developed which represent extractors of three-dimensional medical image characteristics of blood vessels. To demonstrate the efficacy of the approach, two experimental studies were conducted to evaluate the efficacy and accuracy of feature-based test oracles in the evaluation of such images. Moreover, an experimental study was conducted to compare feature-based test oracles with human oracles. The results show the efficacy of the approach as a promising strategy to automate testing activities, contributing to the reduction of time and effort generated by manual approaches during the quality assessment of three-dimensional medical imaging systems.

Doenças vasculares são um problema mundial, que representa 28% das mortes no mundo e 66% do total de doenças que acometem os brasileiros. Dessa forma, há um grande interesse em pesquisar formas de prevenção e tratamento dessas doenças. Algumas medidas são relevantes no auxílio de diagnóstico, tal como: tamanho médio dos ramos, diâmetro médio das seções transversais dos vasos e padrões de divisão de ramos. Calcular essas medidas de forma manual é uma tarefa demorada e trabalhosa. Assim, esta Tese tem como objetivo, propor um método computacional de rastreamento e extração de atributos em redes vasculares a partir de imagens 3D de angiografia por ressonância magnética e por tomografia computadorizada. Trata-se de uma abordagem de rastreamento e identificação de bifurcações que difere das técnicas anteriores, utilizando a Transformada de Hough para identificar o diâmetro do vaso em cortes transversais num dado ponto ao longo de um vaso sanguíneo. Mais detalhadamente, essa abordagem utiliza um campo vetorial advindo do cálculo de uma matriz formada por derivadas parciais de segunda ordem, obtida da intensidade luminosa da imagem, para identificar a direção de um ramo de vaso. Além disso, durante o processo de rastreamento de um ramo de vaso, são calculados vários descritores de forma com o objetivo de classificar regiões como pertencentes a uma bifurcação ou não. Em adição a estes descritores, desenvolvemos uma nova medida chamada de variância do raio que permite distinguir, bifurcações, não-bifurcações e segmentos de vaso com stents (aparelho metálico usado para aumentar o diâmetro dos vasos). Para a classificação de bifurcações, criamos a medida de bifurcação, que trata-se de uma combinação linear de todos os descritores de forma apresentados neste trabalho. Testes foram realizados para atestar a eficácia da abordagem proposta, utilizando tanto imagens sintéticas quantoimagens reais. Os resultados mostraram que o método é capaz de rastrear 91% de uma rede vascular sintética variando o ponto de inicialização e 76% variando o nível de ruído. Também foi observado por meio de testes que o método proposto consegue rastrear vasos e identificar bifurcações em imagens reais sem avaliação numérica. Essa abordagem permite a extração da relação hierárquica entre os ramos em uma rede vascular e a extração do padrão de divisão dos vasos, o que contribui sobremaneira para o estudo do comportamento do fenômeno da angiogênese e no auxílio no diagnóstico de anomalias vasculares. / Vascular diseases are a main health problem, representing 28% of deaths worldwide and 66% of all diseases affecting the Brazilian population. Thus, it is important that researches in prevention and treatment of this type of disease increase. Moreover, there are several demands, such as computational tools capable of analyzing and extracting attributes from non-invasive images. The scope of this work is the analysis and extraction of data from magnetic resonance angiography and computed tomography angiography images by highlighting blood vessels. In this context, this thesis aims the development of a novel computational tracking and feature extraction method for vascular networks from 3D images. Our approach presents the following steps: First, identify the vessel cross-sections along it using the Hough transform. Then, compute a matrix composed of second order partial derivatives of image intensity to identify the direction of the vessel. Perform a feature analysis of the vessel contour to classify the bifurcation point, and finally, identify the direction of the new branch in a bifurcation point. The main contribution of this Thesis is the two new measures developed, called radius ratio and bifurcation measure, the radius ratio is capable to distinguish between a region with bifurcation, stents or without both of them. The bifurcation measure is a linear combination that allows to classify a region as bifurcation or not. Tests were performed in order to verify the proposed approach effectiveness, using both synthetic images and real images. The results showed the method is capable to track 91% of synthetic vascular networks varying the seed point and 76% varying the level of noise. Also, we performed tests in real images and by visual evaluation, we could observed that the proposed method was able to track vessels and identify bifurcations from different parts of the body. This approach allows to calculate, in the future, the density of bifurcations in a vascular network, the distance between them, the stenosis and aneurysms grading and characterize specific vessels. In addition, the vascular networks extraction allows the study of the angiogenesis phenomena and vascular anomalies.

Apesar de ser uma técnica muito difundida, a radioterapia pode causar danos ao reparo ósseo, como por exemplo, a diminuição da vascularização. Entretanto, a rede vascular óssea tem um papel importante na capacidade de regeneração dos ossos, pois fornece oxigênio e nutrientes essenciais, logo, ferramentas que auxiliem a análise dessas redes são importantes para o estudo de diversas terapias que têm influência sobre o tecido ósseo. Para analisar tais redes foi feita a reconstrução tridimensional de imagens coletadas a partir do seccionamento dos fêmures de um rato que recebeu doses de radiação em seu fêmur esquerdo, enquanto que o direito não foi irradiado sendo, portanto, utilizado para controle. Com o objetivo de auxiliar a análise desses volumes foi utilizada a técnica de esqueletização, que tem a finalidade de diminuir a quantidade de informação dos objetos e tornar a análise mais precisa e eficiente. Entretanto, existem diversos tipos de algoritmos esqueletização, sendo eles, de Afinamento, Geométricos, baseados na Transformada Distância, em Campo de Força e em Propagação de Ondas. Com o objetivo de analisar qual deles produz melhores resultados em volumes de redes vasculares foi escolhida uma implementação de cada tipo para ser testada e analisada em volumes pertencentes às redes vasculares. Além disso, o algoritmo escolhido para representar os métodos baseados em Propagação de Ondas foi desenvolvido e proposto neste trabalho exclusivamente para extrair canais de redes vasculares. Por fim, os esqueletos das redes vasculares conseguiram reproduzir com clareza a rede estudada e possibilitaram a conclusão de análises relacionadas ao impacto da radioterapia sobre a topologia vascular. Além disso, a comparação entre os tipos de algoritmos de esqueletização possibilitou um estudo aprofundado sobre o tema e sobre as diversas características de esqueletos de curva que podem ser usadas para classificar e comparar os métodos presentes na literatura. / Although a common technique, the radiotherapy can cause damage to bone repair, such as decrease in vascularization. However, the bone vascular network has an important role in capacity of bone regeneration because it provides oxygen and nutrients, therefore, tools that helps the analysis of vascular networks are important for the study of various therapies that have influence on the bone repair. In order to analyze such networks, we mande three-dimensional reconstructions of collected images from the sectioning of a mouse femurs that received radiation doses in the left femur, while the right was not irradiated and used for control. In order to aid the analysis of these volumes, skeletonization techniques were used to decrease the amount of the objects’s information and make the analysis more accurate and efficient. However, there are several types of skeletonization algorithms which uses different approachs as based on Forcefield, Thinning, based on Distance Transform, Geometrical and based on Wave Propagation. In order to analyze which of them produces the best results in vascular networks, an implementation of each type was chosen to be tested and analyzed in vascular network volumes. Furthermore, the algorithm chosen to represent the methods based on Wave Propagation was developed and proposed in this work exclusively to extract vascular networks. Finally, the skeletons of the vascular networks reproduced the network studied with clarity and enabled the conclusion of analysis related to the radiation impact on vascular topology. In addition, the comparison between the types of skeletonization algorithms allowed a deep study about the subject and on the various curve skeletons characteristics that can be used to classify and compare the methods in the literature. / Dissertação (Mestrado)

Doenças vasculares são um problema mundial, que representa 28% das mortes no mundo e 66% do total de doenças que acometem os brasileiros. Dessa forma, há um grande interesse em pesquisar formas de prevenção e tratamento dessas doenças. Algumas medidas são relevantes no auxílio de diagnóstico, tal como: tamanho médio dos ramos, diâmetro médio das seções transversais dos vasos e padrões de divisão de ramos. Calcular essas medidas de forma manual é uma tarefa demorada e trabalhosa. Assim, esta Tese tem como objetivo, propor um método computacional de rastreamento e extração de atributos em redes vasculares a partir de imagens 3D de angiografia por ressonância magnética e por tomografia computadorizada. Trata-se de uma abordagem de rastreamento e identificação de bifurcações que difere das técnicas anteriores, utilizando a Transformada de Hough para identificar o diâmetro do vaso em cortes transversais num dado ponto ao longo de um vaso sanguíneo. Mais detalhadamente, essa abordagem utiliza um campo vetorial advindo do cálculo de uma matriz formada por derivadas parciais de segunda ordem, obtida da intensidade luminosa da imagem, para identificar a direção de um ramo de vaso. Além disso, durante o processo de rastreamento de um ramo de vaso, são calculados vários descritores de forma com o objetivo de classificar regiões como pertencentes a uma bifurcação ou não. Em adição a estes descritores, desenvolvemos uma nova medida chamada de variância do raio que permite distinguir, bifurcações, não-bifurcações e segmentos de vaso com stents (aparelho metálico usado para aumentar o diâmetro dos vasos). Para a classificação de bifurcações, criamos a medida de bifurcação, que trata-se de uma combinação linear de todos os descritores de forma apresentados neste trabalho. Testes foram realizados para atestar a eficácia da abordagem proposta, utilizando tanto imagens sintéticas quantoimagens reais. Os resultados mostraram que o método é capaz de rastrear 91% de uma rede vascular sintética variando o ponto de inicialização e 76% variando o nível de ruído. Também foi observado por meio de testes que o método proposto consegue rastrear vasos e identificar bifurcações em imagens reais sem avaliação numérica. Essa abordagem permite a extração da relação hierárquica entre os ramos em uma rede vascular e a extração do padrão de divisão dos vasos, o que contribui sobremaneira para o estudo do comportamento do fenômeno da angiogênese e no auxílio no diagnóstico de anomalias vasculares. / Vascular diseases are a main health problem, representing 28% of deaths worldwide and 66% of all diseases affecting the Brazilian population. Thus, it is important that researches in prevention and treatment of this type of disease increase. Moreover, there are several demands, such as computational tools capable of analyzing and extracting attributes from non-invasive images. The scope of this work is the analysis and extraction of data from magnetic resonance angiography and computed tomography angiography images by highlighting blood vessels. In this context, this thesis aims the development of a novel computational tracking and feature extraction method for vascular networks from 3D images. Our approach presents the following steps: First, identify the vessel cross-sections along it using the Hough transform. Then, compute a matrix composed of second order partial derivatives of image intensity to identify the direction of the vessel. Perform a feature analysis of the vessel contour to classify the bifurcation point, and finally, identify the direction of the new branch in a bifurcation point. The main contribution of this Thesis is the two new measures developed, called radius ratio and bifurcation measure, the radius ratio is capable to distinguish between a region with bifurcation, stents or without both of them. The bifurcation measure is a linear combination that allows to classify a region as bifurcation or not. Tests were performed in order to verify the proposed approach effectiveness, using both synthetic images and real images. The results showed the method is capable to track 91% of synthetic vascular networks varying the seed point and 76% varying the level of noise. Also, we performed tests in real images and by visual evaluation, we could observed that the proposed method was able to track vessels and identify bifurcations from different parts of the body. This approach allows to calculate, in the future, the density of bifurcations in a vascular network, the distance between them, the stenosis and aneurysms grading and characterize specific vessels. In addition, the vascular networks extraction allows the study of the angiogenesis phenomena and vascular anomalies.

It is currently a well-established fact that the dynamics of interacting fluid compartments of the central nervous system (CNS) may play a role in the CNS fluid physiology and pathology of a number of neurological disorders, including neurodegenerative diseases associated with accumulation of waste products in the brain. However, the mechanisms and routes of waste clearance from the brain are still unclear. One of the main components of this interacting cerebral fluids dynamics is blood flow. In the last decades, mathematical modeling and fluid dynamics simulations have become a valuable complementary tool to experimental approaches, contributing to a deeper understanding of the circulatory physiology and pathology. However, modeling blood flow in the brain remains a challenging and demanding task, due to the high complexity of cerebral vascular networks and the difficulties that consequently arise to describe and reproduce the blood flow dynamics in these vascular districts. The first part of this work is devoted to the development of efficient numerical strategies for blood flow simulations in complex vascular networks. In cardiovascular modeling, one-dimensional (1D) and lumped-parameter (0D) models of blood flow are nowadays well-established tools to predict flow patterns, pressure wave propagation and average velocities in vascular networks, with a good balance between accuracy and computational cost. Still, the purely 1D modeling of blood flow in complex and large networks can result in computationally expensive simulations, posing the need for extremely efficient numerical methods and solvers. To address these issues, we develop a novel modeling and computational framework to construct hybrid networks of coupled 1D and 0D vessels and to perform computationally efficient and accurate blood flow simulations in such networks. Starting from a 1D model and a family of nonlinear 0D models for blood flow, with either elastic or viscoelastic tube laws, this methodology is based on (i) suitable coupling equations ensuring conservation principles; (ii) efficient numerical methods and numerical coupling strategies to solve 1D, 0D and hybrid junctions of vessels; (iii) model selection criteria to construct hybrid networks, which provide a good trade-off between accuracy in the predicted results and computational cost of the simulations. By applying the proposed hybrid network solver to very complex and large vascular networks, we show how this methodology becomes crucial to gain computational efficiency when solving networks and models where the heterogeneity of spatial and/or temporal scales is relevant, still ensuring a good level of accuracy in the predicted results. Hence, the proposed hybrid network methodology represents a first step towards a high-performance modeling and computational framework to solve highly complex networks of 1D-0D vessels, where the complexity does not only depend on the anatomical detail by which a network is described, but also on the level at which physiological mechanisms and mechanical characteristics of the cardiovascular system are modeled. Then, in the second part of the thesis, we focus on the modeling and simulation of cerebral blood flow, with emphasis on the venous side. We develop a methodology that, departing from the high-resolution MRI data obtained from a novel in-vivo microvascular imaging technique of the human brain, allows to reconstruct detailed subject-specific cerebral networks of specific vascular districts which are suitable to perform blood flow simulations. First, we extract segmentations of cerebral districts of interest in a way that the arterio-venous separation is addressed and the continuity and connectivity of the vascular structures is ensured. Equipped with these segmentations, we propose an algorithm to extract a network of vessels suitable and good enough, i.e. with the necessary properties, to perform blood flow simulations. Here, we focus on the reconstruction of detailed venous vascular networks, given that the anatomy and patho-physiology of the venous circulation is of great interest from both clinical and modeling points of view. Then, after calibration and parametrization of the MRI-reconstructed venous networks, blood flow simulations are performed to validate the proposed methodology and assess the ability of such networks to predict physiologically reasonable results in the corresponding vascular territories. From the results obtained we conclude that this work represents a proof-of-concept study that demonstrates that it is possible to extract subject-specific cerebral networks from the novel high-resolution MRI data employed, setting the basis towards the definition of an effective processing pipeline for detailed blood flow simulations from subject-specific data, to explore and quantify cerebral blood flow dynamics, with focus on venous blood drainage.