Design and Assembly Considerations in the Engineering of Vascular Tissue

Native vascular tissue functions are highly dependent on structural organization at the super-cellular, cellular, and sub-cellular spatial scales. We hypothesized that the structure-function relationship of vascular tissues in vivo can be leveraged to engineer vascular tissues in vitro by prescribing the shape of constituent cells and their assembly into organized three-dimensional structures. To this end, we first asked if vascular smooth muscle cell shape influences cellular contractility. We engineered human vascular smooth muscle cells to assume similar shapes to those in elastic and muscular arteries and then measured their contraction while stimulating with endothelin-1. We found that vascular smooth muscle cells with elongated shapes exhibited lower contractile strength but a greater percentage increase in contraction after endothelin-1 stimulation, suggesting that elongated vascular smooth muscle cell shape endows the muscular artery with greater dynamic contractile range. Next, we sought to assemble cells into tissues by employing a three-dimensional cellular patterning strategy based on the folding of porous, thin polymer films. We assembled different three-dimensional endothelial and vascular smooth muscle organizations by patterning two-dimensional poly(lactic-co-glycolic) acid and collagen thin films with cell suspensions at prescribed locations. The films were subsequently folded following Miura-ori geometry guidelines and the matrices were embedded subcutaneously in immunodeficient mice in order to assess the vascularization of the implanted constructs. We found that spatial organization that allowed endothelial and vascular smooth muscle cells to interact adjacent to each other laterally in the same folding plane created the densest vascularized network, suggesting that three-dimensional structural organization of vascular cells can influence the formation of vascularized networks. Taken together, our result shows that functional vascular tissues in vitro can be engineered by encoding structure cues in their design and assembly.Engineering and Applied Science

Sarc-Graph: automated segmentation, tracking, and analysis of sarcomeres in hiPSC-derived cardiomyocytes

A better fundamental understanding of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) has the potential to advance applications ranging from drug discovery to cardiac repair. Automated quantitative analysis of beating hiPSC-CMs is an important and fast developing component of the hiPSC-CM research pipeline. Here we introduce "Sarc-Graph," a computational framework to segment, track, and analyze sarcomeres in fluorescently tagged hiPSC-CMs. Our framework includes functions to segment z-discs and sarcomeres, track z-discs and sarcomeres in beating cells, and perform automated spatiotemporal analysis and data visualization. In addition to reporting good performance for sarcomere segmentation and tracking with little to no parameter tuning and a short runtime, we introduce two novel analysis approaches. First, we construct spatial graphs where z-discs correspond to nodes and sarcomeres correspond to edges. This makes measuring the network distance between each sarcomere (i.e., the number of connecting sarcomeres separating each sarcomere pair) straightforward. Second, we treat tracked and segmented components as fiducial markers and use them to compute the approximate deformation gradient of the entire tracked population. This represents a new quantitative descriptor of hiPSC-CM function. We showcase and validate our approach with both synthetic and experimental movies of beating hiPSC-CMs. By publishing Sarc-Graph, we aim to make automated quantitative analysis of hiPSC-CM behavior more accessible to the broader research community.https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009443Published versio

Mapping microstructural dynamics in a mouse stroke model using advanced diffusion MRI

Tese de mestrado integrado em Engenharia Biomédica e Biofísica (Sinais e Imagens Médicas), Universidade de Lisboa, Faculdade de Ciências, 2020O acidente vascular cerebral (AVC) corresponde a uma das principais causas de morte e invalidez a nível mundial, sendo o AVC isquémico o mais predominante, perfazendo mais de 80% dos casos. Este traduz-se no bloqueio de um ou mais vasos sanguíneos devido à formação de coágulos, comprometendo a oxigenação no local e o fornecimento de nutrientes como consequência da redução do fluxo sanguíneo. O único tratamento aceite para o AVC baseia-se na administração de agentes trombolíticos. Porém, a sua aplicabilidade é muito reduzida pois o intervalo de tempo exigido para a sua atuação é demasiado curto (menos de 4 horas desde a última vez em que o sujeito se apresentou assintomático). De momento, o desenvolvimento de técnicas inovadoras encontra-se dependente de um conhecimento mais aprofundado do tecido envolvente no decorrer do acidente isquémico. Posto tal, as técnicas de neuroimagiologia de cariz não invasivo, como a imagem por ressonância magnética (IRM), apresentam um papel crucial na investigação nesta área. A importância da ressonância magnética de difusão (dMRI, do inglês diffusion MRI) tem vindo a ser cada vez mais favorecida, especialmente na deteção do enfarte e no estudo do microambiente na zona respetiva. Contudo, as métricas convencionais de dMRI apenas disponibilizam informação relativa, no máximo, a um sumatório de efeitos não Gaussianos da difusão da água nos tecidos, o que a torna numa técnica consideravelmente inespecífica. Esta falta de especificidade pode então refletir-se numa incorreta caraterização do núcleo da lesão, de tecido recuperável e da resposta ao tratamento, no sentido em que os mecanismos subjacentes ao contraste de dMRI obtido são desconhecidos. No âmbito deste trabalho, de forma a aumentar a sensibilidade e especificidade da dMRI na informação obtida em contexto de AVC isquémico, a metodologia de imagem por contraste do tensor de correlação (CTI, do inglês Correlation Tensor Imaging), desenvolvida no nosso laboratório, foi aplicada num modelo de AVC isquémico em murganho (Mus musculus). A CTI permite a obtenção de informações mais específicas acerca de efeitos de difusão provenientes das fontes de curtose (relativos a anisotropia, dispersão na orientação, variância na difusão nos tecidos e propriedades não Gaussianas). Esta técnica baseia-se na expansão cumulativa do sinal adquirido em sequências avançadas de codificação de difusão dupla (DDE, do inglês Double Diffusion Encoding), em que ambas as codificações podem ser aplicadas em direções e magnitudes independentes (caraterizadas por vetores independentes q1 e q2). Todos os procedimentos em animais foram previamente aprovados pelas autoridades nacionais e internacionais competentes, e foram realizados de acordo com a Diretiva EU 2010/63. Murganhos macho C57BL/6J (N = 12; 26,4 ± 6,5 g) com 11 semanas foram utilizados. O modelo fototrombótico de Rose Bengal foi usado de forma a induzir um enfarte focalizado na região do cortéx de barril com uma solução de um corante fotossensível (15 mg/ml). Em animais do grupo experimental (N = 5), a solução foi administrada de forma intravenosa (10 μl/g peso do animal) e a zona cortical de interesse foi irradiada com uma fonte de luz fria durante 15 minutos. Os animais do grupo de controlo (N = 5) foram submetidos a procedimentos idênticos, à exceção da irradiação responsável pelo desencadeamento da lesão, mantendo o tempo de espera suposto. Os cérebros do grupo de AVC e do grupo de controlo foram perfundidos 3 h após o fim do período com ou sem iluminação e utilizados para aquisições ex vivo. Além disso, dois animais foram usados para examinação in vivo: um submetido à indução do AVC para validação com os resultados ex vivo, e outro animal saudável foi usado para efeitos corroborativos com estudos anteriores. Os cérebros foram examinados no scanner Aeon da Bruker de 16.4 T. As imagens por difusão ex vivo foram adquiridas com sequências de DDE com base em EPI (do inglês Echo Planar Imaging) escritas in house. Usou-se um protocolo com um total de 5 combinações q1-q2 de magnitudes diferentes (1498,0 – 0; 1059,2 – 1059,2; 1059,2 – 0; 749,0 – 749,0 e 749,0 - 0 mT/m), associando cada combinação a uma aquisição. Para combinações em que as magnitudes eram iguais entre vetores, foram usadas 135 direções paralelas e perpendiculares, resultando em 7 aquisições com valor b total de 750, 1500 ou 3000 mm/s2 . Os restantes parâmetros foram: TR/TE = 3000/49 ms, FOV = 11 × 11 mm2 , matriz = 78 × 78, resolução de voxel no plano de 141 × 141 μm2 , 25 fatias coronais com espessura de 0,5 mm, δ/Δ/τm = 1,5/10/10 ms e 2 segmentos. 20 imagens foram adquiridas sem gradientes de difusão aplicados (i.e., b = 0 mm/s2 ). Cada examinação durou aproximadamente 14 h na totalidade. No caso das aquisições in vivo, os animais foram sedados (isoflurano 2,5%) e examinados no scanner Biospec da Bruker de 9.4 T. As imagens por difusão foram adquiridas com um protocolo otimizado em comparação com o utilizado nas sequências ex vivo, diferindo nos seguintes parâmetros: as combinações q1-q2 de magnitude foram de 518,79 – 0; 366,84 – 366,84; 366,84 – 0; 259,4 – 259,4 e 259,4 - 0 mT/m. As combinações de direções foram idênticas às utilizadas nas aquisições ex vivo, resultando também em 7 aquisições com valor b total de 625, 1250 ou 1500 mm/s2 , TR/TE = 2800/44,5 ms, FOV = 12 × 12 mm2 , matriz = 78 × 78, resolução de voxel no plano de 181 × 181 μm2 , 5 fatias coronais com espessura de 0,85 mm, δ/Δ/τm = 4/10/10 ms e 1 segmento. Cada examinação durou aproximadamente 1 h e 15 min. O processamento dos dados englobou a correção do sinal ao nível do ruído, alinhamento dos dados e correção ao nível de Gibbs ringing. As métricas de difusão convencionais, tais como a difusão média, a anisotropia fracional, a difusão radial e axial (MD, FA, RD e AD, respetivamente) foram extraídas pelo tensor de difusão (D). No âmbito das fontes resolvidas pela CTI, a fonte de curtose excedente total (KT) foi obtida a partir de D e do tensor de curtose (W), as curtoses anisotrópica e isotrópica ( e ), ditas fontes intercompartimentais, foram extraídas a partir do tensor D e do tensor de correlação do deslocamento Z (de quarta ordem na expansão cumulativa), e a fonte de curtose intracompartimental () foi extraída a partir da subtração das fontes intercompartimentais à fonte KT. De forma a analisar os mapas obtidos para as métricas de curtose 3 h após enfarte ao nível de substância branca e cinzenta, regiões de interesse foram definidas (com base nos mapas de MD e FA) no hemisfério ipsilateral ou ipsilesional (relativo à lesão), e no hemisfério contralateral (não afetado), dos animais que sofreram o AVC. Regiões de interesse no grupo de controlo foram também definidas no hemisfério ipsilateral. Após associar os dados obtidos de cada hemisfério a diferentes subgrupos, foram realizadas comparações entre subgrupos para as diferentes métricas de curtose e uma análise ANOVA para testar diferenças significativas entre subgrupos, permitindo assim uma análise de especificidade de cada métrica aos efeitos do AVC. Foi ainda realizada uma análise da sensibilidade de cada métrica perante a lesão no hemisfério ipsilesional para todos os animais do grupo de AVC através da quantificação de voxeis sensíveis à lesão em cada animal, quer ao nível da lesão total, quer ao nível das substâncias branca e cinzenta. Uma breve análise histológica foi produzida para uma comparação qualitativa com os mapas das diferentes fontes de curtose e associação com degeneração e perda celular. Os resultados indicaram diferenças significativas (p < 0,05) para as métricas KT e entre o hemisfério ipsilateral do grupo de AVC e o hemisfério contralateral do mesmo grupo, bem como entre o hemisfério ipsilaterial do grupo de AVC e o hemisfério ipsilateral do grupo de controlo (em substância substância cinzenta e substância branca). Porém, a métrica de foi a que mais se destacou, visto ter mostrado sensibilidade para o AVC na substância cinzenta perante outras métricas. Os mapas de curtose in vivo mostraram-se consistentes com os mapas ex vivo. Em comparação com estudos anteriores, os resultados obtidos nas métricas de difusão (MD, FA, RD e AD) demonstraram congruência com a literatura, tendo os valores de KT seguido a tendência dos valores de curtose média (MK) obtidos noutros estudos de AVC em murganho. A menor sensibilidade para o AVC em KT, quando comparada com , por exemplo, sugere que certos efeitos de curtose se poderão anular, informação essa anteriormente desconhecida. Os nossos resultados, além de favorecerem maior sensibilidade comparativamente às métricas convencionais em contexto de AVC, acentuam também a especificidade de cada fonte de curtose perante o tecido isquémico, permitindo uma possível relação com mecanismos patofisiológicos a ocorrer na fase aguda-subaguda do AVC, tais como fenómenos citotóxicos e vasogénicos. Ao resolver as fontes de curtose em tecido isquémico, foi-nos possibilitada uma maior compreensão dos mecanismos microscópicos subjacentes, que, num formato mais sensível e específico, propicia uma caraterização de AVC inovadora e uma maior eficácia no tratamento associado.Stroke is a leading cause of long-term disability and death worldwide, with ischaemic infarct accounting for approximately 80% of all cases. Currently, novel treatments depend on a deeper understanding of the local tissue milieu following ischemia. Therefore, non-invasive neuroimaging plays a crucial role in stroke research. Diffusion MRI (dMRI) is one of the most reliable imaging techniques, mainly for the early detection of ischemic stroke via detection of microstructural changes. However, dMRI is critically unspecific, thereby hampering the conclusive characterization of infarct core, salvageable tissue and response to treatment. To overcome this drawback, Correlation Tensor Imaging (CTI) – a ground-breaking approach enhancing sensitivity and specificity towards tissue microstructure via the resolution of non-Gaussian diffusion sources – was applied for the first time towards the characterization of ischemic tissue (ex vivo and in vivo) and assessment of the mechanisms underlying dMRI contrasts in a mouse stroke model at an early stage post ischemic insult. In this study, a photothrombotic stroke model was used to induce a focal infarct in the barrel cortex and dMRI ex vivo datasets were acquired with CTI pulse sequences written in house. For corroboration of results, in vivo datasets were additionally acquired. The stroke model reproducibly induced well-delimited infarction cores in the targeted region in all animals. Our results suggest that CTI is capable of resolving microscopic features of ischemic tissue in-vivo, which until now were obfuscated or conflated in conventional dMRI measurements. Particularly, intra-compartmental kurtosis (), one of the resolved sources, shows higher sensitivity and specificity towards ischemic alterations when compared to other sources of kurtosis. These are critical first steps towards resolving the contributions of cytotoxic and vasogenic edema sources as well as potential for revealing salvageable tissue or ongoing excitotoxicity

Computational Approaches to Understanding Structure-Function Relationships at the Intersection of Cellular Organization, Mechanics, and Electrophysiology

The heart is a complex mechanical and electrical environment and small changes at the cellular and subcellular scale can have profound impacts at the tissue, organ, and organ system levels. The goal of this research is to better understand structure-function relationships at these cellular and subcellular levels of the cardiac environment. This improved understanding may prove increasingly important as medicine begins shifting toward engineered replacement tissues and organs. Specifically, we work towards this goal by presenting a framework to automatically create finite element models of cells based on optical images. This framework can be customized to model the effects of subcellular structure and organization on mechanical and electrophysiological properties at the cellular level and has the potential for extension to the tissue level and beyond. In part one of this work, we present a novel algorithm is presented that can generate physiologically relevant distributions of myofibrils within adult cardiomyocytes from confocal microscopy images. This is achieved by modelling these distributions as directed acyclic graphs, assigning a cost to each node based on observations of cardiac structure and function, and determining to minimum-cost flow through the network. This resulting flow represents the optimal distribution of myofibrils within the cell. In part two, these generated geometries are used as inputs to a finite element model (FEM) to determine the role the myofibrillar organization plays in the axal and transverse mechanics of the whole cell. The cardiomyocytes are modeled as a composite of fiber trusses within an elastic solid matrix. The behavior of the model is validated by comparison to data from combined Atomic Force Microscopy (AFM) and Carbon Fiber manipulation. Recommendations for extending the FEM framework are also explored. A secondary goal, discussed in part three of this work, is to make computational models and simulation tools more accessible to novice learners. Doing so allows active learning of complicated course materials to take place. Working towards this goal, we present CellSpark: a simulation tool developed for teaching cellular electrophysiology and modelling to undergraduate bioengineering students. We discuss the details of its implementation and implications for improved student learning outcomes when used as part of a discovery learning assignment

A multiscale biophysical platform for charting design-specific interactions of nanoparticles with model cellular membranes

In this thesis, we outline the development of a multiscale physics-based platform for exploring and ultimately predicting the design-specific interaction of ~1-10 nm particles with model cellular membranes. Nanoparticles (NP) are ever-present in foods and beverages, cosmetics, packaging, cooking products, fertilizers, pesticides, and novel pharmaceuticals, and pose significant challenges related to their increased consumer, occupational, and environmental exposure and their unique bioactivity relative to small molecules and large colloids. Thanks to rapidly advancing fabrication and characterization techniques, NPs are highly tunable in physicochemical properties such as size, surface chemistry, shape, elasticity, roughness, and crystallinity. Currently, however, the influence of these NP design parameters is highly underdeveloped, and difficult to reproducibly demonstrate in in vivo, in vitro, and even model experiments. Specifically, NP interactions with and passive transport across cellular membranes play a significant role in pharmacological and consumer product performance (biodistribution) as well as adverse outcome pathways in toxicology. We thus focus on the fundamental problem of design-specific interactions between NPs and cellular membranes, modeled to a first approximation as lipid bilayers.To provide accurate, efficient, and robust predictions for a range of NP designs, we construct a first-of-its kind, multiscale physics-based platform linking detailed molecular dynamics (MD) simulations, continuum mechanical theory, and multi-compartment modeling. Using this platform, we examine the two most influential design parameters--size and surface chemistry--and through two main case studies: (1) the membrane permeability of sub-nanometer particles and (2) the thermodynamic stability of larger-scale, ~1-10 nm particle-membrane interactions. Within (1), we first simulate the NP-membrane interactions and transport in full detail to test the validity of Overton's Rule, a longstanding structure-property relationship, and the inhomogeneous solubility-diffusion (ISD) model, a microscopic mechanistic continuum model for transport. We show that Overton's Rule is overly simplified for describing transport across a fluctuating lipid bilayer membrane, yet that ISD model holds for small enough particles. Within this range of particles where the solubility-diffusion mechanism holds, we directly link the impact of particle chemistry in the MD simulations to transient (time-dependent) transport outcomes in the macroscopic multi-compartmental models. This allows us to both compare with and evaluate models used in experimental permeability assays and close the orders of magnitude gap between simulation-predicted and experimentally-calculated permeabilities. We also leverage our platform to construct improved structure-property relationships for the steady-state membrane permeability and structure-kinetic relationships, accounting for a wider range of particle chemistries and highlighting the imperative of time in dictating the design rules for membrane permeation.Within case study (2), we probe larger NP-membrane interactions that implicate macroscopic membrane deformations and restructuring. Using the molecular simulations, we map out in particle size and chemistry space the putative NP-membrane interaction configurations, some of which resemble and agree with small-scale solubility-diffusion theory or large-scale membrane elastic theory (e.g. for lipid bilayer or monolayer wrapping of the NP) in stability limits and free energies and some of which require closer examination in the simulation to explain the thermodynamics. We also discover an entirely novel mechanism of interaction for ~4 nm, rough crystalline hydrophobic particles that we call "asymmetric leaflet hopping," wherein the particle preferentially inserts in one bilayer leaflet, forming a pre-pore in the membrane and inducing large-scale membrane curvature, and flips to the other leaflet over extended time scales.We conclude with preliminary phenomenologies to outline the phase behavior of ~1-10 nm particles of varying chemistry, as well as other areas where our platform shows great promise. By accounting for a vast range of NP designs, natural lipid diversity (lipidomics), and variable compartmental size, boundary layer, and transient conditions, this platform has the potential to more intuitively and effectively inform systems-level physiologically-based pharmacokinetic models for NP biodistribution predictions, as well as structure-activity relationships for direct predictions of product efficacy and toxicity. The end result of this multiscale platform is that we can directly link a NP's microscopic physicochemical properties to its macroscopic outcomes in a dynamic biodistribution setting

Convex Relaxations for Particle-Gradient Flow with Applications in Super-Resolution Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) techniques have become advanced bioanalytical tools by quantifying the positions and orientations of molecules in space and time at the nanoscale. With the noisy and heterogeneous nature of SMLM datasets in mind, we discuss leveraging particle-gradient flow 1) for quantifying the accuracy of localization algorithms with and without ground truth and 2) as a basis for novel, model-driven localization algorithms with empirically robust performance. Using experimental data, we demonstrate that overlapping images of molecules, a typical consequence of densely packed biological structures, cause biases in position estimates and reconstruction artifacts. To minimize such biases, we develop a novel sparse deconvolution algorithm by relaxing a particle-gradient flow algorithm (called relaxed-gradient flow or RGF). In contrast to previous methods based on sequential source matching or grid-based strategies, RGF detects source molecules based on the estimated “gradient flux.” RGF reconstructs experimental images of microtubules with much greater accuracy in terms of separation and diameter. We further extend RGF to the problem of joint estimation of molecular position and orientation. By lifting the optimization from first-order to second-order orientational moments, we derive an efficient version of RGF, which exhibits robustness to instrumental mismatches. Finally, we discuss the fundamental problem of quantifying the accuracy of a localization estimate without ground truth. We show that by computing measurement stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly quantify the confidence of individual localizations without ground-truth knowledge of the sample. To demonstrate the broad applicability of our method, termed Wasserstein-induced flux, we measure the accuracy of various reconstruction algorithms directly on experimental data

Spinal cord diffusion imaging: Challenging characterization and prognostic value

The aim of this thesis is to explore the potential of quantitative imaging mark¬ers derived from diffusion-weighted MRI (DW MRI) in the spinal cord to char¬acterise healthy white matter pathways and provide sensitivity to axonal dam¬age, regeneration and collateral sprouting in spinal cord disease. With new innovative treatment strategies emerging for spinal cord patholo¬gies such as spinal cord injury and Multiple Sclerosis, there is a need for new in-vivo biomarkers that can be specific to structural and functional changes and their underlying mechanisms on a microscopic scale. DW MRI has the potential to quantifying those microstructural characteristics beyond the scale of conventional MRI. In the first part of this dissertation I investigate Diffusion Tensor Imaging (DTI), which is the most established DW MRI analysis technique in clinical practice. In two studies we assess DTI in the context of spinal cord imaging. In the first experiment I show that DTI is sensitive to the presence of collateral fi¬bres, e.g., at inter-vertebral level where peripheral nerves enter the spinal tract. In the second experiment I propose a new method for reducing partial volume effects on whole cord DTI measurements, which is specifically tailored for the imaging and analysis challenges in the cord. The second part of this thesis comprises two studies of q-space imaging (QSI) in healthy controls. In theory, QSI offers a more comprehensive descrip¬tion of the diffusion process, but is challenging to set up on a clinical MRI scanner. I present here two QSI protocols, set up for two different scanners with different gradient hardware, receive coils and software limitations. For the first time we perform a systematic study of QSI that assesses the reproducibility and specificity to different white pathways in-vivo in the cervical cord within a group of healthy volunteers. Both studies show superior reproducibility of QSI over conventional analysis, although the results of using QSI parameters to distinguish individual white matter tracts in the cord were inconclusive. The third part of this thesis describes a new imaging method protocol based on the ActiveAx optimisation framework. It uses a complex multi- compartment model, which relates DW MRI data to microstructural parame¬ters like axon diameter and density. I design a new orientation aware method based ActiveAx, which incorporates the known fibre structure of the spinal cord. In a first step I validate the approach in in a post-mortem cervical spinal cord sample of a velveteen monkey. I then demonstrate clinical feasibility and good reproducibility of the new protocol for in-vivo human studies, using the corpus callosum as a preliminary model system for structures with uni¬directional fibre architecture. Finally I present first estimation results of axon diameter and density of the cervical spinal cord in-vivo in a healthy control that agree with the findings in the ex-vivo monkey spinal cord sample

Machine learning-based automated segmentation with a feedback loop for 3D synchrotron micro-CT

Die Entwicklung von Synchrotronlichtquellen der dritten Generation hat die Grundlage für die Untersuchung der 3D-Struktur opaker Proben mit einer Auflösung im Mikrometerbereich und höher geschaffen. Dies führte zur Entwicklung der Röntgen-Synchrotron-Mikro-Computertomographie, welche die Schaffung von Bildgebungseinrichtungen zur Untersuchung von Proben verschiedenster Art förderte, z.B. von Modellorganismen, um die Physiologie komplexer lebender Systeme besser zu verstehen. Die Entwicklung moderner Steuerungssysteme und Robotik ermöglichte die vollständige Automatisierung der Röntgenbildgebungsexperimente und die Kalibrierung der Parameter des Versuchsaufbaus während des Betriebs. Die Weiterentwicklung der digitalen Detektorsysteme führte zu Verbesserungen der Auflösung, des Dynamikbereichs, der Empfindlichkeit und anderer wesentlicher Eigenschaften. Diese Verbesserungen führten zu einer beträchtlichen Steigerung des Durchsatzes des Bildgebungsprozesses, aber auf der anderen Seite begannen die Experimente eine wesentlich größere Datenmenge von bis zu Dutzenden von Terabyte zu generieren, welche anschließend manuell verarbeitet wurden. Somit ebneten diese technischen Fortschritte den Weg für die Durchführung effizienterer Hochdurchsatzexperimente zur Untersuchung einer großen Anzahl von Proben, welche Datensätze von besserer Qualität produzierten. In der wissenschaftlichen Gemeinschaft besteht daher ein hoher Bedarf an einem effizienten, automatisierten Workflow für die Röntgendatenanalyse, welcher eine solche Datenlast bewältigen und wertvolle Erkenntnisse für die Fachexperten liefern kann. Die bestehenden Lösungen für einen solchen Workflow sind nicht direkt auf Hochdurchsatzexperimente anwendbar, da sie für Ad-hoc-Szenarien im Bereich der medizinischen Bildgebung entwickelt wurden. Daher sind sie nicht für Hochdurchsatzdatenströme optimiert und auch nicht in der Lage, die hierarchische Beschaffenheit von Proben zu nutzen. Die wichtigsten Beiträge der vorliegenden Arbeit sind ein neuer automatisierter Analyse-Workflow, der für die effiziente Verarbeitung heterogener Röntgendatensätze hierarchischer Natur geeignet ist. Der entwickelte Workflow basiert auf verbesserten Methoden zur Datenvorverarbeitung, Registrierung, Lokalisierung und Segmentierung. Jede Phase eines Arbeitsablaufs, die eine Trainingsphase beinhaltet, kann automatisch feinabgestimmt werden, um die besten Hyperparameter für den spezifischen Datensatz zu finden. Für die Analyse von Faserstrukturen in Proben wurde eine neue, hochgradig parallelisierbare 3D-Orientierungsanalysemethode entwickelt, die auf einem neuartigen Konzept der emittierenden Strahlen basiert und eine präzisere morphologische Analyse ermöglicht. Alle entwickelten Methoden wurden gründlich an synthetischen Datensätzen validiert, um ihre Anwendbarkeit unter verschiedenen Abbildungsbedingungen quantitativ zu bewerten. Es wurde gezeigt, dass der Workflow in der Lage ist, eine Reihe von Datensätzen ähnlicher Art zu verarbeiten. Darüber hinaus werden die effizienten CPU/GPU-Implementierungen des entwickelten Workflows und der Methoden vorgestellt und der Gemeinschaft als Module für die Sprache Python zur Verfügung gestellt. Der entwickelte automatisierte Analyse-Workflow wurde erfolgreich für Mikro-CT-Datensätze angewandt, die in Hochdurchsatzröntgenexperimenten im Bereich der Entwicklungsbiologie und Materialwissenschaft gewonnen wurden. Insbesondere wurde dieser Arbeitsablauf für die Analyse der Medaka-Fisch-Datensätze angewandt, was eine automatisierte Segmentierung und anschließende morphologische Analyse von Gehirn, Leber, Kopfnephronen und Herz ermöglichte. Darüber hinaus wurde die entwickelte Methode der 3D-Orientierungsanalyse bei der morphologischen Analyse von Polymergerüst-Datensätzen eingesetzt, um einen Herstellungsprozess in Richtung wünschenswerter Eigenschaften zu lenken

Life Sciences Program Tasks and Bibliography for FY 1997

This document includes information on all peer reviewed projects funded by the Office of Life and Microgravity Sciences and Applications, Life Sciences Division during fiscal year 1997. This document will be published annually and made available to scientists in the space life sciences field both as a hard copy and as an interactive internet web page