The Virtual Physiological Human: Ten Years After

Biomedical research and clinical practice are struggling to cope with the growing complexity that the progress of health care involves. The most challenging diseases, those with the largest socioeconomic impact (cardiovascular conditions; musculoskeletal conditions; cancer; metabolic, immunity, and neurodegenerative conditions), are all characterized by a complex genotype–phenotype interaction and by a “systemic” nature that poses a challenge to the traditional reductionist approach. In 2005 a small group of researchers discussed how the vision of computational physiology promoted by the Physiome Project could be translated into clinical practice and formally proposed the term Virtual Physiological Human. Our knowledge about these diseases is fragmentary, as it is associated with molecular and cellular processes on the one hand and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us tame the complexity that such systemic behavior involves. In 2005 this was simply not possible—the necessary methods and technologies were not available. Now, 10 years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done

A multi-technique hierarchical X-ray phase-based approach for the characterization and quantification of the effects of novel radiotherapies

Cancer is the first or second leading cause of premature deaths worldwide with an overall rapidly growing burden. Standard cancer therapies include surgery, chemotherapy and radiotherapy (RT) and often a combination of the three is applied to improve the probability of tumour control. Standard therapy protocols have been established for many types of cancers and new approaches are under study especially for treating radio-resistant tumours associated to an overall poor prognosis, as for brain and lung cancers. Follow up techniques able to monitor and investigate the effects of therapies are important for surveying the efficacy of conventionally applied treatments and are key for accessing the curing capabilities and the onset of acute and late adverse effects of new therapies. In this framework, this doctoral Thesis proposes the X-ray Phase Contrast Im-aging - Computed Tomography (XPCI-CT) technique as an imaging-based tool to study and quantify the effects of novel RTs, namely Microbeam and Minibeam Radiation therapy (MRT and MB), and to compare them to the standard Broad Beam (BB) induced effects on brain and lungs. MRT and MB are novel radiotherapies that deliver an array of spatially fractionated X-ray beamlets issued from a synchrotron radiation source, with widths of tens or hundreds of micrometres, respectively. MRT and MB exploit the so-called dose-volume effect: hundreds of Grays are well tolerated by healthy tissues and show a preferential effect on tumour cells and vasculature when delivered in a micrometric sized micro-plane, while induce lethal effects if applied over larger uniform irradiation fields. Such highly collimated X-ray beams need a high-resolution and a full-organ approach that can visualize, with high sensitivity, the effects of the treatment along and outside the beamlets path. XPCI-CT is here suggested and proven as a powerful imaging technique able to determine and quantify the effects of the radiation on normal and tumour-bearing tissues. Moreover, it is shown as an effective technique to complement, with 3D information, the histology findings in the follow-up of the RT treatments. Using a multi-scale and multi-technique X-ray-based approach, I have visualized and analysed the effects of RT delivery on healthy and glioblastoma multiforme (GBM)-bearing rat brains as well as on healthy rat lungs. Ex-vivo XPCI-CT datasets acquired with isotropic voxel sizes in the range 3.253 – 0.653 μm3 could distinguish, with high sensitivity, the idiopathic effects of MRT, MB and BB therapies. Histology, immunohistochemistry, Small- and Wide-Angle X-ray Scattering and X-ray Fluorescence experiments were also carried out to accurately interpret and complement the XPCI-CT findings as well as to obtain a detailed structural and chemical characterization of the detected pathological features. Overall, this multi-technique approach could detect: i) a different radio-sensitivity for the MRT-treated brain areas; ii) Ca and Fe deposits, hydroxyapatite crystals formation; iii) extended and isolated fibrotic contents. Full-organ XPCI-CT datasets allowed for the quantification of tumour and mi-crocalcifications’ volumes in treated brains and the amount of scarring tissue in irradiated lungs. Herein, the role of XPCI-CT as a 3D virtual histology technique for the follow-up of ex-vivo RT effects has been assessed as a complementary method for an accurate volumetric investigation of normal and pathological states in brains and lungs, in a small animal model. Moreover, the technique is proposed as a guidance and auxiliary tool for conventional histology, which is the gold standard for pathological evaluations, owing to its 3D capabilities and the possibility of virtually navigating within samples. This puts a landmark for XPCI-CT inclusion in the pre-clinical studies pipeline and for advancing towards in-vivo XPCI-CT imaging of treated organs.Weltweit gilt Krebs als häufigste bzw. zweithäufigste Ursache eines zu früh erfolgenden Todes, wobei die Zahlen rasch ansteigen. Standardmäßige Krebstherapien umfassen chirurgische Eingriffe, Chemotherapie und Strahlentherapie (radiotherapy, RT); oft kommt eine Kombination daraus zur Anwendung, um die Wahrscheinlichkeit der Tumorkontrolle zu erhöhen. Es wurden Standardtherapieprotokolle für zahlreiche Krebsarten eingerichtet und es wird vor allem in der Behandlung von strahlenresistenten Tumoren mit allgemein schlechter Prognose wie bei Hirn- und Lungentumoren an neuen Ansätzen geforscht. Nachverfolgungstechniken, welche die Auswirkungen von Therapien überwachen und ermitteln, sind zur Überwachung der Wirksamkeit herkömmlich angewandter Behandlungen wichtig und auch maßgeblich am Zugang zu den Fähigkeiten zur Heilung sowie zum Auftreten akuter und verzögerter Nebenwirkungen neuer Therapien beteiligt. In diesem Rahmenwerk unterbreitet diese Doktorarbeit die Technik der Röntgen-Phasenkontrast-Bildgebung über Computertomographie (X-ray Phase Contrast Imaging - Computed Tomography, XPCI‑CT) als bildverarbeitungs-basiertes Tool zur Untersuchung und Quantifizierung der Auswirkungen neuartiger Strahlentherapien, nämlich der Mikrobeam- und Minibeam-Strahlentherapie (MRT und MB), sowie zum Vergleich derselben mit den herkömmlichen durch Breitstrahlen (Broad Beam, BB) erzielten Auswirkungen auf Gehirn und Lunge. MRT und MB sind neuartige Strahlentherapien, die ein Array räumlich aufgeteilter Röntgenstrahlenbeamlets aus einer synchrotronen Strahlenquelle mit einer Breite von Zehnteln bzw. Hundersteln Mikrometern abgeben. MRT und MB nutzen den sogenannten Dosis-Volumen-Effekt: Hunderte Gray werden von gesundem Gewebe gut vertragen und wirken bei der Abgabe in einer Mikroebene im Mikrometerbereich vorrangig auf Tumorzellen und Blutgefäße, während sie bei einer Anwendung über größere gleichförmige Strahlungsfelder letale Auswirkungen aufweisen. Solche hoch kollimierten Röntgenstrahlen erfordern eine hohe Auflösung und einen Zugang zum gesamten Organ, bei dem die Auswirkungen der Behandlung entlang und außerhalb der Beamletpfade mit hoher Empfindlichkeit visualisiert werden können. Hier empfiehlt und bewährt sich die XPCI‑CT als leistungsstarke Bildverarbeitungstechnik, welche die Auswirkungen der Strahlung auf normale und tumortragende Gewebe feststellen und quantifizieren kann. Außerdem hat sich gezeigt, dass sie durch 3‑D-Informationen eine effektive Technik zur Ergänzung der histologischen Erkenntnisse in der Nachverfolgung der Strahlenbehandlung ist. Anhand eines mehrstufigen und multitechnischen röntgenbasierten Ansatzes habe ich die Auswirkungen der Strahlentherapie auf gesunde und von Glioblastomen (GBM) befallene Rattenhirne sowie auf gesunde Rattenlungen visualisiert und analysiert. Mit isotropen Voxelgrößen im Bereich von 3,53 bis 0,653 μm3 erfasste Ex-vivo-XPCI-CT-Datensätze konnten die idiopathischen Auswirkungen der MRT-, MB- und BB‑Behandlung mit hoher Empfindlichkeit unterscheiden. Es wurden auch Experimente zu Histologie, Immunhistochemie, Röntgenklein- und ‑weitwinkelstreuung und Röntgenfluoreszenz durchgeführt, um die XPCI‑CT-Erkenntnisse präzise zu interpretieren und zu ergänzen sowie eine detaillierte strukturelle und chemische Charakterisierung der nachgewiesenen pathologischen Merkmale zu erhalten. Im Allgemeinen wurde durch diesen multitechnischen Ansatz Folgendes ermittelt: i) eine un-terschiedliche Strahlenempfindlichkeit der mit MRT behandelten Gehirnbereiche; ii) Ca- und Fe-Ablagerungen und die Bildung von Hydroxylapatitkristallen; iii) ein ausgedehnter und isolierter Fibrosegehalt. XPCI‑CT-Datensätze des gesamten Organs ermöglichten die Quantifizierung der Volume von Tumoren und Mikroverkalkungen in den behandelten Gehirnen und der Menge des Narbengewebes in bestrahlten Lungen. Dabei wurde die Rolle der XPCI‑CT als virtuelle 3‑D-Histologietechnik für die Nachverfolgung von Ex-vivo-RT‑Auswirkungen als ergänzende Methode für eine präzise volumetrische Untersuchung des normalen und pathologischen Zustands von Gehirnen und Lungen im Kleintiermodell untersucht. Darüber hinaus wird die Technik aufgrund ihrer 3‑D-Fähigkeiten und der Möglichkeit zur virtuellen Navigation in den Proben als Leitfaden und Hilfstool für die herkömmliche Histologie vorgeschlagen, die der Goldstandard für die pathologische Evaluierung ist. Dies markiert einen Meilenstein für die Übernahme der XPCI‑CT in die Pipeline präklinischer Studien und für den Übergang zur In-vivo-XPCI‑CT von behandelten Organen

Morphological characterisation of unstained and intact tissue microarchitecture by x-ray computed micro- and nano-tomography

Characterisation and quantification of tissue structures is limited by sectioning-induced artefacts and by the difficulties of visualising and segmenting 3D volumes. Here we demonstrate that, even in the absence of X-ray contrast agents, X-ray computed microtomography (microCT) and nanotomography (nanoCT) can circumvent these problems by rapidly resolving compositionally discrete 3D tissue regions (such as the collagen-rich adventitia and elastin-rich lamellae in intact rat arteries) which in turn can be segmented due to their different X-ray opacities and morphologies. We then establish, using X-ray tomograms of both unpressurised and pressurised arteries that intra-luminal pressure not only increases lumen cross-sectional area and straightens medial elastic lamellae but also induces profound remodelling of the adventitial layer. Finally we apply microCT to another human organ (skin) to visualise the cell-rich epidermis and extracellular matrix-rich dermis and to show that conventional histological and immunohistochemical staining protocols are compatible with prior X-ray exposure. As a consequence we suggest that microCT could be combined with optical microscopy to characterise the 3D structure and composition of archival paraffin embedded biological materials and of mechanically stressed dynamic tissues such as the heart, lungs and tendons

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included

Multi-Nuclear Magnetic Resonance Imaging of Obstructive Lung Disease

Obstructive lung diseases such as chronic-obstructive-lung-disease (COPD), bronchiectasis, and asthma are characterized by airflow obstruction. They affect over six million Canadians costing the economy $12 billion/year. Despite decades of research, therapies that modify obstructive-lung-disease progression and control are lacking because patient diagnosis, monitoring, and response to therapy are currently made using airflow measurements that may conceal the independent contributions of underlying pathologies. One goal of obstructive-lung-disease research is to develop ways to identify patients with specific underlying pathological phenotypes to improve patient care and outcomes. Thoracic computed-tomography (CT) and magnetic-resonance-imaging (MRI) provide ways to regionally identify the underlying pathologies associated with obstructive-lung-disease, and offer quantitative biomarkers of obstructive-lung-disease (e.g. lung-density, airway dimensions, ventilation abnormalities, and lung microstructure). As the first step to identify patients with specific underlying pathological phenotypes, it is important to understand the physiological and clinical consequences of these imaging derived measurements. Accordingly, our objective was to evaluate lung structure and function using multi-nuclear pulmonary MRI in aging and obstructive-lung-disease to provide a better understanding of MR-derived biomarkers. In older never-smokers, the majority of subjects had 3He MR ventilation abnormalities that were not responsive to bronchodilation. 3He ventilation abnormalities were related to airflow obstruction and airways resistance, but not occupational exposure or exercise limitation. We then developed and evaluated ultra-short-echo-time MRI in COPD subjects with and without bronchiectasis. This work demonstrated that ultra-short-echo-time MR-derived measurements were reproducible and significantly related to CT tissue-density measurements. In the COPD subjects with bronchiectasis, ultra-short-echo-time signal-intensity was related to airway measurements. In COPD subjects without bronchiectasis, ultra-short-echo-time signal-intensity was related to the severity of emphysema. Finally, based on the ultra-short-echo-time MR biomarkers developed in patients with COPD and bronchiectasis, patients that share some of the airway and inflammatory features common in asthmatics, we produced ultra-short-echo-time MR measurements in asthma. These measurements not only provided similar information as CT, but also information about regional ventilation deficits. These results demonstrated that ultra-short-echo-time MR biomarkers may reflect ventilation heterogeneity and/or gas-trapping in asthma. These important findings indicate that multi-nuclear pulmonary MRI has the potential to quantitatively evaluate the different pathologies of obstructive-lung-disease

Análise funcional do ventrículo esquerdo em angio-TC coronária

Doutoramento em Engenharia InformáticaCoronary CT angiography is widely used in clinical practice for the assessment of coronary artery disease. Several studies have shown that the same exam can also be used to assess left ventricle (LV) function. LV function is usually evaluated using just the data from end-systolic and end-diastolic phases even though coronary CT angiography (CTA) provides data concerning multiple cardiac phases, along the cardiac cycle. This unused wealth of data, mostly due to its complexity and the lack of proper tools, has still to be explored in order to assess if further insight is possible regarding regional LV functional analysis. Furthermore, different parameters can be computed to characterize LV function and while some are well known by clinicians others still need to be evaluated concerning their value in clinical scenarios. The work presented in this thesis covers two steps towards extended use of CTA data: LV segmentation and functional analysis. A new semi-automatic segmentation method is presented to obtain LV data for all cardiac phases available in a CTA exam and a 3D editing tool was designed to allow users to fine tune the segmentations. Regarding segmentation evaluation, a methodology is proposed in order to help choose the similarity metrics to be used to compare segmentations. This methodology allows the detection of redundant measures that can be discarded. The evaluation was performed with the help of three experienced radiographers yielding low intraand inter-observer variability. In order to allow exploring the segmented data, several parameters characterizing global and regional LV function are computed for the available cardiac phases. The data thus obtained is shown using a set of visualizations allowing synchronized visual exploration. The main purpose is to provide means for clinicians to explore the data and gather insight over their meaning, as well as their correlation with each other and with diagnosis outcomes. Finally, an interactive method is proposed to help clinicians assess myocardial perfusion by providing automatic assignment of lesions, detected by clinicians, to a myocardial segment. This new approach has obtained positive feedback from clinicians and is not only an improvement over their current assessment method but also an important first step towards systematic validation of automatic myocardial perfusion assessment measures.A angiografia coronária por TC (angio-TC) é prática clínica corrente para a avaliação de doença coronária. Alguns estudos mostram que é também possível utilizar o exame de angio-TC para avaliar a função do ventrículo esquerdo (VE). A função ventricular esquerda (FVE) é normalmente avaliada considerando as fases de fim de sístole e de fim de diástole, apesar de a angio-TC proporcionar dados relativos a diferentes fases distribuídas ao longo do ciclo cardíaco. Estes dados não considerados, devido à sua complexidade e à falta de ferramentas apropriadas para o efeito, têm ainda de ser explorados para que se perceba se possibilitam uma melhor compreensão da FVE. Para além disso, podem ser calculados diferentes parâmetros para caracterizar a FVE e, enquanto alguns são bem conhecidos dos médicos, outros requerem ainda uma avaliação do seu valor clínico. No âmbito de uma utilização alargada dos dados proporcionados pelos angio- TC, este trabalho apresenta contributos ao nível da segmentação do VE e da sua análise funcional. É proposto um método semi-automático para a segmentação do VE de forma a obter dados para as diferentes fases cardíacas presentes no exame de angio- TC. Foi também desenvolvida uma ferramenta de edição 3D que permite aos utilizadores a correcção das segmentações assim obtidas. Para a avaliação do método de segmentação apresentado foi proposta uma metodologia que permite a detecção de medidas de similaridade redundantes, a usar no âmbito da avaliação para comparação entre segmentações, para que tais medidas redundantes possam ser descartadas. A avaliação foi executada com a colaboração de três técnicos de radiologia experientes, tendo-se verificado uma baixa variabilidade intra- e inter-observador. De forma a permitir explorar os dados segmentados, foram calculados vários parâmetros para caracterização global e regional da FVE, para as diversas fases cardíacas disponíveis. Os resultados assim obtidos são apresentados usando um conjunto de visualizações que permitem uma exploração visual sincronizada dos mesmos. O principal objectivo é proporcionar ao médico a exploração dos resultados obtidos para os diferentes parâmetros, de modo a que este tenha uma compreensão acrescida sobre o seu significado clínico, assim como sobre a correlação existente entre diferentes parâmetros e entre estes e o diagnóstico. Finalmente, foi proposto um método interactivo para ajudar os médicos durante a avaliação da perfusão do miocárdio, que atribui automaticamente as lesões detectadas pelo médico ao respectivo segmento do miocárdio. Este novo método obteve uma boa receptividade e constitui não só uma melhoria em relação ao método tradicional mas é também um primeiro passo para a validação sistemática de medidas automáticas da perfusão do miocárdio

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

Decoding Neural Signals with Computational Models: A Systematic Review of Invasive BMI

There are significant milestones in modern human's civilization in which mankind stepped into a different level of life with a new spectrum of possibilities and comfort. From fire-lighting technology and wheeled wagons to writing, electricity and the Internet, each one changed our lives dramatically. In this paper, we take a deep look into the invasive Brain Machine Interface (BMI), an ambitious and cutting-edge technology which has the potential to be another important milestone in human civilization. Not only beneficial for patients with severe medical conditions, the invasive BMI technology can significantly impact different technologies and almost every aspect of human's life. We review the biological and engineering concepts that underpin the implementation of BMI applications. There are various essential techniques that are necessary for making invasive BMI applications a reality. We review these through providing an analysis of (i) possible applications of invasive BMI technology, (ii) the methods and devices for detecting and decoding brain signals, as well as (iii) possible options for stimulating signals into human's brain. Finally, we discuss the challenges and opportunities of invasive BMI for further development in the area.Comment: 51 pages, 14 figures, review articl