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Das adaptive Immunsystem schützt den Menschen vor extra- wie auch intrakorporal auftretenden Pathogenen und Krebszellen. Die Funktionalität dieses Prozesses geht hierbei auf die Interaktion und Kooperation einer Vielzahl verschiedener Zelltypen des Körpers zurück und ist vorwiegend innerhalb der Lymphknoten lokalisiert. Ist auch nur ein Bestandteil dieses sensiblen Prozesses gestört, kann dies zu einem teilweisen oder vollständigen Verlust der immunologischen Fitness des Menschen führen. Daher war es das Ziel dieser Arbeit, solche Aberrationen des humanen Lymphknotengewebes umfassend digital-pathologisch zu detektieren und zu definieren. Hierfür wurde zunächst eine digitale Gewebedatenbank etabliert. Diese basiert auf dem im Rahmen dieser Arbeit implementierten Content-Management-System Digital Tissue Management Suite. Weiterhin wurde die Software Feature analysis in tissue histomorphometry entwickelt, welche die Analyse von zweidimensionalen whole slide images ermöglicht. Hierbei werden Methoden aus dem Bereich Computer Vision und Graphentheorie eingesetzt, um morphologische und distributionale Eigenschaften der Zelltypen des Lymphknotens zu charakterisieren. Darüber hinaus enthält diese Software Plug-ins zur Visualisierung und statistischen Analyse der Daten. Aufbauend auf der eigens implementierten, digitalen Infrastruktur, in Kombination mit der Software Imaris wurden zweidimensional und dreidimensional gescannte, reaktive und neoplastische Gewebeproben digital phänotypisiert. Hierbei konnten neue mechanische Barrieren zur Kompartimentalisierung der Keimzentren aufgeklärt werden. Weiterhin konnte der Erhalt des quantitativen Verhältnisses einzelner Zellpopulationen innerhalb der Keimzentren beschrieben werden. Ausgehend von den reaktiven Phänotypen des Lymphknotens, wurden pathophysiologische Aberrationen in verschiedenen lymphatischen Neoplasien untersucht. Hierbei konnte gezeigt werden, dass speziell die strukturelle Destruktion häufig mit einer morphologische, The adaptive immune system defends humans’ from extra- and intracorporeally occurring pathogens and cancer cells. This process is based on the interaction and cooperation of diverse cell populations within lymph nodes. If even one component of this sensitive process is disturbed, a partial or complete loss of immunological fitness in humans can be found. To recognize and understand such disturbances at an early stage, this work aimed to detect and define new digital biomarkers for benign and malignant aberrations of human lymph nodes. For this purpose, a digital biobank was established. For the management of this biobank a new content management system named Digital Tissue Management Suite was developed. In addition, the digital pathology software Feature analysis in tissue histomorphometry was implemented to analyze whole slide images. Feature analysis in tissue histomorphometry comprised methods from Computer vision to detect and analyze cell objects and methods from data science to visualize and statistically analyze the data. To analyze three-dimensional images the software IMARIS was used. Based on the IT infrastructure, it was possible, to digitally phenotype reactive and neoplastic tissue samples. Here, wall-like structures supporting compartmentalization by enclosing the germinal centers could be described for the first time. In addition, the conservation of quantitative ratios of individual cell populations within germinal centers could be shown. The ongoing process of phenotyping intact, reactive tissue enabled the detection and description of neoplastic lymphoid aberrations. Here, it could be shown that structural aberrations like the decompartimentalization process are mostly correlated with morphological alterations of fibroblastic reticulum cells. Cells that are also associated with these structural changes are called tumor-associated macrophages. Analyzing the distribution and morphology of macrophages in the tumor microenvironment revealed specific p

Human lymph nodes play a central part of immune defense against infection agents and tumor cells. Lymphoid follicles are compartments of the lymph node which are spherical, mainly filled with B cells. B cells are cellular components of the adaptive immune systems. In the course of a specific immune response, lymphoid follicles pass different morphological differentiation stages. The morphology and the spatial distribution of lymphoid follicles can be sometimes associated to a particular causative agent and development stage of a disease. We report our new approach for the automatic detection of follicular regions in histological whole slide images of tissue sections immuno-stained with actin. The method is divided in two phases: (1) shock filter-based detection of transition points and (2) segmentation of follicular regions. Follicular regions in 10 whole slide images were manually annotated by visual inspection, and sample surveys were conducted by an expert pathologist. The results of our method were validated by comparing with the manual annotation. On average, we could achieve a Zijbendos similarity index of 0.71, with a standard deviation of 0.07.

Aims: The examination of histological sections is still the gold standard in diagnostic pathology. Important histopathological diagnostic criteria are nuclear shapes and chromatin distribution as well as nucleus-cytoplasm relation and immunohistochemical properties of surface and intracellular proteins. The aim of this investigation was to evaluate the benefits and drawbacks of three-dimensional imaging of CD30+ cells in classical Hodgkin Lymphoma (cHL) in comparison to CD30+ lymphoid cells in reactive lymphoid tissues. Materials and results: Using immunoflourescence confocal microscopy and computer-based analysis, we compared CD30+ neoplastic cells in Nodular Sclerosis cHL (NScCHL), Mixed Cellularity cHL (MCcHL), with reactive CD30+ cells in Adenoids (AD) and Lymphadenitis (LAD). We confirmed that the percentage of CD30+ cell volume can be calculated. The amount in lymphadenitis was approx. 1.5%, in adenoids around 2%, in MCcHL up to 4,5% whereas the values for NScHL rose to more than 8% of the total cell cytoplasm. In addition, CD30+ tumour cells (HRS-cells) in cHL had larger volumes, and more protrusions compared to CD30+ reactive cells. Furthermore, the formation of large cell networks turned out to be a typical characteristic of NScHL. Conclusion: In contrast to 2D histology, 3D laser scanning offers a visualisation of complete cells, their network interaction and spatial distribution in the tissue. The possibility to differentiate cells in regards to volume, surface, shape, and cluster formation enables a new view on further diagnostic and biological questions. 3D includes an increased amount of information as a basis of bioinformatical calculations.