Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights

There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve functional tumour-associated blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation medi- ated by vascular targeting agents that induce occlusion/collapse of tumour blood vessels. In contrast, the therapeutic intention of normalising the abnormal structure and function of tumour vascular net- works, e.g. via alleviating stress-induced vaso-occlusion, is to improve chemo-, immuno- and radiation therapy efficacy. Although both strategies have shown therapeutic potential, it remains unclear why they often fail to control glioma invasion into the surrounding healthy brain tissue. To shed light on this issue, we propose a mathematical model of glioma invasion focusing on the interplay between the mi- gration/proliferation dichotomy (Go-or-Grow) of glioma cells and modulations of the functional tumour vasculature. Vaso-modulatory interventions are modelled by varying the degree of vaso-occlusion. We discovered the existence of a critical cell proliferation/diffusion ratio that separates glioma invasion re- sponses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the tumour front speed and increase the infiltration width, for those in the other regime the invasion speed increases and infiltration width decreases. We show how these in silico findings can be used to guide individualised approaches of vaso-modulatory treatment strategies and thereby improve success rates

Crowdsourcing of Histological Image Labeling and Object Delineation by Medical Students

Crowdsourcing in pathology has been performed on tasks that are assumed to be manageable by nonexperts. Demand remains high for annotations of more complex elements in digital microscopic images, such as anatomical structures. Therefore, this work investigates conditions to enable crowdsourced annotations of high-level image objects, a complex task considered to require expert knowledge. 76 medical students without specific domain knowledge who voluntarily participated in three experiments solved two relevant annotation tasks on histopathological images: (1) Labeling of images showing tissue regions, and (2) delineation of morphologically defined image objects. We focus on methods to ensure sufficient annotation quality including several tests on the required number of participants and on the correlation of participants' performance between tasks. In a set up simulating annotation of images with limited ground truth, we validated the feasibility of a confidence score using full ground truth. For this, we computed a majority vote using weighting factors based on individual assessment of contributors against scattered gold standard annotated by pathologists. In conclusion, we provide guidance for task design and quality control to enable a crowdsourced approach to obtain accurate annotations required in the era of digital pathology

Determination of parking space and its concurrent usage over time using semantically segmented mobile mapping data

Public space is a scarce good in cities. There are many concurrent usages, which makes an adequate allocation of space both difficult and highly attractive. A lot of space is allocated by parking cars - even if the parking spaces are not occupied by cars all the time. In this work, we analyze space demand and usage by parking cars, in order to evaluate, when this space could be used for other purposes. The analysis is based on 3D point clouds acquired at several times during a day. We propose a processing pipeline to extract car bounding boxes from a given 3D point cloud. For the car extraction we utilize a label transfer technique for transfers from semantically segmented 2D RGB images to 3D point cloud data. This semantically segmented 3D data allows us to identify car instances. Subsequently, we aggregate and analyze information about parking cars. We present an exemplary analysis of the urban area where we extracted 15.000 cars at five different points in time. Based on this aggregated we present analytical results for time dependent parking behavior, parking space availability and utilization

In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium

Scattered inflammatory cells are commonly observed in mammary gland tissue, most likely in response to normal cell turnover by proliferation and apoptosis, or as part of immunosurveillance. In contrast, lymphocytic lobulitis (LLO) is a recurrent inflammation pattern, characterized by lymphoid cells infiltrating lobular structures, that has been associated with increased familial breast cancer risk and immune responses to clinically manifest cancer. The mechanisms and pathogenic implications related to the inflammatory microenvironment in breast tissue are still poorly understood. Currently, the definition of inflammation is mainly descriptive, not allowing a clear distinction of LLO from physiological immunological responses and its role in oncogenesis remains unclear. To gain insights into the prognostic potential of inflammation, we developed an agent-based model of immune and epithelial cell interactions in breast lobular epithelium. Physiological parameters were calibrated from breast tissue samples of women who underwent reduction mammoplasty due to orthopedic or cosmetic reasons. The model allowed to investigate the impact of menstrual cycle length and hormone status on inflammatory responses to cell turnover in the breast tissue. Our findings suggested that the immunological context, defined by the immune cell density, functional orientation and spatial distribution, contains prognostic information previously not captured by conventional diagnostic approaches. Several studies provided conclusive evidence that a delicate balance between mammary epithelial cell proliferation and apoptosis regulates homeostasis in the healthy breast tissue 1-7. After menarche, and in the absence of pregnancy, the adult female mammary gland is subjected to cyclic fluctuations depending on hormonal stimulation 1,8. In response to such systemic hormonal changes, the breast epithelium undergoes a tightly regulated sequence of cell proliferation and apoptosis during each ovarian/menstrual cycle 1-3. The peak of epithelial cell proliferation has been reported to occur during the luteal phase, suggesting a synergistic influence of steroid hormones, such as estrogen and progesterone 2-5. In turn, the peak of apoptotic activity would be expected in response to decreasing hormone levels towards the end of the menstrual cycle 2-5. However, recent histologic findings indicate that apoptosis reaches its maximum levels in the middle of the luteal phase, although there is also a peak at about the third day of the menstrual cycle 6,7. Experimental measurements of cell turnover, i.e. programmed cell death and proliferation, demonstrated that an imbalance between the mitotic and apoptotic activity might lead to malignant transformation of epithelial cells and tumorigenic processes 9-11. Indeed, excessive cell proliferation promotes accumulation of DNA damage due to insufficient timely repair and mutations 12,13. There is also recent evidence that hormones suppress effective DNA repair and alter DNA damage response (DDR) 13-15

Fast segmentation for texture-based cartography of whole slide images

In recent years, new optical microscopes have been developed, providing very high spatial resolution images called Whole Slide Images (WSI). The fast and accurate display of such images for visual analysis by pathologists and the conventional automated analysis remain challenging, mainly due to the image size (sometimes billions of pixels) and the need to analyze certain image features at high resolution. To propose a decision support tool to help the pathologist interpret the information contained by the WSI, we present a new approach to establish an automatic cartography of WSI in reasonable time. The method is based on an original segmentation algorithm and on a supervised multiclass classification using a textural characterization of the regions computed by the segmentation. Application to breast cancer WSI shows promising results in terms of speed and quality

Synthesizing Whole Slide Images

The increasing availability of digital whole slide images opens new perspectives for computer-assisted image analysis complementing modern histopathology, assuming we can implement reliable and efficient image analysis algorithms to extract the biologically relevant information. Both validation and supervised learning techniques typically rely on ground truths manually made by human experts. However, this task is difficult, subjective and usually not exhaustive. This is a well-known issue in the field of biomedical imaging, and a common solution is the use of artificial “phantoms”. Following this trend, we study the feasibility of synthesizing artificial histological images to create perfect ground truths. In this paper, we show that it is possible to generate a synthetic whole slide image with reasonable computing resources, and we propose a way to evaluate its quality

A Graph-Based Digital Pathology Approach To Describe Lymphocyte Clustering Patterns After Renal Transplantation

Introduction/ Background Renal transplantation (rTx) induces an adaptive immune response against foreign donor antigens mediated by lymphocytes of the recipient. Local accumulation of B- and T-cells is an important component of this response enabling and controlling immune cell interactions [1]. Combining digital microscopic images with network analysis [2][3] opens new perspectives to study the spa- tial dimension of lymphocyte clustering and to model their potential interactions.   Aims The aim of this study is to characterize the range of B- and T-lymphocytic infiltrates below the threshold of rejection defined by theBanffclassification [4][5] and to propose a mathematical description of immune cell clustering for use in systems medicine approaches.   Methods We established a workflow to comprehensively characterize lymphocyte clusters and compare their morphological features with organized structures such as secondary or tertiary lymphoid organs (TLO/SLO) [6]. 51 renal protocol and indication biopsies from 13 patients without evidence for severe rejection over 10 years were stained by CD3/CD20 duplex immunohisto- chemistry. Whole slide images (WSIs) were acquired to automatically detect biologically relevant regions of in- terest (ROIs) by means of density maps for lymphocytes (image analysis workflow illustrated in Fig. 1a). They are generated from single nuclei identification using an au- to-adaptive random forest pixelwise classifier (“nucleus container” module [7],Definiens,Germany). We imple- mented a graph-based tool in Java using individual cell coordinates to identify cell compartments (Fig. 1b) and applied it to each selected ROI. For this, a neighborhood graph is built by Delaunay triangulation and Euclidean distances. This analysis allows describing their specific clustering behavior based on features as described in [8]. The convex hull of the neighborhood graph allows a visualization of B- and T-cell compartments.   Results We identified B-cell rich compartments in about 55% of 150 ROIs in kidney tissue after successful transplantation (examples in Fig. 2). The B-cell compartments in rTx tended towards smaller overall size with on average about 90 cells in a B-cell cluster compared to more than 600 B-cells observed in mature TLOs and SLOs and they showed less prominent spatial organization (average degree on average 3.92 instead of 4.97; degree shows generally Poisson distribution as illustrated in Fig. 3A). Further, the graph analysis confirmed lower B-cell density (Fig. 3B displays the exponential character of the spatial B-cell distribution in a selected ROI), a different ratio between T- and B-cell compartments, and more frequent overlap between both regions than in mature lymphoid structures.   We conclude that the graph-based approach is feasible to distinguish relevant immune cell patterns in rTx and provides a useful mathematical description of neighborhood relationships between immune cells and their spatial organization. The workflow has the potential to improve throughput and robustness of immune cell evaluation for use in translational science

Stain unmixing in brightfield multiplexed immunohistochemistry

Automated image analysis of multiplexed brightfield immunohistochemistry assays is a challenging objective. One central task of the analysis is the robust identification of the different stains in the image, called stain unmixing. Stain unmixing strongly depends on the method of image acquisition. Currently available multispectral cameras enable color unmixing of single fields of view (FoV), selected by matter experts (e.g. pathologists). Beyond the individual FoV approach, there is an increasing need to process larger regions or whole histopathological sections (whole slide imaging; WSI). Rapid color deconvolution in WSI is a challenge that is only partially solved. We propose a method based on a multilayer perceptron to compute dye-specific stain layers for chromogenic red and brown labeling in WSI

Role of P-selectin in platelet sequestration in pulmonary capillaries during endotoxemia

Background: There is growing evidence that platelets accumulate in the lung and contribute to the pathogenesis of acute lung injury during endotoxemia. The aims of the present study were to localize platelet sequestration in the pulmonary microcirculation and to investigate the role of P-selectin as a molecular mechanism of platelet endothelial cell interaction. Methods: We used in vivo fluorescence microscopy to quantify the kinetics of fluorescently labeled erythrocytes and platelets in alveolar capillary networks in rabbit lungs. Results: Six hours after onset of endotoxin infusion we observed a massive rolling along and firm adherence of platelets to lung capillary endothelial cells whereas under control conditions no platelet sequestration was detected. P-selectin was expressed on the surface of separated platelets which were incubated with endotoxin and in lung tissue. Pretreatment of platelets with fucoidin, a P-selectin antagonist, significantly attenuated the endotoxin-induced platelet rolling and adherence. In contrast, intravenous infusion of fucoidin in endotoxin-treated rabbits did not inhibit platelet sequestration in pulmonary capillaries. Conclusion: We conclude that platelets accumulate in alveolar capillaries following endotoxemia. P-selectin expressed on the surface of platelets seems to play an important role in mediating this platelet-endothelial cell interaction. Copyright (c) 2006 S. Karger AG, Basel

Leukocyte trafficking in alveoli and airway passages

Many pulmonary diseases preferentially affect the large airways or the alveoli. Although the mechanisms are often particular to each disease process, site-specific differences in leukocyte trafficking and the regulation of inflammation also occur. Differences in the process of margination, sequestration, adhesion, and migration occur that can be attributed to differences in anatomy, hemodynamics, and the expression of proteins. The large airways are nourished by the bronchial circulation, whereas the pulmonary circulation feeds the distal lung parenchyma. The presence of different cell types in large airways from those in alveoli might contribute to site-specific differences in the molecular regulation of the inflammatory process