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In the context of precision medicine with immunotherapies there is an increasing need for companion diagnostic tests to identify potential therapy responders and avoid treatment coming along with severe adverse events for non-responders. Here, we present a retrospective case study to discover image-based signatures for developing a potential companion diagnostic test for ipilimumab (IPI) in malignant melanoma. Signature discovery is based on digital pathology and fully automatic quantitative image analysis using virtual multiplexing as well as machine learning and deep learning on whole-slide images. We systematically correlated the patient outcome data with potentially relevant local image features using a Tissue Phenomics approach with a sound cross validation procedure for reliable performance evaluation. Besides uni-variate models we also studied combinations of signatures in several multi-variate models. The most robust and best performing model was a decision tree model based on relative densities of CD8+ tumor infiltrating lymphocytes in the intra-tumoral infiltration region. Our results are well in agreement with observations described in previously published studies regarding the predictive value of the immune contexture, and thus, provide predictive potential for future development of a companion diagnostic test.

Our aim is to complement observer-dependent approaches of immune cell evaluation in microscopy images with reproducible measures for spatial composition of lymphocytic infiltrates. Analyzing such patterns of inflammation is becoming increasingly important for therapeutic decisions, for example in transplantation medicine or cancer immunology. We developed a graph-based assessment of lymphocyte clustering in full whole slide images. Based on cell coordinates detected in the full image, a Delaunay triangulation and distance criteria are used to build neighborhood graphs. The composition of nodes and edges are used for classification, e.g. using a support vector machine. We describe the variability of these infiltrates on CD3/CD20 duplex staining in renal biopsies of long-term functioning allografts, in breast cancer cases, and in lung tissue of cystic fibrosis patients. The assessment includes automated cell detection, identification of regions of interest, and classification of lymphocytic clusters according to their degree of organization. We propose a neighborhood feature which considers the occurrence of edges with a certain type in the graph to distinguish between phenotypically different immune infiltrates. Our work addresses a medical need and provides a scalable framework that can be easily adjusted to the requirements of different research questions., Author summary In this study, we developed a workflow to detect and classify immune infiltrates in giga-pixel microscopy images. It allowed us to measure the degree of organization in lymphocyte clusters with graph-based features and finally to distinguish between tertiary lymphoid organs and other infiltrates. As a clinically relevant use case, we applied it to three different types of tissues and diseases. Our method addresses the need for observer-independent, large-scale evaluation of immune cell patterns and is a prerequisite to capture spatial composition of immune cells that can be used to parameterize mathematical models in systems immunology.

Changes in wall shear stress of blood vessels are assumed to be an important component of many physiological and pathophysiological processes. However, due to technical limitations experimental in vivo data are rarely available. Here, we investigated two-photon excitation fluorescence microscopy as an option to measure vessel diameter as well as blood flow velocities in a murine hindlimb model of arteriogenesis (collateral artery growth). Using line scanning at high frequencies, we measured the movement of blood cells along the vessel axis. We found that peak systolic blood flow velocity averaged 9 mm/s and vessel diameter 42 µm in resting collaterals. Induction of arteriogenesis by femoral artery ligation resulted in a significant increase in centerline peak systolic velocity after 1 day with an average of 51 mm/s, whereas the averaged luminal diameter of collaterals (52 µm) changed much less. Thereof calculations revealed a significant fourfold increase in hemodynamic wall shear rate. Our results indicate that two-photon line scanning is a suitable tool to estimate wall shear stress e.g., in experimental animal models, such as of arteriogenesis, which may not only help to understand the relevance of mechanical forces in vivo, but also to adjust wall shear stress in ex vivo investigations on isolated vessels as well as cell culture experiments.

Objective— Cell–matrix interactions are crucial for regulating cellular activities, such as migration. This is of special importance for morphogenic processes, such as angiogenesis (the development of new blood vessels). Most of our understanding of cell migration relies on 2-dimensional (2D) experiments. However, the awareness that 3D settings might elicit different results has increased. Knowledge about endothelial cell (EC) behavior in 3D environments and the influence of matrix composition on EC migration, in particular, is still limited. Approach and Results— We characterize the migration of single ECs through 2 structurally different hydrogels: spongy Matrigel and fibrillar collagen I. Our observations reveal an elongated migration phenotype in Matrigel and a rounded phenotype with pronounced cell blebs (blebs >2 µm) in collagen I, which have not previously been described in ECs. Directed migration seems to depend on Rac1 and Cdc42 in collagen, but not in Matrigel (shown using appropriate pharmacological inhibitors). By applying anti-integrin antibodies and supplementing laminin in collagen gels, we identify laminin as the main determinant of the elongated phenotype. Laminin seems to induce a morphological switch between modes of migration. As an in situ proof of principle, we performed live imaging of EC migration during vascular growth in a murine retina in the absence and presence of anti-integrin antibodies. Conclusions— We show that, surprisingly, ECs can evade the pharmacological inhibition of central signaling pathways involved in migration (contractility, small GTPases, and proteolysis) by shifting gears between modes of migration. This finding indicates an unexpected contextual plasticity of EC behavior.

Raw PET list-mode data contains motion artifacts causing image blurring and decreased spatial resolution. Unless corrected, this leads to underestimation of the tracer uptake and overestimation of the lesion size, as well as inaccuracies with regard to left ventricular volume and ejection fraction (LVEF), especially in small animal imaging. A respiratory trigger signal from respiration-induced variations in the electro-cardiogram (ECG) was detected. Original and revised list-mode PET data were used for calculation of left ventricular function parameters using both respiratory gating techniques. For adequately triggered datasets we saw no difference in mean respiratory cycle period between the reference standard (RRS) and the ECG-based (ERS) methods (1120 ± 159 ms vs 1120 ± 159 ms; P = n.s.). While the ECG-based method showed somewhat higher signal noise (66 ± 22 ms vs 51 ± 29 ms; P