Novel AI-Based Algorithm for the Automated Measurement of Cervical Sagittal Balance Parameters. A Validation Study on Pre- and Postoperative Radiographs of 129 Patients.

STUDY DESIGN: Retrospective, mono-centric cohort research study. OBJECTIVES: The analysis of cervical sagittal balance parameters is essential for preoperative planning and dependent on the physician's experience. A fully automated artificial intelligence-based algorithm could contribute to an objective analysis and save time. Therefore, this algorithm should be validated in this study. METHODS: Two surgeons measured C2-C7 lordosis, C1-C7 Sagittal Vertical Axis (SVA), C2-C7-SVA, C7-slope and T1-slope in pre- and postoperative lateral cervical X-rays of 129 patients undergoing anterior cervical surgery. All parameters were measured twice by surgeons and compared to the measurements by the AI algorithm consisting of 4 deep convolutional neural networks. Agreement between raters was quantified, among other metrics, by mean errors and single measure intraclass correlation coefficients for absolute agreement. RESULTS: ICC-values for intra- (range: .92-1.0) and inter-rater (.91-1.0) reliability reflect excellent agreement between human raters. The AI-algorithm could determine all parameters with excellent ICC-values (preop:0.80-1.0; postop:0.86-.99). For a comparison between the AI algorithm and 1 surgeon, mean errors were smallest for C1-C7 SVA (preop: -.3 mm (95% CI:-.6 to -.1 mm), post: .3 mm (.0-.7 mm)) and largest for C2-C7 lordosis (preop:-2.2° (-2.9 to -1.6°), postop: 2.3°(-3.0 to -1.7°)). The automatic measurement was possible in 99% and 98% of pre- and postoperative images for all parameters except T1 slope, which had a detection rate of 48% and 51% in pre- and postoperative images. CONCLUSION: This study validates that an AI-algorithm can reliably measure cervical sagittal balance parameters automatically in patients suffering from degenerative spinal diseases. It may simplify manual measurements and autonomously analyze large-scale datasets. Further studies are required to validate the algorithm on a larger and more diverse patient cohort.

Evidence for Enhanced Efficacy of Passive Immunotherapy against Beta-Amyloid in CD33-Negative 5xFAD Mice.

Passive immunotherapy is a very promising approach for the treatment of Alzheimer's disease (AD). Among the different antibodies under development, those targeting post-translationally modified Aß peptides might combine efficient reduction in beta-amyloid accompanied by lower sequestration in peripheral compartments and thus anticipated and reduced treatment-related side effects. In that regard, we recently demonstrated that the antibody-mediated targeting of isoD7-modified Aß peptides leads to the attenuation of AD-like amyloid pathology in 5xFAD mice. In order to assess novel strategies to enhance the efficacy of passive vaccination approaches, we investigated the role of CD33 for Aß phagocytosis in transgenic mice treated with an isoD7-Aß antibody. We crossbred 5xFAD transgenic mice with CD33 knock out (CD33KO) mice and compared the amyloid pathology in the different genotypes of the crossbreds. The knockout of CD33 in 5xFAD mice leads to a significant reduction in Aß plaques and concomitant rescue of behavioral deficits. Passive immunotherapy of 5xFAD/CD33KO showed a significant increase in plaque-surrounding microglia compared to 5xFAD treated with the antibody. Additionally, we observed a stronger lowering of Aß plaque load after passive immunotherapy in 5xFAD/CD33KO mice. The data suggest an additive effect of passive immunotherapy and CD33KO in terms of lowering Aß pathology. Hence, a combination of CD33 antagonists and monoclonal antibodies might represent a strategy to enhance efficacy of passive immunotherapy in AD.

Extracellular Vesicles of Mesenchymal Stromal Cells Can be Taken Up by Microglial Cells and Partially Prevent the Stimulation Induced by ß-amyloid.

Mesenchymal stromal/stem cells (MSCs) have great capacity for immune regulation. MSCs provide protective paracrine effects, which are partially exerted by extracellular vesicles (EVs). It has been reported that MSCs-derived EVs (MSC-EVs) contain soluble factors, such as cytokines, chemokines, growth factors and even microRNAs, which confer them similar anti-inflammatory and regenerative effects to MSCs. Moreover, MSCs modulate microglia activation through a dual mechanism of action that relies both on cell contact and secreted factors. Microglia cells are the central nervous system immune cells and the main mediators of the inflammation leading to neurodegenerative disorders. Here, we investigated whether MSC-EVs affect the activation of microglia cells by ß-amyloid aggregates. We show that the presence of MSC-EVs can prevent the upregulation of pro-inflammatory mediators such as tumor necrosis factor (TNF)-α and nitric oxide (NO). Both are up-regulated in neurodegenerative diseases representing chronic inflammation, as in Alzheimer's disease. We demonstrate that MSC-EVs are internalized by the microglia cells. Further, our study supports the use of MSC-EVs as a promising therapeutic tool to treat neuroinflammatory diseases.Significance StatementIt has been reported that mesenchymal stromal/stem cells and MSC-derived small extracellular vesicles have therapeutic effects in the treatment of various degenerative and inflammatory diseases. Extracellular vesicles are loaded with proteins, lipids and RNA and act as intercellular communication mediators. Here we show that extracellular vesicles can be taken up by murine microglial cells. In addition, they partially reduce the activation of microglial cells against ß-amyloid aggregates. This inhibition of microglia activation may present an effective strategy for the control/therapy of neurodegenerative diseases such as Alzheimer's disease.

Visualization and co-registration of correlative microscopy data with the ImageJ plug-in Correlia.

Correlative microscopy experiments require the co-registration of the image data acquired by different micro-analytical techniques. Major challenges are the potentially very different fields-of-view and resolutions as well as the multi-modality of the data. To provide microscopists with an easy-to-use software for two-dimensional image co-registration we have developed Correlia, an open source software based on ImageJa/Fiji,b which is fully tailored for the registration of multi-modal microscopy data. It can handle data-sets of in principle arbitrary extent and uses classical approaches, i.e., rigid registration tools or B-spline based deformation models for the correction of both, global and local misalignments, such that a fast registration output is provided. Here we describe some of the basics of Correlia focusing on its application: firstly, registration workflows are outlined on artificial data. In the second part these recipes are applied to register correlative data acquired on an algal biofilm and a soil sample.

Correlia: an ImageJ plug-in to co-register and visualise multimodal correlative micrographs.

The correlation of different microscopic imaging techniques alongside with microanalytical methods is crucial to better understand biological processes on a subcellular level. For that, micrographs and chemical maps exhibiting both, very different spatial resolution and field-of-view but also a highly multimodal content has to be co-registered. We developed the ImageJ/Fiji plug-in Correlia that provides an environment for handling multimodal correlative microscopy data. Several linear and nonlinear registration methods using either feature or area-based similarity measures can flexibly be cascaded to align and warp 2D microscopy data sets. The registration of data sets containing light- and electron micrographs as well as chemical maps acquired by secondary-ion mass spectroscopy and energy-dispersive X-ray spectroscopy is demonstrated. Correlia is an open-source tool developed particularly for the registration and analysis of highly multimodal 2D correlative microscopy data. LAY DESCRIPTION: If a microscopic object is imaged correlatively by two or more different microscopes the acquired micrographs will have to be overlaid accurately using an image-registration software. In cases of relatively similar image content creating such an overlay is straight-forward but what if the fields-of-view and resolutions of the micrographs differ significantly? What if there are distortions in a micrograph which have to be corrected before creating an overlay? What if furthermore a chemical map shall be overlaid that merely shows regions in which a certain chemical element is present? The rapidly increasing number of applications in correlative microscopy is calling for an easy-to-use and flexible image registration software that can deal with these challenges. Having that in mind, we developed Correlia, an ImageJ/Fiji plug-in that provides an environment for handling multimodal 2D correlative microscopy data-sets. It allows for creating overlays using different registration algorithms that can flexibly be cascaded. In this paper we describe what is happening 'under the hood' and give two example data-sets from microbiology which were registered using Correlia. Correlia is open source software and available from www.ufz.de/correlia - including introductory examples, as the authors would like to encourage other scientists to process their individual correlative microscopy data using Correlia.

An image dataset related to automated macrophage detection in immunostained lymphoma tissue samples.

BACKGROUND: We present an image dataset related to automated segmentation and counting of macrophages in diffuse large B-cell lymphoma (DLBCL) tissue sections. For the classification of DLBCL subtypes, as well as for providing a prognosis of the clinical outcome, the analysis of the tumor microenvironment and, particularly, of the different types and functions of tumor-associated macrophages is indispensable. Until now, however, most information about macrophages has been obtained either in a completely indirect way by gene expression profiling or by manual counts in immunohistochemically (IHC) fluorescence-stained tissue samples while automated recognition of single IHC stained macrophages remains a difficult task. In an accompanying publication, a reliable approach to this problem has been established, and a large set of related images has been generated and analyzed. RESULTS: Provided image data comprise (i) fluorescence microscopy images of 44 multiple immunohistostained DLBCL tumor subregions, captured at 4 channels corresponding to CD14, CD163, Pax5, and DAPI; (ii) "cartoon-like" total variation-filtered versions of these images, generated by Rudin-Osher-Fatemi denoising; (iii) an automatically generated mask of the evaluation subregion, based on information from the DAPI channel; and (iv) automatically generated segmentation masks for macrophages (using information from CD14 and CD163 channels), B-cells (using information from Pax5 channel), and all cell nuclei (using information from DAPI channel). CONCLUSIONS: A large set of IHC stained DLBCL specimens is provided together with segmentation masks for different cell populations generated by a reference method for automated image analysis, thus featuring considerable reuse potential.

Automated macrophage counting in DLBCL tissue samples: a ROF filter based approach.

BACKGROUND: For analysis of the tumor microenvironment in diffuse large B-cell lymphoma (DLBCL) tissue samples, it is desirable to obtain information about counts and distribution of different macrophage subtypes. Until now, macrophage counts are mostly inferred from gene expression analysis of whole tissue sections, providing only indirect information. Direct analysis of immunohistochemically (IHC) fluorescence stained tissue samples is confronted with several difficulties, e.g. high variability of shape and size of target macrophages and strongly inhomogeneous intensity of staining. Consequently, application of commercial software is largely restricted to very rough analysis modes, and most macrophage counts are still obtained by manual counting in microarrays or high power fields, thus failing to represent the heterogeneity of tumor microenvironment adequately. METHODS: We describe a Rudin-Osher-Fatemi (ROF) filter based segmentation approach for whole tissue samples, combining floating intensity thresholding and rule-based feature detection. Method is validated against manual counts and compared with two commercial software kits (Tissue Studio 64, Definiens AG, and Halo, Indica Labs) and a straightforward machine-learning approach in a set of 50 test images. Further, the novel method and both commercial packages are applied to a set of 44 whole tissue sections. Outputs are compared with gene expression data available for the same tissue samples. Finally, the ROF based method is applied to 44 expert-specified tumor subregions for testing selection and subsampling strategies. RESULTS: Among all tested methods, the novel approach is best correlated with manual count (0.9297). Automated detection of evaluation subregions proved to be fully reliable. Comparison with gene expression data obtained for the same tissue samples reveals only moderate to low correlation levels. Subsampling within tumor subregions is possible with results almost identical to full sampling. Mean macrophage size in tumor subregions is 152.5±111.3 µm2. CONCLUSIONS: ROF based approach is successfully applied to detection of IHC stained macrophages in DLBCL tissue samples. The method competes well with existing commercial software kits. In difference to them, it is fully automated, externally repeatable, independent on training data and completely documented. Comparison with gene expression data indicates that image morphometry constitutes an independent source of information about antibody-polarized macrophage occurence and distribution.

T-Cell Clustering in Neoplastic Follicles of Follicular Lymphoma.

The nonneoplastic microenvironment is abundant in follicular lymphoma. Its composition has been reported to be associated with the course of the disease. Lack of animal models hampers studies of interaction between lymphoma and bystander cells. We aimed to identify indicators of cellular interaction exemplified by nonrandom distribution of cell types within neoplastic follicles. Physiological germinal centers and follicles in follicular lymphoma were stained to identify macrophages, all T, follicular T-helper, dendritic and B cells. Density of cell types and cell distribution (spatial point pattern) were analyzed by digital image analysis. The density of all T, follicular T-helper and dendritic cells was higher in the dark zone than in the light zone of physiological germinal centers. Densities of cell types in follicular lymphoma were intermediate between the light and the dark zone. All cell types analyzed showed a completely random spatial distribution pattern within the dark and the light zone, respectively. In follicular lymphoma B cells and macrophages displayed complete spatial randomness. In contrast, all T cells, follicular T-helper cells and dendritic cells showed clustering of each individual cell type within a radius of 6-10 µm in the lymphoma. We conclude that the distribution of nonneoplastic cells within follicles of follicular lymphoma is not random. T cells and dendritic cells form clusters within the follicles, suggestive of sites of interaction between microenvironment and lymphoma cells. These clusters might help to understand the interaction of lymphoma cells with the microenvironment and might provide a structure for therapeutic intervention.

Linking stem cell function and growth pattern of intestinal organoids.

Intestinal stem cells (ISCs) require well-defined signals from their environment in order to carry out their specific functions. Most of these signals are provided by neighboring cells that form a stem cell niche, whose shape and cellular composition self-organize. Major features of this self-organization can be studied in ISC-derived organoid culture. In this system, manipulation of essential pathways of stem cell maintenance and differentiation results in well-described growth phenotypes. We here provide an individual cell-based model of intestinal organoids that enables a mechanistic explanation of the observed growth phenotypes. In simulation studies of the 3D structure of expanding organoids, we investigate interdependences between Wnt- and Notch-signaling which control the shape of the stem cell niche and, thus, the growth pattern of the organoids. Similar to in vitro experiments, changes of pathway activities alter the cellular composition of the organoids and, thereby, affect their shape. Exogenous Wnt enforces transitions from branched into a cyst-like growth pattern; known to occur spontaneously during long term organoid expansion. Based on our simulation results, we predict that the cyst-like pattern is associated with biomechanical changes of the cells which assign them a growth advantage. The results suggest ongoing stem cell adaptation to in vitro conditions during long term expansion by stabilizing Wnt-activity. Our study exemplifies the potential of individual cell-based modeling in unraveling links between molecular stem cell regulation and 3D growth of tissues. This kind of modeling combines experimental results in the fields of stem cell biology and cell biomechanics constituting a prerequisite for a better understanding of tissue regeneration as well as developmental processes.

Skin regeneration in deep second-degree scald injuries either by infusion pumping or topical application of recombinant human erythropoietin gel.

Large doses of recombinant growth factors formulated in solution form directly injected into the body is usual clinical practice in treating second-degree scald injuries, with promising results, but this approach creates side effects; furthermore, it may not allow appropriate levels of the factor to be sensed by the target injured tissue/organ in the specific time frame, owing to complications arising from regeneration. In this research, two delivery methods (infusion pumping and local topical application) were applied to deliver recombinant human erythropoietin (rHuEPO) for skin regeneration. First, rHuEPO was given in deep second-degree scald injury sites in mice by infusion pump. Vascularization was remarkably higher in the rHuEPO pumping group than in controls. Second, local topical application of rHuEPO gel was given in deep second-degree scald injury sites in rats. Histological analysis showed that epithelialization rate was significantly higher in the rHuEPO gel-treated group than in controls. Immunohistochemical studies showed that the rHuEPO gel-treated group showed remarkably higher expression of skin regeneration makers than the control group. An accurate method for visualization and quantification of blood vessel networks in target areas has still not been developed up to this point, because of technical difficulties in detecting such thin blood vessels. A method which utilizes a series of steps to enhance the image, removes noise from image background, and tracks the vessels edges for vessel segmentation and quantification has been used in this study. Using image analysis methods, we were able to detect the microvascular networks of newly formed blood vessels (less than 500 µm thickness), which participate in the healing process, providing not only nutrition and oxygen to grow tissues but also necessary growth factors to grow tissue cells for complete skin regeneration. The rHuEPO-treated group showed higher expression of stem cell markers (CD 31, CD 90, CD 71, and nestin), which actively contribute to in-wound-healing processes for new hair follicle generation as well as skin regeneration. Collectively, both rHuEPO group pumping into the systemic circulation system, and injection into the local injury area, prompted mice and rats to form new blood vessel networks in scald injury sites, which significantly participate in the scald healing process. These results may lead to the development of novel treatments for scald wounds.

Parametric model for the 3D reconstruction of individual fovea shape from OCT data.

As revealed by optical coherence tomography (OCT), the shape of the fovea may vary greatly among individuals. However, none of the hitherto available mathematical descriptions comprehensively reproduces all individual characteristics such as foveal depth, slope, naso-temporal asymmetry, and others. Here, a novel mathematical approach is presented to obtain a very accurate model of the complete 3D foveal surface of an individual, by utilizing recent developments in OCT. For this purpose, a new formula was developed serving as a simple but very flexible way to represent a given fovea. An extensive description of the used model parameters, as well as, of the complete method of reconstructing a foveal surface from OCT data, is presented. Noteworthy, the formula analytically provides characteristic foveal parameters and thus allows for extensive quantification. The present approach was verified on 432 OCT scans and has proved to be able to capture the whole range of asymmetric foveal shapes with high accuracy (i.e. a mean fit error of 1.40 µm).

Nanostructured self-assembling peptides as a defined extracellular matrix for long-term functional maintenance of primary hepatocytes in a bioartificial liver modular device.

Much effort has been directed towards the optimization of the capture of in vivo hepatocytes from their microenvironment. Some methods of capture include an ex vivo cellular model in a bioreactor based liver module, a micropatterned module, a microfluidic 3D chip, coated plates, and other innovative approaches for the functional maintenance of primary hepatocytes. However, none of the above methods meet US Food and Drug Administration (FDA) guidelines, which recommend and encourage that the duration of a toxicity assay of a drug should be a minimum of 14 days, to a maximum of 90 days for a general toxicity assay. Existing innovative reports have used undefined extracellular matrices like matrigel, rigid collagen, or serum supplementations, which are often problematic, unacceptable in preclinical and clinical applications, and can even interfere with experimental outcomes. We have overcome these challenges by using integrated nanostructured self-assembling peptides and a special combination of growth factors and cytokines to establish a proof of concept to mimic the in vivo hepatocyte microenvironment pattern in vitro for predicting the in vivo drug hepatotoxicity in a scalable bioartificial liver module. Hepatocyte functionality (albumin, urea) was measured at days 10, 30, 60, and 90 and we observed stable albumin secretion and urea function throughout the culture period. In parallel, drug metabolizing enzyme biomarkers such as ethoxyresorufin-O-deethylase, the methylthiazol tetrazolium test, and the lactate dehydrogenase test were carried out at days 10, 30, 60, and 90. We noticed excellent mitochondrial status and membrane stability at 90 days of culture. Since alpha glutathione S-transferase (GST) is highly sensitive and a specific marker of hepatocyte injury, we observed significantly low alpha GST levels on all measured days (10, 30, 60, and 90). Finally, we performed the image analysis of mitochondria-cultured hepatocytes at day 90 in different biophysical parameters using confocal microscopy. We applied an automatic algorithm-based method for 3D visualization to show the classic representation of the mitochondrial distribution in double hepatocytes. An automated morphological measurement was conducted on the mitochondrial distribution in the cultured hepatocytes. Our proof of concept of a scalable bioartificial liver modular device meets FDA guidelines and may function as an alternative model of animal experimentation for pharmacological and toxicological studies involving drug metabolism, enzyme induction, transplantation, viral hepatitis, hepatocyte regeneration, and can also be used in other existing bioreactor modules for long-term culture for up to 90 days or more.

Quantitative analysis of astrogliosis in drug-dependent humans.

Drug addiction is a chronic, relapsing disease caused by neurochemical and molecular changes in the brain. In this human autopsy study qualitative and quantitative changes of glial fibrillary acidic protein (GFAP)-positive astrocytes in the hippocampus of 26 lethally intoxicated drug addicts and 35 matched controls are described. The morphological characterization of these cells reflected alterations representative for astrogliosis. But, neither quantification of GFAP-positive cells nor the Western blot analysis indicated statistical significant differences between drug fatalities versus controls. However, by semi-quantitative scoring a significant shift towards higher numbers of activated astrocytes in the drug group was detected. To assess morphological changes quantitatively, graph-based representations of astrocyte morphology were obtained from single cell images captured by confocal laser scanning microscopy. Their underlying structures were used to quantify changes in astroglial fibers in an automated fashion. This morphometric analysis yielded significant differences between the investigated groups for four different measures of fiber characteristics (Euclidean distance, graph distance, number of graph elements, fiber skeleton distance), indicating that, e.g., astrocytes in drug addicts on average exhibit significant elongation of fiber structures as well as two-fold increase in GFAP-positive fibers as compared with those in controls. In conclusion, the present data show characteristic differences in morphology of hippocampal astrocytes in drug addicts versus controls and further supports the involvement of astrocytes in human pathophysiology of drug addiction. The automated quantification of astrocyte morphologies provides a novel, testable way to assess the fiber structures in a quantitative manner as opposed to standard, qualitative descriptions.

Classifying prostate cancer malignancy by quantitative histomorphometry.

PURPOSE: Prostate cancer is routinely graded according to the Gleason grading scheme. This scheme is predominantly based on the textural appearance of aberrant glandular structures. Gleason grade is difficult to standardize and often leads to discussion due to interrater and intrarater disagreement. Thus, we investigated whether digital image based automated quantitative histomorphometry could be used to achieve a more standardized, reproducible classification outcome. MATERIALS AND METHODS: In a proof of principle study we developed a method to evaluate digitized histological images of single prostate cancer regions in hematoxylin and eosin stained sections. Preprocessed color images were subjected to color deconvolution, followed by the binarization of obtained hematoxylin related image channels. Highlighted neoplastic epithelial gland related objects were morphometrically assessed by a classifier based on 2 calculated quantitative and objective geometric measures, that is inverse solidity and inverse compactness. The procedure was then applied to the prostate cancer probes of 125 patients. Each probe was independently classified for Gleason grade 3, 4 or 5 by an experienced pathologist blinded to image analysis outcome. RESULTS: Together inverse compactness and inverse solidity were adequate discriminatory features for a powerful classifier that distinguished Gleason grade 3 from grade 4/5 histology. The classifier was robust on sensitivity analysis. CONCLUSIONS: Results suggest that quantitative and interpretable measures can be obtained from image based analysis, permitting algorithmic differentiation of prostate Gleason grades. The method must be validated in a large independent series of specimens.

Suitability of infrared microspectroscopic imaging for histopathology of the uterine cervix.

AIMS: Infrared microspectroscopy (IR-MSP) has been proposed for automated histological tissue differentiation of unstained specimens based on chemical analysis of cell and extracellular constituents. This study aimed to determine the accuracy of IR-MSP-based histopathology of cervical carcinoma sections with complex tissue architecture under practically relevant testing conditions. METHODS AND RESULTS: In total, 46 regions of interest, covering an area of almost 50 mm(2) on sections derived from paraffin-embedded tissue of radical hysterectomy specimens, were analysed by IR-MSP (nominal resolution ~4.2 µm). More than 2.8 million pixel spectra that were processed using fuzzy c-means clustering followed by hierarchical cluster analysis permitted image segmentation regarding different biochemical properties. Linear image registration was applied to compare these segmentation results with manual labelling on haematoxylin and eosin-stained references (resolution ~0.7 µm). For recognition of nine tissue types, sensitivities were 42-91% and specificities were 79-100%, mostly being affected by peritumoral inflammatory responses. Algorithmic variation of the outline of dysplasia and carcinoma revealed a spatial preference of false values in tissue transition areas. CONCLUSIONS: This imaging technique has potential as a new method for tissue characterization; however, the recognition accuracy does not justify a pathologist-independent tissue analysis, and the application is only possible in combination with concomitant conventional histopathology.

Comparison of different fabrication techniques for human adipose tissue engineering in severe combined immunodeficient mice.

Adipose tissue engineering has been advocated for soft-tissue augmentation and for the treatment of soft tissue defects. The efficacy in terms of persistence of the engineered fat is, however, not yet understood and could depend on the nature of fabrication and application. The high metabolic demand of adipose tissue also points to the problem of vascularization. Endothelial cell (EC) cotransplantation could be a solution. Human adipose tissue-derived stromal cells were seeded on collagen microcarriers and submitted to adipogenic differentiation ("microparticles"). In a first run of experiments, these microparticles were implanted under the skin of severe combined immunodeficient (SCID) mice (n = 45) with and without the addition of human umbilical vein ECs (HUVECs). A group of carriers without any cells served as control. In a second run, adipose tissue constructs were fabricated by embedding microparticles in fibrin matrix with and without the addition of HUVEC, and were also implanted in SCID mice (n = 30). The mice were sacrificed after 12 days, 4 weeks, and 4 months. Mature adipose tissue, fibrous tissue, and acellular regions were quantified on whole-specimen histological sections. The implantation of microparticles showed a better sustainment of tissue volume and a higher degree of mature adipose tissue compared with adipose tissue constructs. Immunohistology proved obviously perfused human tissue-engineered vessels. There was a limited but not significant advantage in EC cotransplantation after 4 weeks in terms of tissue volume. In groups with EC cotransplantation, there were significantly fewer acellular/necrotic areas after 4 weeks and 4 months. In conclusion, the size of the implanted tissue equivalents is a crucial parameter, affecting volume maintenance and the gain of mature adipose tissue. EC cotransplantation leads to functional stable vascular networks connecting in part to the host vasculature and contributing to tissue perfusion; however, the long-term benefit depends on additional basic conditions that need further research.

Determination of pore size distribution at the cell-hydrogel interface.

BACKGROUND: Analyses of the pore size distribution in 3D matrices such as the cell-hydrogel interface are very useful when studying changes and modifications produced as a result of cellular growth and proliferation within the matrix, as pore size distribution plays an important role in the signaling and microenvironment stimuli imparted to the cells. However, the majority of the methods for the assessment of the porosity in biomaterials are not suitable to give quantitative information about the textural properties of these nano-interfaces. FINDINGS: Here, we report a methodology for determining pore size distribution at the cell-hydrogel interface, and the depth of the matrix modified by cell growth by entrapped HepG(2) cells in microcapsules made of 0.8% and 1.4% w/v alginate. The method is based on the estimation of the shortest distance between two points of the fibril-like network hydrogel structures using image analysis of TEM pictures. Values of pore size distribution determined using the presented method and those obtained by nitrogen physisorption measurements were compared, showing good agreement. A combination of these methodologies and a study of the cell-hydrogel interface at various cell culture times showed that after three days of culture, HepG(2) cells growing in hydrogels composed of 0.8% w/v alginate had more coarse of pores at depths up to 40 nm inwards (a phenomenon most notable in the first 20 nm from the interface). This coarsening phenomenon was weakly observed in the case of cells cultured in hydrogels composed of 1.4% w/v alginate. CONCLUSIONS: The method purposed in this paper allows us to obtain information about the radial deformation of the hydrogel matrix due to cell growth, and the consequent modification of the pore size distribution pattern surrounding the cells, which are extremely important for a wide spectrum of biotechnological, pharmaceutical and biomedical applications.

Image-processing chain for a three-dimensional reconstruction of basal cell carcinomas.

Basal cell carcinoma (BCC) is the most common malignant skin cancer. For a deeper insight into the specific growth patterns of the tumorous tissue in BCC, we have focused on the development of a novel automated image-processing chain for 3D reconstruction of BCC using histopathological serial sections. For fully automatic delineation of the tumor within the tissue, we apply a fuzzy c-means segmentation method. We used a novel multi-grid form of the non-linear registration introduced by Braumann and Kuska in 2005 effectively suppressing registration runs into local minima (possibly caused by diffuse nature of the tumor). Our method was successfully applied in a proof-of-principle study for automated reconstruction.

Local spread of cervical cancer revisited: a clinical and pathological pattern analysis.

BACKGROUND: Local tumor spread of cervical cancer is currently considered as radial progressive intra- and extracervical permeation. For radical tumor resection or radiation the inclusion of a wide envelope of tumor-free tissue is demanded. However, this concept may lead to considerable treatment-related morbidity and does not prevent local relapse. We propose an alternative model of local tumor propagation involving permissive compartments related to embryonic development. METHODS: We analyzed local tumor spread macroscopically and microscopically in consecutive patients with advanced cervical cancer and post-irradiation recurrences. RESULTS: Macroscopically, all 33 stage I B (>2cm) tumors, 40 of 42 stage II tumors and 32 of 44 stage III B tumors were confined to the embryologically defined uterovaginal (Müllerian) compartment. Local tumor permeation deformed the uterovaginal compartment mirroring the mesenchyme distribution of the Müllerian anlage at the corresponding pelvic level in cases of symmetrical tumor growth. Tumor transgression into adjacent compartments mainly involved the embryologically related lower urinary tract. Compartmental transgression was associated with larger tumor size, paradox improvement in oxygenation and an increase in microvessel density. Post-irradiation pelvic relapse landscapes were congruent with the inflated Müllerian compartment. Microscopically, all locally advanced primary cancers and post-irradiation recurrences were confined to the uterovaginal and lower urinary tract compartments. CONCLUSION: Cervical cancer spreads locally within the uterovaginal compartment derived from the Müllerian anlage. Compartment transgression is a relatively late event in the natural disease course associated with distinct phenotypic changes of the tumor. Compartmental tumor permeation suggests a new definition of local treatment radicality.

Characteristics and management of diaphragm involvement in patients with primary advanced-stage ovarian, fallopian tube, or peritoneal cancer.

OBJECTIVES: The aim of this study was to determine the frequency of diaphragm involvement (DI) in cases of International Federation of Gynecology and Obstetrics (FIGO) stage IIIC and IV primary epithelial ovarian, fallopian tube, or peritoneal cancer; the frequency of use of different surgical techniques in managing diaphragm implants; and the procedure-associated morbidity. METHODS: A retrospective analysis of consecutive patients undergoing primary surgery by a single surgical team between January 2005 and June 2007 was accomplished. Patients with tumors of low malignant potential and nonepithelial histologic diagnosis and those who received neoadjuvant chemotherapy were excluded. RESULTS: Thirty-three patients met the inclusion criteria. Diaphragm involvement was found in 91% of the cases. Whereas the left hemidiaphragm is never involved alone, the right side is significantly affected more extensively (P = 0.002) and frequently (alone, 20%; both sides, 80%). The frequency of use of procedures varies considerably in the literature, whereas full-thickness diaphragm resection (DR) had to be performed in 53% of our patients with DI. Diaphragm resection at the left hemidiaphragm and bilateral DRs are very rare in primary cases. A specific histopathologic examination of the DR preparation is desirable. A simple 4-tiered classification of the infiltration depth is proposed. The most frequent complication is serothorax, but a generous indication for intraoperative chest tube placement is solely recommended in cases of DR. CONCLUSIONS: Surgical effort in achieving an optimum cytoreduction could be evaluated more precisely with parameters of DI and diaphragm-related treatment procedures. The usual quality criteria for ovarian cancer surgery, such as residual tumor state and morbidity, are more marked by subjectivity and inconsistent definitions.