Robust Automated Tumour Segmentation on Histological and Immunohistochemical Tissue Images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification

Drawings of very preterm-born children at 5 years of age: a first impression of cognitive and motor development?

INTRODUCTION: The aim of this study was to examine differences in drawing skills between very preterm and term children, and to determine whether very preterm children's cognitive and motor development is reflected in the draw-a-person test (DAP) at age 5. Seventy-two very preterm children (birth weight <1,500 g and/or gestational age <32 weeks) and 60 term children at 5 years of age were compared on the DAP. Cognitive and motor skills of the very preterm children had been assessed four times, at 1/2, 1, 2, and 5 years of age. Very preterm children showed a developmental delay in drawing ability. Structural equation modeling revealed a positive relation between both cognitive as well as motor development and the DAP. CONCLUSION: The DAP could be a crude parameter for evaluating cognitive and motor deficits of very preterm children. A worrisome result should be followed by more standardized tests measuring cognitive and motor skill

Canine classical seminoma: a specific malignant type with human classifications is highly correlated with tumor angiogenesis

<p>Abstract</p> <p>Background</p> <p>Human seminoma is classified as classical seminoma (SE) and spermatocytic seminoma (SS). Human SE is known to be more malignant and metastasizing more frequently than SS. Tumor angiogenesis is highly related with tumor progression and metastasis, with microvessel density (MVD) being an important parameter of metastatic potential. Canine seminoma is not yet well-established as SE or SS type including correlation with angiogenesis. We classified canine SE and SS, and then compared them to tumor associated vessels.</p> <p>Methods</p> <p>Twenty-three cases of canine seminomas (2 intratubular, 9 diffuse, and 12 intratubular/diffuse seminomas showing both intratubular and diffuse patterns) were classified as SE or SS by immunohistochemistry (IHC) using monoclonal antibody against PLAP and by PAS stain. The histopathological data were then compared to see if there was a correlation with SE or SS. Angiogenesis of seminomas were evaluated by immunohistochemical assay using polyclonal antibody against Von Willebrand factor (vWF) and by calculating the means of MVD, vessels area and perimeters using computerized image analysis. Statistical Package for Social Sciences (SPSS) program was used for various statistical analyses.</p> <p>Results</p> <p>The numbers of PLAP+/PAS+ canine SEs were 8/23 (34.8%) and PLAP-/PAS- SSs were 15/23 (61.2%). All SE cases (8/8, 100%) were intratubular/diffuse types. SS types included 2 intratubular (2/15, 13.3%), 9 diffuse (9/15, 60%), and 4 intratubular/diffuse (4/15, 26.7%) types. MVD and vascular parameters in SEs were significantly higher than in SSs, showing the highest value in the intratubular/diffuse type. Seminomas observed with neoplastic cells invasion of vessels presented higher perimeter and area values than seminomas without conformed neoplastic cells invasion.</p> <p>Conclusion</p> <p>In this study, we demonstrated a positive relationship between canine SE and tumor angiogenesis. Furthermore, we also showed that a tumor cells invasion of vessels were a correlated vascular parameter. Although metastasis of canine seminomas has rarely been reported, our results support that canine SE could have high metastatic potential similar to the human counterpart. Further studies are required to clarify the relationship between canine SE and clinical data with metastatic factors.</p

Chemogenomic Analysis of G-Protein Coupled Receptors and Their Ligands Deciphers Locks and Keys Governing Diverse Aspects of Signalling

Understanding the molecular mechanism of signalling in the important super-family of G-protein-coupled receptors (GPCRs) is causally related to questions of how and where these receptors can be activated or inhibited. In this context, it is of great interest to unravel the common molecular features of GPCRs as well as those related to an active or inactive state or to subtype specific G-protein coupling. In our underlying chemogenomics study, we analyse for the first time the statistical link between the properties of G-protein-coupled receptors and GPCR ligands. The technique of mutual information (MI) is able to reveal statistical inter-dependence between variations in amino acid residues on the one hand and variations in ligand molecular descriptors on the other. Although this MI analysis uses novel information that differs from the results of known site-directed mutagenesis studies or published GPCR crystal structures, the method is capable of identifying the well-known common ligand binding region of GPCRs between the upper part of the seven transmembrane helices and the second extracellular loop. The analysis shows amino acid positions that are sensitive to either stimulating (agonistic) or inhibitory (antagonistic) ligand effects or both. It appears that amino acid positions for antagonistic and agonistic effects are both concentrated around the extracellular region, but selective agonistic effects are cumulated between transmembrane helices (TMHs) 2, 3, and ECL2, while selective residues for antagonistic effects are located at the top of helices 5 and 6. Above all, the MI analysis provides detailed indications about amino acids located in the transmembrane region of these receptors that determine G-protein signalling pathway preferences

Deep convolutional gaussian mixture model for stain-color normalization of histopathological images

\u3cp\u3eAutomated microscopic analysis of stained histopathological images is degraded by the amount of color and intensity variations in data. This paper presents a novel unsupervised probabilistic approach by integrating a convolutional neural network (CNN) and the Gaussian mixture model (GMM) in a unified framework, which jointly optimizes the modeling and normalizing the color and intensity of hematoxylin- and eosin-stained (H&amp;E) histological images. In contrast to conventional GMM-based methods that are applied only on the color distribution of data for stain color normalization, our proposal learns how to cluster the tissue structures according to their shape and appearance and simultaneously fits a multivariate GMM to the data. This approach is more robust than standard GMM in the presence of strong staining variations because fitting the GMM is conditioned on the appearance of tissue structures in the density channel of an image. Performing a gradient descent optimization in an end-to-end learning, the network learns to maximize the log-likelihood of data given estimated parameters of multivariate Gaussian distributions. Our method does not need ground truth, shape and color assumptions of image contents or manual tuning of parameters and thresholds which makes it applicable to a wide range of histopathological images. Experiments show that our proposed method outperforms the state-of-the-art algorithms in terms of achieving a higher color constancy.\u3c/p\u3

MIB1 expression in basal cell layer: a diagnostic tool to identify premalignancies of the vulva.

Contains fulltext : 51438.pdf (publisher's version ) (Closed access)Lichen sclerosus, high-grade usual vulvar intraepithelial neoplasia (VIN) and differentiated VIN have a different malignant potential. The objective of this study was to quantify the proliferative activity in the basal region of the epithelium of vulvar premalignancies. Furthermore, we investigated whether MIB1 expression in the basal region of vulvar epithelium can be helpful in diagnosing differentiated VIN, which may be hard to discern from normal epithelium. MIB1 was used to immunohistochemically visualise proliferating cells within formalin-fixed, paraffin-embedded, archival tissue sections of different vulvar premalignancies (N=48) and normal vulvar epithelium (N=16). Automatic digital image analysis software was developed to quantify the proliferating fraction in different parts of the epithelium (MIB1 positivity index). MIB1 expression differed among the various vulvar premalignancies; a MIB1-negative basal cell layer was a distinct feature of normal vulvar epithelium. No MIB1-negative basal cell layer was noted in differentiated VIN or other vulvar premalignancies. Owing to this negative cell layer, the MIB1 proliferation index in normal vulvar epithelium was significantly lower than in vulvar premalignancies. In conclusion, MIB1 expression can be a helpful tool in diagnosing a premalignancy and has additional value especially to distinguish differentiated VIN neoplasia from normal vulvar epithelium, but cannot explain the differences in malignant potential