Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images

Tissue segmentation is an important pre-requisite for efficient and accurate diagnostics in digital pathology. However, it is well known that whole-slide scanners can fail in detecting all tissue regions, for example due to the tissue type, or due to weak staining because their tissue detection algorithms are not robust enough. In this paper, we introduce two different convolutional neural network architectures for whole slide image segmentation to accurately identify the tissue sections. We also compare the algorithms to a published traditional method. We collected 54 whole slide images with differing stains and tissue types from three laboratories to validate our algorithms. We show that while the two methods do not differ significantly they outperform their traditional counterpart (Jaccard index of 0.937 and 0.929 vs. 0.870, p < 0.01).Comment: Accepted for poster presentation at the IEEE International Symposium on Biomedical Imaging (ISBI) 201

Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks

Manual counting of mitotic tumor cells in tissue sections constitutes one of the strongest prognostic markers for breast cancer. This procedure, however, is time-consuming and error-prone. We developed a method to automatically detect mitotic figures in breast cancer tissue sections based on convolutional neural networks (CNNs). Application of CNNs to hematoxylin and eosin (H&E) stained histological tissue sections is hampered by: (1) noisy and expensive reference standards established by pathologists, (2) lack of generalization due to staining variation across laboratories, and (3) high computational requirements needed to process gigapixel whole-slide images (WSIs). In this paper, we present a method to train and evaluate CNNs to specifically solve these issues in the context of mitosis detection in breast cancer WSIs. First, by combining image analysis of mitotic activity in phosphohistone-H3 (PHH3) restained slides and registration, we built a reference standard for mitosis detection in entire H&E WSIs requiring minimal manual annotation effort. Second, we designed a data augmentation strategy that creates diverse and realistic H&E stain variations by modifying the hematoxylin and eosin color channels directly. Using it during training combined with network ensembling resulted in a stain invariant mitosis detector. Third, we applied knowledge distillation to reduce the computational requirements of the mitosis detection ensemble with a negligible loss of performance. The system was trained in a single-center cohort and evaluated in an independent multicenter cohort from The Cancer Genome Atlas on the three tasks of the Tumor Proliferation Assessment Challenge (TUPAC). We obtained a performance within the top-3 best methods for most of the tasks of the challenge.Comment: Accepted to appear in IEEE Transactions on Medical Imagin

The role of tunneling in enzyme catalysis of C–H activation

AbstractRecent data from studies of enzyme catalyzed hydrogen transfer reactions implicate a new theoretical context in which to understand C–H activation. This is much closer to the Marcus theory of electron transfer, in that environmental factors influence the probability of effective wave function overlap from donor to acceptor atoms. The larger size of hydrogen and the availability of three isotopes (H, D and T) introduce a dimension to the kinetic analysis that is not available for electron transfer. This concerns the role of gating between donor and acceptor atoms, in particular whether the system in question is able to tune distance between reactants to achieve maximal tunneling efficiency. Analysis of enzyme systems is providing increasing evidence of a role for active site residues in optimizing the inter-nuclear distance for nuclear tunneling. The ease with which this optimization can be perturbed, through site-specific mutagenesis or an alteration in reaction conditions, is also readily apparent from an analysis of the changes in the temperature dependence of hydrogen isotope effects

Evaluation of the pharmacokinetics of prednisolone in paediatric patients with acute lymphoblastic leukaemia treated according to Dutch Childhood Oncology Group protocols and its relation to treatment response

Glucocorticoids form the backbone of paediatric acute lymphoblastic leukaemia (ALL) treatment. Many studies have been performed on steroid resistance; however, few studies have addressed the relationship between dose, concentration and clinical response. The aim of the present study was to evaluate the pharmacokinetics of prednisolone in the treatment of paediatric ALL and the correlation with clinical parameters. A total of 1028 bound and unbound prednisolone plasma concentrations were available from 124 children (aged 0–18 years) with newly diagnosed ALL enrolled in the Dutch Childhood Oncology Group studies. A population pharmacokinetic model was developed and post hoc area under the curve (AUC) was tested against treatment outcome parameters. The pharmacokinetics of unbound prednisolone in plasma was best described with allometric scaling and saturable binding to proteins. Plasma protein binding decreased with age. The AUC of unbound prednisolone was not associated with any of the disease parameters or treatment outcomes. Unbound prednisolone plasma concentrations correlated with age. No effect of exposure on clinical treatment outcome parameters was observed and does not substantiate individualised dosing. Poor responders, high-risk and relapsed patients showed a trend towards lower exposure compared to good responders. However, the group of poor responders was small and requires further research.</p

Population Pharmacokinetics and Pharmacodynamics of Ciprofloxacin Prophylaxis in Pediatric Acute Lymphoblastic Leukemia Patients

Background. Ciprofloxacin is used as antimicrobial prophylaxis in pediatric acute lymphoblastic leukemia (ALL) to decrease infections with gram-negative bacteria. However, there are no clear guideline

Organizational culture, team climate and diabetes care in small office-based practices

Contains fulltext : 71456.pdf ( ) (Open Access)BACKGROUND: Redesigning care has been proposed as a lever for improving chronic illness care. Within primary care, diabetes care is the most widespread example of restructured integrated care. Our goal was to assess to what extent important aspects of restructured care such as multidisciplinary teamwork and different types of organizational culture are associated with high quality diabetes care in small office-based general practices. METHODS: We conducted cross-sectional analyses of data from 83 health care professionals involved in diabetes care from 30 primary care practices in the Netherlands, with a total of 752 diabetes mellitus type II patients participating in an improvement study. We used self-reported measures of team climate (Team Climate Inventory) and organizational culture (Competing Values Framework), and measures of quality of diabetes care and clinical patient characteristics from medical records and self-report. We conducted multivariate analyses of the relationship between culture, climate and HbA1c, total cholesterol, systolic blood pressure and a sum score on process indicators for the quality of diabetes care, adjusting for potential patient- and practice level confounders and practice-level clustering. RESULTS: A strong group culture was negatively associated to the quality of diabetes care provided to patients (beta = -0.04; p = 0.04), whereas a more 'balanced culture' was positively associated to diabetes care quality (beta = 5.97; p = 0.03). No associations were found between organizational culture, team climate and clinical patient outcomes. CONCLUSION: Although some significant associations were found between high quality diabetes care in general practice and different organizational cultures, relations were rather marginal. Variation in clinical patient outcomes could not be attributed to organizational culture or teamwork. This study therefore contributes to the discussion about the legitimacy of the widespread idea that aspects of redesigning care such as teamwork and culture can contribute to higher quality of care. Future research should preferably combine quantitative and qualitative methods, focus on possible mediating or moderating factors and explore the use of instruments more sensitive to measure such complex constructs in small office-based practices

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms