A comprehensive methodology for determining the most informative mammographic features

This study aims to determine the most informative mammographic features for breast cancer diagnosis using mutual information (MI) analysis. Our Health Insurance Portability and Accountability Act-approved database consists of 44,397 consecutive structured mammography reports for 20,375 patients collected from 2005 to 2008. The reports include demographic risk factors (age, family and personal history of breast cancer, and use of hormone therapy) and mammographic features from the Breast Imaging Reporting and Data System lexicon. We calculated MI using Shannon's entropy measure for each feature with respect to the outcome (benign/malignant using a cancer registry match as reference standard). In order to evaluate the validity of the MI rankings of features, we trained and tested naïve Bayes classifiers on the feature with tenfold cross-validation, and measured the predictive ability using area under the ROC curve (AUC). We used a bootstrapping approach to assess the distributional properties of our estimates, and the DeLong method to compare AUC. Based on MI, we found that mass margins and mass shape were the most informative features for breast cancer diagnosis. Calcification morphology, mass density, and calcification distribution provided predictive information for distinguishing benign and malignant breast findings. Breast composition, associated findings, and special cases provided little information in this task. We also found that the rankings of mammographic features with MI and AUC were generally consistent. MI analysis provides a framework to determine the value of different mammographic features in the pursuit of optimal (i.e., accurate and efficient) breast cancer diagnosis. © 2013 Society for Imaging Informatics in Medicine

Modeling the natural history of ductal carcinoma in situ based on population data

Background: The incidence of ductal carcinoma in situ (DCIS) has increased substantially since the introduction of mammography screening. Nevertheless, little is known about the natural history of preclinical DCIS in the absence of biopsy or complete excision. Methods: Two well-established population models evaluated six possible DCIS natural history submodels. The submodels assumed 30%, 50%, or 80% of breast lesions progress from undetectable DCIS to preclinical screen-detectable DCIS; each model additionally allowed or prohibited DCIS regression. Preclinical screen-detectable DCIS could also progress to clinical DCIS or invasive breast cancer (IBC). Applying US population screening dissemination patterns, the models projected age-specific DCIS and IBC incidence that were compared to Surveillance, Epidemiology, and End Results data. Models estimated mean sojourn time (MST) in the preclinical screen-detectable DCIS state, overdiagnosis, and the risk of progression from preclinical screen-detectable DCIS. Results: Without biopsy and surgical excision, the majority of DCIS (64-100%) in the preclinical screen-detectable state progressed to IBC in submodels assuming no DCIS regression (36-100% in submodels allowing for DCIS regression). DCIS overdiagnosis differed substantially between models and submodels, 3.1-65.8%. IBC overdiagnosis ranged 1.3-2.4%. Submodels assuming DCIS regression resulted in a higher DCIS overdiagnosis than submodels without DCIS regression. MST for progressive DCIS varied between 0.2 and 2.5 years. Conclusions: Our findings suggest that the majority of screen-detectable but unbiopsied preclinical DCIS lesions progress to IBC and that the MST is relatively short. Nevertheless, due to the heterogeneity of DCIS, more research is needed to understand the progression of DCIS by grades and molecular subtypes

Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set

Using quantitative radiomics, we demonstrate that computer-extracted magnetic resonance (MR) image-based tumor phenotypes can be predictive of the molecular classification of invasive breast cancers. Radiomics analysis was performed on 91 MRIs of biopsy-proven invasive breast cancers from National Cancer Institute’s multi-institutional TCGA/TCIA. Immunohistochemistry molecular classification was performed including estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and for 84 cases, the molecular subtype (normal-like, luminal A, luminal B, HER2-enriched, and basal-like). Computerized quantitative image analysis included: three-dimensional lesion segmentation, phenotype extraction, and leave-one-case-out cross validation involving stepwise feature selection and linear discriminant analysis. The performance of the classifier model for molecular subtyping was evaluated using receiver operating characteristic analysis. The computer-extracted tumor phenotypes were able to distinguish between molecular prognostic indicators; area under the ROC curve values of 0.89, 0.69, 0.65, and 0.67 in the tasks of distinguishing between ER+ versus ER−, PR+ versus PR−, HER2+ versus HER2−, and triple-negative versus others, respectively. Statistically significant associations between tumor phenotypes and receptor status were observed. More aggressive cancers are likely to be larger in size with more heterogeneity in their contrast enhancement. Even after controlling for tumor size, a statistically significant trend was observed within each size group (P = 0.04 for lesions ≤ 2 cm; P = 0.02 for lesions >2 to≤ 5 cm) as with the entire data set (P-value = 0.006) for the relationship between enhancement texture (entropy) and molecular subtypes (normal-like, luminal A, luminal B, HER2-enriched, basal-like). In conclusion, computer-extracted image phenotypes show promise for high-throughput discrimination of breast cancer subtypes and may yield a quantitative predictive signature for advancing precision medicine

Modeling Ductal Carcinoma In Situ (DCIS): An Overview of CISNET Model Approaches

Background. Ductal carcinoma in situ (DCIS) can be a precursor to invasive breast cancer. Since the advent of screening mammography in the 1980’s, the incidence of DCIS has increased dramatically. The value of screen detection and treatment of DCIS, however, is a matter of controversy, as it is unclear the extent to which detection and treatment of DCIS prevents invasive disease and reduces breast cancer mortality. The aim of this paper is to provide an overview of existing Cancer Intervention and Surveillance Modelling Network (CISNET) modeling approaches for the natural history of DCIS, and to compare these to other modeling approaches reported in the literature. Design. Five of the 6 CISNET models currently include DCIS. Most models assume that some, but not all, lesions progress to invasive cancer. The natural history of DCIS cannot be directly observed and the CISNET models differ in their assumptions and in the data sources used to estimate the DCIS model parameters. Results. These model differences translate into variation in outcomes, such as the amount of overdiagnosis of DCIS, with estimates ranging from 34% to 72% for biennial screening from ages 50 to 74 y. The other models described in the literature also report a large range in outcomes, with progression rates varying from 20% to 91%. Limitations. DCIS grade was not yet included in the CISNET models. Conclusion. In the future, DCIS data by grade from active surveillance trials, the development of predictive markers of progression probability, and evidence from other screening modalities, such as tomosynthesis, may be used to inform and improve the models’ representation of DCIS, and might lead to convergence of the model estimates. Until then, the CISNET model results consistently show a considerable amount of overdiagnosis of DCIS, supporting the safety and value of observational trials for low-risk DCIS

Alteração das características biológicas dos biótipos de azevém (Lolium multiflorum) ocasionada pela resistência ao herbicida glyphosate Change in the biological characteristics of ryegrass (Lolium multiflorum) biotypes caused by resistance to the herbicide glyphosate

A resistência de biótipos de azevém ao herbicida glyphosate está alterando o manejo da vegetação de cobertura do solo em pomares de maçã. O objetivo deste trabalho foi determinar a dose de glyphosate necessária para reduzir 50% do acúmulo de matéria seca (GR50), a resposta do biótipo resistente e sensível a herbicidas graminicidas e o acúmulo de matéria seca destes biótipos durante o ciclo. Para isso, foram conduzidos três experimentos. No primeiro, os tratamentos constaram de doses crescentes de glyphosate aplicadas sobre plantas dos biótipos resistente e sensível para determinar o GR50. No segundo experimento, os tratamentos constaram de doses dos herbicidas glyphosate, haloxyfop-r, diclofop, fluazifop-p, fenoxaprop-p e paraquat. No terceiro experimento, sementes dos biótipos resistente e sensível foram semeadas em recipientes com capacidade para 10 L e as plantas originadas delas foram colhidas quinzenalmente, para determinação da matéria seca da parte aérea, radicular e total. Como resultados, foi obtido GR50 de 287,5 e de 4.833,5 g e.a. ha-1 de glyphosate para os biótipos sensível e resistente, respectivamente, e verificou-se que existem diferenças significativas na resposta dos biótipos aos herbicidas graminicidas, dependendo da dose utilizada. Além disso, o biótipo sensível evidenciou maior capacidade de acúmulo de matéria seca e produção de sementes. Constatouse, assim, fator de resistência (FR) de 16,8 e que o mecanismo de resistência provoca alterações nas características biológicas do biótipo resistente e afeta a sensibilidade deste aos herbicidas graminicidas.<br>The identification of ryegrass biotypes resistant to glyphosate is causing changes in weed management in apple orchards. Three experiments were carried out to determine the GR50 of the biotypes, to grass herbicides and dry matter accumulation. The first experiment tested different rates of glyphosate. Their effects on GR50 dry matter accumulation by the biotype were assessed. In the second experiment different rates of glyphosate and grass herbicides were tested: glyphosate, haloxyfop-r, diclofop, fluazifop-p, fenoxaprop-p and paraquat. A third experiments was carried out under glasshouse conditions to determine the curve of dry matter accumulation. The results showed GR50 of 287.5 and 4,833.5 g e. a. ha-1 of glyphosate for the sensitive and resistant biotypes, respectively. The results showed that the resistant factor (RF) was 16.8 and that the resistance mechanism alters the biological characteristics of the resistant biotype affecting its sensitivity to grass herbicides

Fine structure of the retinal pigment epithelium and cones of Antarctic fish Notohenia coriiceps Richardson in light and dark-conditions

The Antarctic fish Notothenia coriiceps Richardson, 1844 lives in an environment of daily and annual photic variation and retina cells have to adjust morphologically to environmental luminosity. After seven day dark or seven day light acclimation of two groups of fish, retinas were extracted and processed for light and transmission electron microscopy. In seven day dark adapted, retina pigment epithelium melanin granules were aggregated at the basal region of cells, and macrophages were seen adjacent to the apical microvilli, between the photoreceptors. In seven day light adapted epithelium, melanin granules were inside the apical microvilli of epithelial cells and macrophages were absent. The supranuclear region of cones adapted to seven day light had less electron dense cytoplasm, and an endoplasmic reticulum with broad tubules. The mitochondria in the internal segment of cones adapted to seven day light were larger, and less electron dense. The differences in the morphology of cones and pigment epithelial cells indicate that N. coriiceps has retinal structural adjustments presumably optimizing vision in different light conditions.<br>O peixe Antártico Notothenia coriiceps Richardson, 1844 habita meios com variações fóticas diária e anual e as células da retina se adaptam morfologicamente a esta luminosidade ambiental. Dois grupos de peixes foram aclimatados durante sete dias à luz constante ou ao escuro constante. Após secção medular, as retinas foram extraídas e processadas para microscopia de luz e microscopia eletrônica de transmissão. No epitélio pigmentar da retina adaptado sete dias ao escuro, os pigmentos de melanina agregam-se na base coroidal das células epiteliais pigmentares e macrófagos são encontrados no interior do processos apicais entre as células fotorreceptoras. No epitélio adaptado sete dias à luz os pigmentos de melanina se dispõem ao longo das projeções apicais das células epiteliais pigmentares e os macrófagos são ausentes. A região supranuclear dos cones adaptados sete dias à luz possui um citoplasma menos elétron denso devido a presença de canais do retículo endoplasmático que se dilatam aumentando o seu lúmen. As mitocôndrias existentes no segmento interno dos cones adaptados à luz são maiores, e menos elétron densas. As diferenças na morfologia dos cones e nas células epiteliais pigmentares indicam que N. coriiceps possui mecanismos celulares de ajustes na retina provavelmente otimizando a capacidade visual em diferentes situações de luz

Dynamic fiscal policies and unemployment in a simple endogenous growth model

This paper analyzes the growth and employment effects of dynamic fiscal policies in an overlapping generations model with endogenous growth and imperfect labour markets. With balanced-budget policies, the modelled closed economy grows at a constant rate which is higher, the lower are the labour tax rate and the unemployment rate. Constant-flow budget policies are not feasible, while government Ponzi games are feasible only if economic agents have implausibly high savings rates. Furthermore, while constant-stock fiscal policies are sustainable, an increase in the debt-to-capital ratio is accompanied by higher taxes, a rise in unemployment and lower economic growth. Copyright Springer Science + Business Media, LLC 2006Unemployment, Public debt, Economic growth, Fiscal policy,