Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Breast cancer prognostic classification in the molecular era: the role of histological grade.

Breast cancer is a heterogeneous disease with varied morphological appearances, molecular features, behavior, and response to therapy. Current routine clinical management of breast cancer relies on the availability of robust clinical and pathological prognostic and predictive factors to support clinical and patient decision making in which potentially suitable treatment options are increasingly available. One of the best-established prognostic factors in breast cancer is histological grade, which represents the morphological assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of breast cancers. Genome-wide microarray-based expression profiling studies have unraveled several characteristics of breast cancer biology and have provided further evidence that the biological features captured by histological grade are important in determining tumor behavior. Also, expression profiling studies have generated clinically useful data that have significantly improved our understanding of the biology of breast cancer, and these studies are undergoing evaluation as improved prognostic and predictive tools in clinical practice. Clinical acceptance of these molecular assays will require them to be more than expensive surrogates of established traditional factors such as histological grade. It is essential that they provide additional prognostic or predictive information above and beyond that offered by current parameters. Here, we present an analysis of the validity of histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers.

Results of the 2nd scientific workshop of the ECCO (III): basic mechanisms of intestinal healing.

The second scientific workshop of the European Crohn's and Colitis Organization (ECCO) focused on the relevance of intestinal healing for the disease course of inflammatory bowel disease (IBD). The objective was to better understand basic mechanisms, markers for disease prediction, detection and monitoring of intestinal healing, impact of intestinal healing on the disease course of IBD as well as therapeutic strategies. The results of this workshop are presented in four separate manuscripts. This section describes basic mechanisms of intestinal healing, identifies open questions in the field and provides a framework for future studies.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

A genetic algorithm to ensemble feature selection

We are going to implement the "GA-SEFS" by Tsymbal and analyse experimentally its performance depending on the classifier algorithms used in the fitness function (NB, MNge, SMO). We are also going to study the effect of adding to the fitness function a measure to control complexity of the base classifiers.

Automatic Detection of Non-deverbal Event Nouns for Quick Lexicon Production

In this work we present the results of experimental work on the development of lexical class-based lexica by automatic means. Our purpose is to assess the use of linguistic lexical-class based information as a feature selection methodology for the use of classifiers in quick lexical development. The results show that the approach can help reduce the human effort required in the development of language resources significantly.

Développement d'une puce à ADN métabolique et application à l'étude d'un modèle murin d'obésité et de diabète de type II

Résumé tout public : Le développement du diabète de type II et de l'obésité est causé par l'interaction entre des gènes de susceptibilité et des facteurs environnementaux, en particulier une alimentation riche en calories et une activité physique insuffisante. Afín d'évaluer le rôle de l'alimentation en absence d'hétérogénéité génétique, nous avons nourri une lignée de souris génétiquement pure avec un régime extrêmement gras. Ce régime a conduit à l'établissement de différents phénotypes parmi ces souris, soit : un diabète et une obésité (ObD), un diabète mais pas d'obésité (LD) ou ni un diabète, ni une obésité (LnD). Nous avons fait l'hypothèse que ces adaptations différentes au stress nutritionnel induit par le régime gras étaient dues à l'établissement de programmes génétiques différents dans les principaux organes impliqués dans le maintien de l'équilibre énergétique. Afin d'évaluer cette hypothèse, nous avons développé une puce à ADN contenant approximativement 700 gènes du métabolisme. Cette puce à ADN, en rendant possible la mesure simultanée de l'expression de nombreux gènes, nous a permis d'établir les profils d'expression des gènes caractéristiques de chaque groupe de souris nourries avec le régime gras, dans le foie et le muscle squelettique. Les données que nous avons obtenues à partir de ces profils d'expression ont montré que des changements d'expression marqués se produisaient dans le foie et le muscle entre les différents groupes de souris nourries avec le régime gras. Dans l'ensemble, ces changements suggèrent que l'établissement du diabète de type II et de l'obésité induits par un régime gras est associé à une synthèse accrue de lipides par le foie et à un flux augmenté de lipides du foie jusqu'à la périphérie (muscles squelettiques). Dans un deuxième temps, ces profils d'expression des gènes ont été utilisés pour sélectionner un sous-ensemble de gènes suffisamment discriminants pour pouvoir distinguer entre les différents phénotypes. Ce sous-ensemble de gènes nous a permis de construire un classificateur phénotypique capable de prédire avec une précision relativement élevée le phénotype des souris. Dans le futur, de tels « prédicteurs » basés sur l'expression des gènes pourraient servir d'outils pour le diagnostic de pathologies liées au métabolisme. Summary: Aetiology of obesity and type II diabetes is multifactorial, involving both genetic and environmental factors, such as calory-rich diets or lack of exercice. Genetically homogenous C57BL/6J mice fed a high fat diet (HFD) up to nine months develop differential adaptation, becoming either obese and diabetic (ObD) or remaining lean in the presence (LD) or absence (LnD) of diabetes development. Each phenotype is associated with diverse metabolic alterations, which may result from diverse molecular adaptations of key organs involved in the control of energy homeostasis. In this study, we evaluated if specific patterns of gene expression could be associated with each different phenotype of HFD mice in the liver and the skeletal muscles. To perform this, we constructed a metabolic cDNA microarray containing approximately 700 cDNA representing genes involved in the main metabolic pathways of energy homeostasis. Our data indicate that the development of diet-induced obesity and type II diabetes is linked to some defects in lipid metabolism, involving a preserved hepatic lipogenesis and increased levels of very low density lipoproteins (VLDL). In skeletal muscles, an increase in fatty acids uptake, as suggested by the increased expression of lipoprotein lipase, would contribute to the increased level of insulin resistance observed in the ObD mice. Conversely, both groups of lean mice showed a reduced expression in lipogenic genes, particularly stearoyl-CoA desaturase 1 (Scd-1), a gene linked to sensitivity to diet-induced obesity. Secondly, we identified a subset of genes from expression profiles that classified with relative accuracy the different groups of mice. Such classifiers may be used in the future as diagnostic tools of each metabolic state in each tissue. Résumé Développement d'une puce à ADN métabolique et application à l'étude d'un modèle murin d'obésité et de diabète de type II L'étiologie de l'obésité et du diabète de type II est multifactorielle, impliquant à la fois des facteurs génétiques et environnementaux, tels que des régimes riches en calories ou un manque d'exercice physique. Des souris génétiquement homogènes C57BL/6J nourries avec un régime extrêmement gras (HFD) pendant 9 mois développent une adaptation métabolique différentielle, soit en devenant obèses et diabétiques (ObD), soit en restant minces en présence (LD) ou en absence (LnD) d'un diabète. Chaque phénotype est associé à diverses altérations métaboliques, qui pourraient résulter de diverses adaptations moléculaires des organes impliqués dans le contrôle de l'homéostasie énergétique. Dans cette étude, nous avons évalué si des profils d'expression des gènes dans le foie et le muscle squelettique pouvaient être associés à chacun des phénotypes de souris HFD. Dans ce but, nous avons développé une puce à ADN métabolique contenant approximativement 700 ADNc représentant des gènes impliqués dans les différentes voies métaboliques de l'homéostasie énergétique. Nos données indiquent que le développement de l'obésité et du diabète de type II induit par un régime gras est associé à certains défauts du métabolisme lipidique, impliquant une lipogenèse hépatique préservée et des niveaux de lipoprotéines de très faible densité (VLDL) augmentés. Au niveau du muscle squelettique, une augmentation du captage des acides gras, suggéré par l'expression augmentée de la lipoprotéine lipase, contribuerait à expliquer la résistance à l'insuline plus marquée observée chez les souris ObD. Au contraire, les souris minces ont montré une réduction marquée de l'expression des gènes lipogéniques, en particulier de la stéaroyl-CoA désaturase 1 (scd-1), un gène associé à la sensibilité au développement de l'obésité par un régime gras. Dans un deuxième temps, nous avons identifié un sous-ensemble de gènes à partir des profils d'expression, qui permettent de classifier avec une précision relativement élevée les différents groupes de souris. De tels classificateurs pourraient être utilisés dans le futur comme outils pour le diagnostic de l'état métabolique d'un tissu donné.

Structural and Resting State Functional Connectivity of the Subthalamic Nucleus: Identification of Motor STN Parts and the Hyperdirect Pathway.

Deep brain stimulation (DBS) for Parkinson's disease often alleviates the motor symptoms, but causes cognitive and emotional side effects in a substantial number of cases. Identification of the motor part of the subthalamic nucleus (STN) as part of the presurgical workup could minimize these adverse effects. In this study, we assessed the STN's connectivity to motor, associative, and limbic brain areas, based on structural and functional connectivity analysis of volunteer data. For the structural connectivity, we used streamline counts derived from HARDI fiber tracking. The resulting tracks supported the existence of the so-called "hyperdirect" pathway in humans. Furthermore, we determined the connectivity of each STN voxel with the motor cortical areas. Functional connectivity was calculated based on functional MRI, as the correlation of the signal within a given brain voxel with the signal in the STN. Also, the signal per STN voxel was explained in terms of the correlation with motor or limbic brain seed ROI areas. Both right and left STN ROIs appeared to be structurally and functionally connected to brain areas that are part of the motor, associative, and limbic circuit. Furthermore, this study enabled us to assess the level of segregation of the STN motor part, which is relevant for the planning of STN DBS procedures.

Comparative testing of a miniature diffusion size classifier to assess airborne ultrafine particles under field conditions

Miniature diffusion size classifiers (miniDiSC) are novel handheld devices to measure ultrafine particles (UFP). UFP have been linked to the development of cardiovascular and pulmonary diseases; thus, detection and quantification of these particles are important for evaluating their potential health hazards. As part of the UFP exposure assessments of highwaymaintenance workers in western Switzerland, we compared a miniDiSC with a portable condensation particle counter (P-TRAK). In addition, we performed stationary measurements with a miniDiSC and a scanning mobility particle sizer (SMPS) at a site immediately adjacent to a highway. Measurements with miniDiSC and P-TRAK correlated well (correlation of r = 0.84) but average particle numbers of the miniDiSC were 30%âeuro"60% higher. This difference was significantly increased for mean particle diameters below 40 nm. The correlation between theminiDiSC and the SMPSduring stationary measurements was very high (r = 0.98) although particle numbers from the miniDiSC were 30% lower. Differences between the three devices were attributed to the different cutoff diameters for detection. Correction for this size dependent effect led to very similar results across all counters.We did not observe any significant influence of other particle characteristics. Our results suggest that the miniDiSC provides accurate particle number concentrations and geometric mean diameters at traffic-influenced sites, making it a useful tool for personal exposure assessment in such settings.

Sistema de información sobre exposición ocupacional a plaguicidas en Catalunya

Objetivo. Diseñar un sistema de información sobre la exposición ocupacional a plaguicidas en Catalunya (PLAGCAT) y evaluar la factibilidad de los procedimientos propuestos para su alimentación.

Desarrollo de una matriz empleo-exposición (MEE) para describir la exposición de los trabajadores a plaguicidas en España (1996-2005)

Introducción: En 2005 se consumían en España más de 100.000 toneladas/año de plaguicidas, en actividades tan diversas como la agricultura y la ganadería o el tratamiento de la madera y la gestión de plagas estructurales. A pesar de los demostrados efectos negativos de estas sustancias sobre la salud de las personas, existe muy poca información relativa a los niveles y la frecuencia de exposición de los trabajadores expuestos, así como de las ocupaciones más afectadas. Este trabajo tiene como objetivo recopilar la información disponible sobre exposición laboral a plaguicidas en España, en forma de una matriz empleo-exposición (MEE), un sistema de información que permite ordenar de forma sistemática la información más relevante sobre ocupaciones, agentes, prevalencia y nivel/intensidad de exposición en un determinado contexto (país, periodo, etc.).

AWSum-Combining Classification with Knowledge Aquisition

Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the^way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whilst providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.

Treatment of autoinflammatory diseases: results from the Eurofever Registry and a literature review.

OBJECTIVE: To evaluate the response to treatment of autoinflammatory diseases from an international registry and an up-to-date literature review. METHODS: The response to treatment was studied in a web-based registry in which clinical information on anonymised patients with autoinflammatory diseases was collected retrospectively as part of the Eurofever initiative. Participating hospitals included paediatric rheumatology centres of the Paediatric Rheumatology International Trial Organisation network and adult centres with a specific interest in autoinflammatory diseases. The following diseases were included: familial Mediterranean fever (FMF), cryopyrin-associated periodic syndromes (CAPS), tumour necrosis factor (TNF)-receptor associated periodic syndrome (TRAPS), mevalonate kinase deficiency (MKD), pyogenic arthritis pustulosis acne (PAPA) syndrome, deficiency of interleukin-1 receptor antagonist (DIRA), NLRP12-related periodic fever and periodic fever aphthosis pharyngitis adenitis (PFAPA) syndrome. Cases were independently validated by experts for each disease. A literature search regarding treatment of the abovementioned diseases was also performed using Medline and Embase. RESULTS: 22 months from the beginning of the enrolment, complete information on 496 validated patients was available. Data from the registry in combination with evidence from the literature confirmed that colchicine is the treatment of choice for FMF and IL-1 blockade for DIRA and CAPS. Corticosteroids on demand probably represent a valid therapeutic strategy for PFAPA, but also for MKD and TRAPS. Patients with poorly controlled MKD, TRAPS, PAPA or FMF may benefit from IL-1 blockade; anti-TNF treatment may represent a possible valuable alternative. CONCLUSIONS: In the absence of high-grade evidence, these results could serve as a basis for therapeutic guidelines and to identify candidate drugs for future therapeutic trials.