Estudi epidemiològic de l'obesitat de 1r d'ESO de l'IES Pedraforca

Treball de recerca realitzat per una alumna d'ensenyament secundari i guardonat amb un Premi CIRIT per fomentar l'esperit científic del Jovent l'any 2009. L'obesitat és una malaltia crònica que es caracteritza per un augment de la massa grassa i en conseqüència per un augment de pes. En el segle XXI aquesta malaltia, considerada epidèmia, està arribant a la població infantil i adolescent, i ha cridat l'atenció de totes les institucions de salut pública que estan lluitant per evitar aquesta alta prevalença d'obesitat i sobrepès. Aquest estudi confirma que existeix un alt percentatge d'obesitat i sobrepès en l'edat infantil i que està relacionat amb factors de risc (alguns modificables) que poden ser clau per a evitar aquesta malaltia. El mètode emprat és la realització d’un estudi epidemiològic transversal sobre una mostra de nens compresa en 39 individus de 12 a 14 anys d'edat. Es van determinar el pes, la talla, el plec bicipital i tricipital, l'ample del canell i del colze, a més de la realització d'una enquesta sobre hàbits alimentaris en l’esmorzar i dades socioculturals. L'obesitat i el sobrepès es van definir com resultats de IMC iguals als percentils 85 i 97 de les taules Orbegozo, respectivament. Els resultats van mostrar una prevalença de sobrepès i obesitat en la nostra mostra de població que va ser de 28,2%, la de només sobrepes del 15,4% i la de només obesitat del 12,8%. La prevalença d'obesitat és major en nens amb un 13,6% que en nenes 12,5% igual que el sobrepès. L'obesitat i sobrepès és major quan els estudis materns són inferiors als universitaris, també quan existeixen famílies amb 3 o més fills i quan es veu la TV més de 3 hores al dia.

Breast cancer incidence and overdiagnosis in Catalonia (Spain)

Early detection of breast cancer (BC) with mammography may cause overdiagnosis andovertreatment, detecting tumors which would remain undiagnosed during a lifetime. The aims of this study were: first, to model invasive BC incidence trends in Catalonia (Spain) taking into account reproductive and screening data; and second, to quantify the extent of BC overdiagnosis. We modeled the incidence of invasive BC using a Poisson regression model. Explanatory variables were:age at diagnosis and cohort characteristics (completed fertility rate, percentage of women that use mammography at age 50, and year of birth). This model also was used to estimate the background incidence in the absence of screening. We used a probabilistic model to estimate the expected BC incidence if women in the population usedmammography as reported in health surveys. The difference between the observed and expected cumulative incidences provided an estimate of overdiagnosis.Incidence of invasive BC increased, especially in cohorts born from 1940 to 1955. The biggest increase was observed in these cohorts between the ages of 50 to 65 years, where the final BC incidence rates more than doubled the initial ones. Dissemination of mammography was significantly associated with BC incidence and overdiagnosis. Our estimates of overdiagnosis ranged from 0.4% to 46.6%, for women born around 1935 and 1950, respectively.Our results support the existence of overdiagnosis in Catalonia attributed to mammography usage, and the limited malignant potential of some tumors may play an important role. Women should be better informed about this risk. Research should be oriented towards personalized screening and risk assessment tools

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

Caracterització i diagnosi de masses en imatges de mamografia

Els objectius del projecte es divideixen en tres blocs: Primerament, realitzar unasegmentació automàtica del contorn d'una imatge on hi ha una massa central. Tot seguit, a partir del contorn trobat, caracteritzar la massa. I finalment, utilitzant les característiques anteriors classificar la massa en benigne o maligne. En el projecte s'utilitza el Matlab com a eina de programació. Concretament les funcions enfocades al processat de imatges del toolbox de Image processing (propi de Matlab) i els classificadors de la PRTools de la Delft University of Technology

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

Munchausen's syndrome simulating reflex sympathetic dystrophy

A 15 year old girl who had pain, oedema of her left hand, and fever of four months' duration is described. Marked demineralisation of her hand was shown by radiography, and increased articular uptake by technetium-99m bone scan. All these changes were indistinguishable from reflex sympathetic dystrophy. After two admissions to hospital and multiple explorations we discovered that she had induced her symptoms herself and a diagnosis of Munchausen's syndrome was made. As far as we know this presentation has not been previously reported and might help to explain the physiopathology of some signs of reflex sympathetic dystrophy.

Diferenciación radiográfica entre el pie pronado y supinado

En este artículo se presentan las dos proyecciones más usadas para la valoración radiográfica del pie, dorsoplantar y perfil en carga, en las cuales se han escogido ocho parámetros en cada proyección con el objetivo de realizar una diferenciación fácil y rápida, de un modo cualitativo, entre las posiciones pronada y supinada de manera que se facilite su detección.

Cronología de osificación del pie. Radiogoniometría.

El motivo por el cual elegimos para el trabajo el tema titulado " Cronología de osificación del pie. Radiogoniometría" fue debido al interés que despertó en nosotras, la disparidad de datos ofrecidos por diferentes autores respecto a la cronología de aparición en la radiografía, de los núcleos primarios, secundarios terciarios de osificación. Respecto a la radiogoniometría, también creímos que era necesario una revisión para comprobar si han aparecido cambios sobre el rango de normalidad de algunos ángulos, cuyas valoraciones son importantes en las edades de crecimiento.

Estudio de los tumores óseos mediante el tratamiento de imágenes digitalizadas

Aquest informe tècnic mostra la classificació, incidència, característiques i diagnòstic dels tumors ossis primaris i secundaris metastàsics més freqüents a partir de 145 radiografies digitalitzades

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is oftenassociated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcificationsis performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcificationshave been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the senseof adding new features not only related to the shape

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Ergonomics and musculoskeletal pain among postgraduate students and faculty members of the School of Dentistry of the University of Barcelona (Spain). A cross-sectional study

Objectives: To evaluate the intensity and location of musculoskeletal pain suffered by students and professors from different postgraduate programs of the School of Dentistry of the University of Barcelona (Spain), to identify the variables related to the occurrence of musculoskeletal symptoms and signs, and to establish possible preventive measures for such disorders. Materials and Methods: A cross-sectional study was made among students and faculty members from different postgraduate courses of the School of Dentistry at the University of Barcelona between May and June 2007. A total of 74 dentists (54 postgraduate students and 20 faculty members) completed an anonymous questionnaire containing 19 questions. The variables were divided into three main groups: sociodemographic information, ergonomic features and musculoskeletal pain arising from professional practice. Results: Most of the dentists (79.8%) had experienced some kind of musculoskeletal pain in the last 6 months. On comparing the different locations of pain (lumbar, cervical, dorsal, wrist, shoulder and others), the neck was found to be the most commonly affected location (58% of all subjects), and only 34% of the respondents took some preventive measures against musculoskeletal disorders. Women showed a higher frequency of intense pain involving the cervical, lumbar, dorsal and wrist areas (p<0.05). A higher incidence of wrist pain was recorded in professionals exclusively dedicated to oral surgery (p<0.05). No statistically significant correlation was found between the workload (hours) and pain in the different anatomical locations (p>0.05). Conclusions: An important incidence of pain symptoms secondary to musculoskeletal disorders was observed, particularly in the cervical region. Females and younger dentists showed a higher frequency of such symptoms. The implementation of preventive measures is necessary, in view of the high incidence of these disorders

Equivalent representation form of oscillators with elastic and damping nonlinear terms

In this work we consider the nonlinear equivalent representation form of oscillators that exhibit nonlinearities in both the elastic and the damping terms. The nonlinear damping effects are considered to be described by fractional power velocity terms which provide better predictions of the dissipative effects observed in some physical systems. It is shown that their effects on the system dynamics response are equivalent to a shift in the coefficient of the linear damping term of a Duffing oscillator. Then, its numerical integration predictions, based on its equivalent representation form given by the well-known forced, damped Duffing equation, are compared to the numerical integration values of its original equations of motion. The applicability of the proposed procedure is evaluated by studying the dynamics response of four nonlinear oscillators that arise in some engineering applications such as nanoresonators, microresonators, human wrist movements, structural engineering design, and chain dynamics of polymeric materials at high extensibility, among others

Moderate-Vigorous physical activity across Body Mass Index in females: moderating effect of endocannabinoids and temperament

Background: Endocannabinoids and temperament traits have been linked to both physical activity and body mass index (BMI) however no study has explored how these factors interact in females. The aims of this cross-sectional study were to 1) examine differences among distinct BMI groups on daytime physical activity and time spent in moderate-vigorous physical activity (MVPA), temperament traits and plasma endocannabinoid concentrations; and 2) explore the association and interaction between MVPA, temperament, endocannabinoids and BMI. Methods: Physical activity was measured with the wrist-worn accelerometer Actiwatch AW7, in a sample of 189 female participants (43 morbid obese, 30 obese, and 116 healthy-weight controls). The Temperament and Character Inventory-Revised questionnaire was used to assess personality traits. BMI was calculated by bioelectrical impedance analysis via the TANITA digital scale. Blood analyses were conducted to measure levels of endocannabinoids and endocannabinoid-related compounds. Path-analysis was performed to examine the association between predictive variables and MVPA. Results: Obese groups showed lower MVPA and dysfunctional temperament traits compared to healthy-weight controls. Plasma concentrations of 2-arachidonoylglyceryl (2-AG) were greater in obese groups. Path-analysis identified a direct effect between greater MVPA and low BMI (b = −0.13, p = .039) and high MVPA levels were associated with elevated anandamide (AEA) levels (b = 0.16, p = .049) and N-oleylethanolamide (OEA) levels (b = 0.22, p = .004), as well as high Novelty seeking (b = 0.18, p<.001) and low Harm avoidance (b = −0.16, p<.001). Conclusions: Obese individuals showed a distinct temperament profile and circulating endocannabinoids compared to controls. Temperament and endocannabinoids may act as moderators of the low MVPA in obesity.