Monte Carlo simulation of the basic features of the GE Millennium MG single photon emission computed tomography gamma camera

Objective - To describe and validate the simulation of the basic features of GE Millennium MG gamma camera using the GATE Monte Carlo platform. Material and methods - Crystal size and thickness, parallel-hole collimation and a realistic energy acquisition window were simulated in the GATE platform. GATE results were compared to experimental data in the following imaging conditions: a point source of 99mTc at different positions during static imaging and tomographic acquisitions using two different energy windows. The accuracy between the events expected and detected by simulation was obtained with the Mann–Whitney–Wilcoxon test. Comparisons were made regarding the measurement of sensitivity and spatial resolution, static and tomographic. Simulated and experimental spatial resolutions for tomographic data were compared with the Kruskal–Wallis test to assess simulation accuracy for this parameter. Results - There was good agreement between simulated and experimental data. The number of decays expected when compared with the number of decays registered, showed small deviation (≤0.007%). The sensitivity comparisons between static acquisitions for different distances from source to collimator (1, 5, 10, 20, 30cm) with energy windows of 126–154 keV and 130–158 keV showed differences of 4.4%, 5.5%, 4.2%, 5.5%, 4.5% and 5.4%, 6.3%, 6.3%, 5.8%, 5.3%, respectively. For the tomographic acquisitions, the mean differences were 7.5% and 9.8% for the energy window 126–154 keV and 130–158 keV. Comparison of simulated and experimental spatial resolutions for tomographic data showed no statistically significant differences with 95% confidence interval. Conclusions - Adequate simulation of the system basic features using GATE Monte Carlo simulation platform was achieved and validated.

Parallel hyperspectral unmixing method via split augmented lagrangian on GPU

One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.

Diagnostic performance of visual screening tests in the elderly

This study aimed to determine and evaluate the diagnostic accuracy of visual screening tests for detecting vision loss in elderly. This study is defined as study of diagnostic performance. The diagnostic accuracy of 5 visual tests -near convergence point, near accommodation point, stereopsis, contrast sensibility and amsler grid—was evaluated by means of the ROC method (receiver operating characteristics curves), sensitivity, specificity, positive and negative likelihood ratios (LR+/LR−). Visual acuity was used as the reference standard. A sample of 44 elderly aged 76.7 years (±9.32), who were institutionalized, was collected. The curves of contrast sensitivity and stereopsis are the most accurate (area under the curves were 0.814−p = 0.001, C.I.95%[0.653;0.975]— and 0.713−p = 0.027, C.I.95%[0,540;0,887], respectively). The scores with the best diagnostic validity for the stereopsis test were 0.605 (sensitivity 0.87, specificity 0.54; LR+ 1.89, LR−0.24) and 0.610 (sensitivity 0.81, specificity 0.54; LR+1.75, LR−0.36). The scores with higher diagnostic validity for the contrast sensibility test were 0.530 (sensitivity 0.94, specificity 0.69; LR+ 3.04, LR−0.09). The contrast sensitivity and stereopsis test's proved to be clinically useful in detecting vision loss in the elderly.

Diagnostic performance of visual screening tests in the elderly

The aging of Portuguese population is characterized by an increase of individuals aged older than 65 years. Preventable visual loss in older persons is an important public health problem. Tests used for vision screening should have a high degree of diagnostic validity confirmed by means of clinical trials. The primary aim of a screening program is the early detection of visual diseases. Between 20% and 50% of older people in the UK have undetected reduced vision and in most cases is correctable. Elderly patients do not receive a systematic eye examination unless a problem arises with their glasses or suspicion vision loss. This study aimed to determine and evaluate the diagnostic accuracy of visual screening tests for detecting vision loss in elderly. Furthermore, it pretends to define the ability to find the subjects affected with vision loss as positive and the subjects not affected with the same disease as negative. The ideal vision screening method should have high sensitivity and specificity for early detection of risk factors. It should be also low cost and easy to implement in all geographic and socioeconomic regions. Sensitivity is the ability of an examination to identify the presence of a given disease and specificity is the ability of the examination to identify the absence of a given disease. It was not an aim of this study to detect abnormalities that affect visual acuity. The aim of this study was to find out what´s the best test for the identification of any vision loss.

More than maternal sensitivity shapes attachment : infant coping and temperament

The aim of this longitudinal studywas to investigate the effect of a set of factors from multiple levels of influence: infant temperament, infant regulatory behavior, and maternal sensitivity on infant’s attachment. Our sample consisted of 48 infants born prematurely and their mothers. At 1 and 3 months of age, mothers described their infants’behavior using the Escala de Temperamento do Beb´e. At 3 months of age, infants’ capacity to regulate stress was evaluated during Tronick’s Face-to-Face Still-Face (FFSF) paradigm. At 9 months of age, mothers’ sensitivity was evaluated during free play using the CARE-Index. At 12 months of age, infants’ attachment security was assessed during Ainsworth’s Strange Situation. A total of 16 infants were classified as securely attached, 17 as insecure-avoidant, and 15 as insecure-resistant. Mothers of securely attached infantswere more likely than mothers of insecure infants to describe their infants as less difficult and to be more sensitive to their infants in free play. In turn, secure infants exhibited more positive responses during the Still-Face. Infants classified as insecureavoidant were more likely to self-comfort during the Still-Face and had mothers who were more controlling during free play. Insecure-resistant exhibited higher levels of negative arousal during the Still-Face and had mothers who were more unresponsive in free play. These findings show that attachment quality is influenced bymultiple factors, including infant temperament, coping behavior, and maternal sensitivity.

Monitorização da insuficiência cardíaca por parâmetros fisiológicos em portadores de cardioversor-desfibrilhador implantável e/ou sistema de ressincronização cardíaca: HF-PREDICT

Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular. Área de especialização: Intervenção Cardiovascular.

Evaluation of the respiratory motion effect in small animal PET images with GATE Monte Carlo simulations

The rapid growth in genetics and molecular biology combined with the development of techniques for genetically engineering small animals has led to increased interest in in vivo small animal imaging. Small animal imaging has been applied frequently to the imaging of small animals (mice and rats), which are ubiquitous in modeling human diseases and testing treatments. The use of PET in small animals allows the use of subjects as their own control, reducing the interanimal variability. This allows performing longitudinal studies on the same animal and improves the accuracy of biological models. However, small animal PET still suffers from several limitations. The amounts of radiotracers needed, limited scanner sensitivity, image resolution and image quantification issues, all could clearly benefit from additional research. Because nuclear medicine imaging deals with radioactive decay, the emission of radiation energy through photons and particles alongside with the detection of these quanta and particles in different materials make Monte Carlo method an important simulation tool in both nuclear medicine research and clinical practice. In order to optimize the quantitative use of PET in clinical practice, data- and image-processing methods are also a field of intense interest and development. The evaluation of such methods often relies on the use of simulated data and images since these offer control of the ground truth. Monte Carlo simulations are widely used for PET simulation since they take into account all the random processes involved in PET imaging, from the emission of the positron to the detection of the photons by the detectors. Simulation techniques have become an importance and indispensable complement to a wide range of problems that could not be addressed by experimental or analytical approaches.

Perceção visual na avaliação diagnóstica em mamografia: uma revisão sistemática

Introdução – Na avaliação diagnóstica em mamografia, o desempenho do radiologista pode estar sujeito a erros de diagnóstico. Objetivo – Descrever a importância da perceção visual na análise da mamografia, identificando os principais fatores que contribuem para a perceção visual do radiologista e que condicionam a acuidade diagnóstica. Metodologia – Estudo descritivo baseado numa revisão sistemática de literatura através da PubMed e da Science Direct. Foram incluídos 42 artigos que respeitavam, pelo menos, um dos critérios de inclusão no estudo. Para a seleção das referências foi utilizada a metodologia PRISMA, constituída por 4 fases: identificação, seleção preliminar, elegibilidade e estudos incluídos. Resultados – Na avaliação diagnóstica em mamografia, a perceção visual está intimamente relacionada com: 1) diferentes parâmetros visuais e da motilidade ocular (acuidade visual, sensibilidade ao contraste e à luminância e movimentos oculares); 2) com condições de visualização de uma imagem (iluminância da sala e luminância do monitor); e 3) fadiga ocular provocada pela observação diária consecutiva de imagens. Conclusões – A perceção visual pode ser influenciada por 3 categorias de erros observados: erros de pesquisa (lesões não são fixadas pela fóvea), erros de reconhecimento (lesões fixadas, mas não durante o tempo suficiente) e erros de decisão (lesões fixadas, mas não identificadas como suspeitas). Os estudos analisados sobre perceção visual, atenção visual e estratégia visual, bem como os estudos sobre condições de visualização não caracterizam a função visual dos observadores. Para uma avaliação correta da perceção visual em mamografia deverão ser efetuados estudos que correlacionem a função visual com a qualidade diagnóstica. ABSTRACT - Introduction – Diagnostic evaluation in mammography could be influenced by the radiologist performance that could be under diagnostic errors. Aims – To describe the importance of radiologist visual perception in mammographic diagnostic evaluation and to identify the main factors that contribute to diagnostic accuracy. Methods – In this systematic review 42 references were included based on inclusion criteria (PubMed and Science Direct). PRISMA method was used to select the references following 4 steps: identification, screening, eligibility and included references. Results – Visual perception in mammography diagnostic evaluation is related with: 1) visual parameters and ocular motility (visual acuity, contrast sensitivity and luminance and ocular movements); 2) image visualization environment (room iluminance and monitor luminance); and 3) eyestrain caused by image daily consecutive observation. Conclusions – Visual perception can be influenced by three errors categories: search errors (lesions are never looked at with high-resolution foveal vision), recognition errors (lesions are looked at, but not long enough to detect or recognize) and decision errors (lesions are looked at for long periods of time but are still missed). The reviewed studies concerning visual perception, visual attention, visual strategies and image visualization environment do not describe observer’s visual function. An accurate evaluation of visual perception in mammography must include visual function analysis.

Accuracy of polls in Portugal

This study has a vast analysis, studying almost all the pre-electoral polls published or issued in Portugal in the month previous to each of the elections, since 1991 until the last one that took place in February 2005. The accuracy measures I used were adapted from the study carried out by Frederick Mosteller in the report to the Committee on Analysis of Pre-election Polls, regarding the USA elections of 1948.

Synthesis of optimization of [11C] Pittsburgh compound B by the captive solvent method

Mestrado em Medicina Nuclear.

O teatro de marionetas e o desenvolvimento da oralidade no 2º ciclo do ensino básico

Dissertação apresentada à Escola Superior de Educação de Lisboa para a obtenção do grau de mestre em Educação Artística - Especialização em Teatro na Educação

Avaliação do desempenho de um sistema híbrido de tomografia por emissão de positrões e tomografia computorizada

Mestrado em Medicina Nuclear.

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.