Influence of reconstruction parameters during filtered backprojection and ordered-subset expectation maximization in the measurement of the left-ventricular volumes and function during gated SPECT

A crucial method for investigating patients with coronary artery disease (CAD) is the calculation of the left ventricular ejection fraction (LVEF). It is, consequently, imperative to precisely estimate the value of LVEF--a process that can be done with myocardial perfusion scintigraphy. Therefore, the present study aimed to establish and compare the estimation performance of the quantitative parameters of the reconstruction methods filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM). Methods: A beating-heart phantom with known values of end-diastolic volume, end-systolic volume, and LVEF was used. Quantitative gated SPECT/quantitative perfusion SPECT software was used to obtain these quantitative parameters in a semiautomatic mode. The Butterworth filter was used in FBP, with the cutoff frequencies between 0.2 and 0.8 cycles per pixel combined with the orders of 5, 10, 15, and 20. Sixty-three reconstructions were performed using 2, 4, 6, 8, 10, 12, and 16 OSEM subsets, combined with several iterations: 2, 4, 6, 8, 10, 12, 16, 32, and 64. Results: With FBP, the values of end-diastolic, end-systolic, and the stroke volumes rise as the cutoff frequency increases, whereas the value of LVEF diminishes. This same pattern is verified with the OSEM reconstruction. However, with OSEM there is a more precise estimation of the quantitative parameters, especially with the combinations 2 iterations × 10 subsets and 2 iterations × 12 subsets. Conclusion: The OSEM reconstruction presents better estimations of the quantitative parameters than does FBP. This study recommends the use of 2 iterations with 10 or 12 subsets for OSEM and a cutoff frequency of 0.5 cycles per pixel with the orders 5, 10, or 15 for FBP as the best estimations for the left ventricular volumes and ejection fraction quantification in myocardial perfusion scintigraphy.

Avaliação das alterações volumétricas da cavidade nasal decorrentes da expansão rápida de maxila assistida cirurgicamente

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelação e concepção da carroçaria do veículo eléctrico ecológico (VEECO)

Neste trabalho aborda-se o desenvolvimento da carroçaria do Veículo Eléctrico Ecológico – VEECO recorrendo a tecnologias assistidas por computador. Devido à impossibilidade de abranger toda a temática das tecnologias assistidas por computador, associadas ao desenvolvimento de uma carroçaria automóvel, o foco deste trabalho assenta no processo de obtenção de um modelo digital válido e no estudo do desempenho aerodinâmico da carroçaria. A existência de um modelo digital válido é a base de qualquer processo de desenvolvimento associado a tecnologias assistidas por computador. Neste sentido, numa primeira etapa, foram aplicadas e desenvolvidas técnicas e metodologias que permitem o desenvolvimento de uma carroçaria desde a sua fase de “design” até à obtenção de um modelo digital CAD. Estas abrangem a conversão e importação de dados, a realização de engenharia inversa, a construção/reconstrução CAD em CATIA V5 e a preparação/correcção de modelos CAD para a análise numérica. Numa segunda etapa realizou-se o estudo da aerodinâmica exterior da carroçaria, recorrendo à ferramenta de análise computacional de fluidos (CFD) Flow Simulation da CosmosFloworks integrado no programa SolidWorks 2010. Associado à temática do estudo aerodinâmico e devido à elevada importância da validação dos resultados numéricos por meio de dados experimentais, foi realizado o estudo de análise dimensional que permite a realização de ensaios experimentais à escala, bem como a análise dos resultados experimentais obtidos.

A novel application of microwave-assisted extraction of polyphenols from brewer’s spent grain with HPLC-DAD-MS analysis

This paper reports a novel application of microwave-assisted extraction (MAE) of polyphenols from brewer’s spent grains (BSG). A 24 orthogonal composite design was used to obtain the optimal conditions of MAE. The influence of the MAE operational parameters (extraction time, temperature, solvent volume and stirring speed) on the extraction yield of ferulic acid was investigated through response surface methodology. The results showed that the optimal conditions were 15 min extraction time, 100 °C extraction temperature, 20 mL of solvent, and maximum stirring speed. Under these conditions, the yield of ferulic acid was 1.31±0.04% (w/w), which was fivefold higher than that obtained with conventional solid–liquid extraction techniques. The developed new extraction method considerably reduces extraction time, energy and solvent consumption, while generating fewer wastes. HPLC-DADMS analysis indicated that other hydroxycinnamic acids and several ferulic acid dehydrodimers, as well as one dehydrotrimer were also present, confirming that BSG is a valuable source of antioxidant compounds.

Analysis of polycyclic aromatic hydrocarbons in fish: optimisation and validation of microwave-assisted extraction

An accurate and sensitive method for determination of 18 polycyclic aromatic hydrocarbons (PAHs) (16 PAHs considered by USEPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) in fish samples was validated. Analysis was performed by microwave-assisted extraction and liquid chromatography with photodiode array and fluorescence detection. Response surface methodology was used to find the optimal extraction parameters. Validation of the overall methodology was performed by spiking assays at four levels and using SRM 2977. Quantification limits ranging from 0.15–27.16 ng/g wet weight were obtained. The established method was applied in edible tissues of three commonly consumed and commercially valuable fish species (sardine, chub mackerel and horse mackerel) originated from Atlantic Ocean. Variable levels of naphthalene (1.03–2.95 ng/g wet weight), fluorene (0.34–1.09 ng/g wet weight) and phenanthrene (0.34–3.54 ng/g wet weight) were detected in the analysed samples. None of the samples contained detectable amounts of benzo[a]pyrene, the marker used for evaluating the occurrence and carcinogenic effects of PAHs in food.

Monte Carlo modeling and simulations of the High Definition (HD120) micro MLC and validation against measurements for a 6 MV beam

Purpose: The most recent Varian® micro multileaf collimator(MLC), the High Definition (HD120) MLC, was modeled using the BEAMNRCMonte Carlo code. This model was incorporated into a Varian medical linear accelerator, for a 6 MV beam, in static and dynamic mode. The model was validated by comparing simulated profiles with measurements. Methods: The Varian® Trilogy® (2300C/D) accelerator model was accurately implemented using the state-of-the-art Monte Carlo simulation program BEAMNRC and validated against off-axis and depth dose profiles measured using ionization chambers, by adjusting the energy and the full width at half maximum (FWHM) of the initial electron beam. The HD120 MLC was modeled by developing a new BEAMNRC component module (CM), designated HDMLC, adapting the available DYNVMLC CM and incorporating the specific characteristics of this new micro MLC. The leaf dimensions were provided by the manufacturer. The geometry was visualized by tracing particles through the CM and recording their position when a leaf boundary is crossed. The leaf material density and abutting air gap between leaves were adjusted in order to obtain a good agreement between the simulated leakage profiles and EBT2 film measurements performed in a solid water phantom. To validate the HDMLC implementation, additional MLC static patterns were also simulated and compared to additional measurements. Furthermore, the ability to simulate dynamic MLC fields was implemented in the HDMLC CM. The simulation results of these fields were compared with EBT2 film measurements performed in a solid water phantom. Results: Overall, the discrepancies, with and without MLC, between the opened field simulations and the measurements using ionization chambers in a water phantom, for the off-axis profiles are below 2% and in depth-dose profiles are below 2% after the maximum dose depth and below 4% in the build-up region. On the conditions of these simulations, this tungsten-based MLC has a density of 18.7 g cm− 3 and an overall leakage of about 1.1 ± 0.03%. The discrepancies between the film measured and simulated closed and blocked fields are below 2% and 8%, respectively. Other measurements were performed for alternated leaf patterns and the agreement is satisfactory (to within 4%). The dynamic mode for this MLC was implemented and the discrepancies between film measurements and simulations are within 4%. Conclusions: The Varian® Trilogy® (2300 C/D) linear accelerator including the HD120 MLC was successfully modeled and simulated using the Monte CarloBEAMNRC code by developing an independent CM, the HDMLC CM, either in static and dynamic modes.

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%.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

Correcção automática de respostas de texto livre para a aplicação UNI_NET-Classroom

Ao longo dos tempos foi possível constatar que uma grande parte do tempo dos professores é gasta na componente de avaliação. Por esse facto, há já algumas décadas que a correcção automática de texto livre é alvo de investigação. Sendo a correcção de exercícios efectuada pelo computador permite que o professor dedique o seu tempo em tarefas que melhorem a aprendizagem dos alunos. Para além disso, cada vez mais as novas tecnologias permitem o uso de ferramentas com bastante utilidade no ensino, pois para além de facilitarem a exposição do conhecimento também permitem uma maior retenção da informação. Logo, associar ferramentas de gestão de sala de aula à correcção automática de respostas de texto livre é um desafio bastante interessante. O objectivo desta dissertação foi a realização de um estudo relativamente à área de avaliação assistida por computador em que este trabalho se insere. Inicialmente, foram analisados alguns correctores ortográficos para seleccionar aquele que seria integrado no módulo proposto. De seguida, foram estudadas as técnicas mais relevantes e as ferramentas que mais se enquadram no âmbito deste trabalho. Neste contexto, a ideia foi partir da existência de uma ferramenta de gestão de sala de aula e desenvolver um módulo para a correcção de exercícios. A aplicação UNI_NET-Classroom, que foi a ferramenta para a qual o módulo foi desenvolvido, já continha um componente de gestão de exercícios que apenas efectuava a correcção para as respostas de escolha múltipla. Com este trabalho pretendeu-se acrescentar mais uma funcionalidade a esse componente, cujo intuito é dar apoio ao professor através da correcção de exercícios e sugestão da cotação a atribuir. Por último, foram realizadas várias experiências sobre o módulo desenvolvido, de forma a ser possível retirar algumas conclusões para o presente trabalho. A conclusão mais importante foi que as ferramentas de correcção automática são uma mais-valia para os professores e escolas.

Avaliação da caracterização de lesões em mamografia com recurso a sistemas CAD (Computer-Aided Diagnosis)

Os sistemas Computer-Aided Diagnosis (CAD) auxiliam a deteção e diferenciação de lesões benignas e malignas, aumentando a performance no diagnóstico do cancro da mama. As lesões da mama estão fortemente correlacionadas com a forma do contorno: lesões benignas apresentam contornos regulares, enquanto as lesões malignas tendem a apresentar contornos irregulares. Desta forma, a utilização de medidas quantitativas, como a dimensão fractal (DF), pode ajudar na caracterização dos contornos regulares ou irregulares de uma lesão. O principal objetivo deste estudo é verificar se a utilização concomitante de 2 (ou mais) medidas de DF – uma tradicionalmente utilizada, a qual foi designada por “DF de contorno”; outra proposta por nós, designada por “DF de área” – e ainda 3 medidas obtidas a partir destas, por operações de dilatação/erosão e por normalização de uma das medidas anteriores, melhoram a capacidade de caracterização de acordo com a escala BIRADS (Breast Imaging Reporting and Data System) e o tipo de lesão. As medidas de DF (DF contorno e DF área) foram calculadas através da aplicação do método box-counting, diretamente em imagens de lesões segmentadas e após a aplicação de um algoritmo de dilatação/erosão. A última medida baseia-se na diferença normalizada entre as duas medidas DF de área antes e após a aplicação do algoritmo de dilatação/erosão. Os resultados demonstram que a medida DF de contorno é uma ferramenta útil na diferenciação de lesões, de acordo com a escala BIRADS e o tipo de lesão; no entanto, em algumas situações, ocorrem alguns erros. O uso combinado desta medida com as quatro medidas propostas pode melhorar a classificação das lesões.

A multiresidue method for the analysis of carbamate and urea pesticides from soils by microwave-assisted extraction and liquid chromatography with photodiode array detection

A multiresidue approach using microwave-assisted extraction and liquid chromatography with photodiode array detection was investigated for the determination of butylate, carbaryl, carbofuran, chlorpropham, ethiofencarb, linuron,metobromuron, and monolinuron in soils. The critical parameters of the developed methodology were studied. Method validation was performed by analyzing freshly and aged spiked soil samples. The recoveries and relative standard deviations reached using the optimized conditions were between 77.0 ± 0.46% and 120 ± 2.9% except for ethiofencarb (46.4 ± 4.4% to 105 ± 1.6%) and butylate (22.1 ± 7.6% to 49.2 ± 11%). Soil samples from five locations of Portugal were analysed.

Determination of chlorfenvinphos in soils by microwave-assisted extraction and stripping voltammetry with an ultramicroelectrode

A methodology for the determination of the pesticide chlorfenvinphos by microwave-assisted solvent extraction and square-wave cathodic stripping voltammetry at a mercury film ultramicroelectrode in soil samples is proposed. Optimization of microwave solvent extraction performed with two soils, selected for having significantly different properties, indicated that the optimum solvent for extracting chlorfenvinphos is hexane-acetone (1:1, v/v). The voltammetric procedure is based on controlled adsorptive accumulation of the insecticide at the potential of -0.60 V (vs. Ag/AgCl) in the presence of Britton-Robinson buffer (pH 6.2). The detection limit obtained for a 10 s collection time was 3.0 x 10-8 mol l-1. The validity of the developed methodology was assessed by recovery experiments at the 0.100 µg g-1 level. The average recoveries and standard deviations for the global procedure reached byMASE-square-wave voltammetry were 90.2±2.8% and 92.1±3.4% for type I (soil rich in organic matter) and type II (sandy soil) samples, respectively. These results are in accordance to the expected values which show that the method has a good accuracy.

Determination of carbamate and urea pesticide residues in fresh vegetables using microwave-assisted extraction and liquid chromatography

An analytical multiresidue method for the simultaneous determination of seven pesticides in fresh vegetable samples, namely, courgette (Cucurbita pepo), cucumber (Cucumis sativus), lettuce (Lactuca sativa, Romaine and Iceberg varieties) and peppers (Capsicum sp.) is described. The procedure, based on microwave-assisted extraction (MAE) and analysis by liquid chromatography– photodiode array (LC–PDA) detection was applied to four carbamates (carbofuran, carbaryl, chlorpropham and EPTC) and three urea pesticides (monolinuron, metobromuron and linuron). Extraction solvent and the addition of anhydrous sodium sulphate to fresh vegetable homogenate before MAE were the parameters optimised for each commodity. Recovery studies were performed using spiked samples in the range 250–403 µgkg- 1 in each pesticide. The pesticide residues were extracted using 20mL acetonitrile at 60 ºC, for 10 min. Acceptable recoveries and RSDs were attained (overall average recovery of 77.2% and RSDs are lower than 11%). Detection limits ranged between 5.8 µgkg- 1 for carbaryl to 12.3 µgkg- 1 for carbofuran. The analytical protocol was applied for quality control of 41 fresh vegetable samples bought in Oporto Metropolitan Area (North Portugal). None of the samples contained any detectable amounts of the studied compounds.

Screening of carbamates and ureas in fresh and processed tomato samples using micowave-assisted extraction and liquid chromatography

An analytical method, based on microwave-assisted extraction and liquid chromatography with diode array detection, for the determination of six carbamate and three urea pesticides in fresh and processed tomato samples is described. Significant parameters affecting extraction efficiency were optimized. Under optimum microwave-assisted extraction conditions (20mL acetonitrile, for 10 minutes, at 60º C), pesticides were extracted with recoveries ranging from 57.6 to 102% (RSDs<7%). Quantification limits between 6.5 and 39.6 µg=kg were obtained. A total number of 28 different fresh tomato samples and 6 processed tomato products were analysed. Confirmation of suspicious samples was performed by LC-MS.