O tratamento de metástases ósseas de fração única vs múltiplas frações com 3D CRT ou SBRT: artigo de revisão sistemática

Introdução – A escolha do tratamento depende de vários fatores, incluindo o estado clínico e prognóstico de cada doente. Estes fatores desempenham um papel importante na escolha da intervenção terapêutica em metástases ósseas. A deteção precoce e o tratamento adequado podem melhorar a qualidade de vida e independência funcional dos doentes. Metodologia – Este artigo pretende realizar uma revisão sistemática da literatura dos últimos 15 anos, identificando os diferentes tipos de fracionamentos (fração única versus múltiplas frações) e técnicas utilizadas em radioterapia no tratamento de metástases ósseas. Resultados – Os recentes avanços na tecnologia e nas técnicas de tratamento de radioterapia ajudam na distribuição de doses altamente conformacionais e com orientação por imagem para uma entrega mais precisa do tratamento. A radioterapia estereotáxica corporal (SBRT, do acrónimo inglês stereotactic body radiotherapy) permite delimitar e aumentar a dose nos tumores a irradiar. No caso das metástases ósseas, os resultados de controlo local do tumor e da dor têm-se revelado promissores. A radioterapia convencional de 8Gyx1, no entanto, continua a ser o tratamento mais indicado nos doentes paliativos. Conclusão – O tratamento de metástases ósseas é complexo e uma abordagem multidisciplinar é sempre necessária. O tratamento deve ser individualizado para se adequar aos sintomas e estado clínico de cada doente.

Cenografia virtual em televisão: relatório de estágio

Relatório de Estágio submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Design de Cena.

Electrochemical response of 70Co-30Ni highly branched 3D-dendritic structures for charge storage electrodes

A 70Co-30Ni dendritic alloy was produced on stainless steel by pulse electrodeposition in the cathodic domain, and oxidized by potential cycling. X-ray diffraction (XRD) identified the presence of two phases and scanning electron microscopy (SEM) evidenced an open 3D highly branched dendritic morphology. After potential cycling in 1 M KOH, SEM and X-ray photoelectron spectroscopy (XPS) revealed, respectively, the presence of thin nanoplates, composed of Co and Ni oxi-hydroxides and hydroxides over the original dendritic film. Cyclic voltammetry tests showd the presence of redox peaks assigned to the oxidation and reduction of Ni and Co centres in the surface film. Charge/discharge measurements revealed capacity values of 121 mAh g(1) at 1 mA cm(2). The capacity retention under 8000 cycles was above 70%, stating the good reversibility of these redox materials and its suitability to be used as charge storage electrodes. Electrochemical impedance spectroscopy (EIS) spectra, taken under different applied bias, showed that the capacitance increased when the electrode was fully oxidized and decreased when the electrode was reduced, reflecting different states-of-charge of the electrode. (C) 2015 Elsevier Ltd. All rights reserved.

Processing and characterization of 3D dense chitosan pieces, for orthopedic applications, by adding plasticizers

In this work, plasticizer agents were incorporated in a chitosan based formulation, as a strategy to improve the fragile structure of chitosan based-materials. Three different plasticizers: ethylene glycol, glycerol and sorbitol, were blended with chitosan to prepare 3D dense chitosan specimens. The properties of the obtained structures were assessed for mechanical, microstructural, physical and biocompatibility behavior. The results obtained revealed that from the different specimens prepared, the blend of chitosan with glycerol has superior mechanical properties and good biological behavior, making this chitosan based formulation a good candidate to improve robust chitosan structures for the construction of bioabsorbable orthopedic implants.

Estimation of 3D shapes using active surface models

This paper addresses the estimation of surfaces from a set of 3D points using the unified framework described in [1]. This framework proposes the use of competitive learning for curve estimation, i.e., a set of points is defined on a deformable curve and they all compete to represent the available data. This paper extends the use of the unified framework to surface estimation. It o shown that competitive learning performes better than snakes, improving the model performance in the presence of concavities and allowing to desciminate close surfaces. The proposed model is evaluated in this paper using syntheticdata and medical images (MRI and ultrasound images).