4 resultados para Tissue Repair

em Repositório Científico do Instituto Politécnico de Lisboa - Portugal


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This paper deals with the coupled effect of temperature and silica fume addition on rheological, mechanical behaviour and porosity of grouts based on CEMI 42.5R, proportioned with a polycarboxylate-based high range water reducer. Preliminary tests were conducted to focus on the grout best able to fill a fibrous network since the goal of this study was to develop an optimized grout able to be injected in a mat of steel fibers for concrete strengthening. The grout composition was developed based on criteria for fresh state and hardened state properties. For a CEMI 42.5R based grout different high range water reducer dosages (0%, 0.2%, 0.4%, 0.5%, 0.7%) and silica fume (SF) dosages (0%, 2%, 4%) were tested (as replacement of cement by mass). Rheological measurements were used to investigate the effect of polycarboxylates (PCEs) and SF dosage on grout properties, particularly its workability loss, as the mix was to be injected in a matrix of steel fibers for concrete jacketing. The workability behaviour was characterized by the rheological parameters yield stress and plastic viscosity (for different grout temperatures and resting times), as well as the procedures of mini slump cone and funnel flow time. Then, further development focused only on the best grout compositions. The cement substitution by 2% of SF exhibited the best overall behaviour and was considered as the most promising compared to the others compositions tested. Concerning the fresh state analysis, a significant workability loss was detected if grout temperature increased above 35 degrees C. Below this temperature the grout presented a self-levelling behaviour and a life time equal to 45 min. In the hardened state, silica fumes increased not only the grout's porosity but also the grout's compressive strength at later ages, since the pozzolanic contribution to the compressive strength does not occur until 28 d and beyond. (C) 2012 Elsevier Ltd. All rights reserved.

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Liver steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles. Today, the assessment is subjectively performed by visual inspection. Here a classifier based on features extracted from ultrasound (US) images is described for the automatic diagnostic of this phatology. The proposed algorithm estimates the original ultrasound radio-frequency (RF) envelope signal from which the noiseless anatomic information and the textural information encoded in the speckle noise is extracted. The features characterizing the textural information are the coefficients of the first order autoregressive model that describes the speckle field. A binary Bayesian classifier was implemented and the Bayes factor was calculated. The classification has revealed an overall accuracy of 100%. The Bayes factor could be helpful in the graphical display of the quantitative results for diagnosis purposes.

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Aim - To use Monte Carlo (MC) together with voxel phantoms to analyze the tissue heterogeneity effect in the dose distributions and equivalent uniform dose (EUD) for (125)I prostate implants. Background - Dose distribution calculations in low dose-rate brachytherapy are based on the dose deposition around a single source in a water phantom. This formalism does not take into account tissue heterogeneities, interseed attenuation, or finite patient dimensions effects. Tissue composition is especially important due to the photoelectric effect. Materials and Methods - The computed tomographies (CT) of two patients with prostate cancer were used to create voxel phantoms for the MC simulations. An elemental composition and density were assigned to each structure. Densities of the prostate, vesicles, rectum and bladder were determined through the CT electronic densities of 100 patients. The same simulations were performed considering the same phantom as pure water. Results were compared via dose-volume histograms and EUD for the prostate and rectum. Results - The mean absorbed doses presented deviations of 3.3-4.0% for the prostate and of 2.3-4.9% for the rectum, when comparing calculations in water with calculations in the heterogeneous phantom. In the calculations in water, the prostate D 90 was overestimated by 2.8-3.9% and the rectum D 0.1cc resulted in dose differences of 6-8%. The EUD resulted in an overestimation of 3.5-3.7% for the prostate and of 7.7-8.3% for the rectum. Conclusions - The deposited dose was consistently overestimated for the simulation in water. In order to increase the accuracy in the determination of dose distributions, especially around the rectum, the introduction of the model-based algorithms is recommended.

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The MCNPX code was used to calculate the TG-43U1 recommended parameters in water and prostate tissue in order to quantify the dosimetric impact in 30 patients treated with (125)I prostate implants when replacing the TG-43U1 formalism parameters calculated in water by a prostate-like medium in the planning system (PS) and to evaluate the uncertainties associated with Monte Carlo (MC) calculations. The prostate density was obtained from the CT of 100 patients with prostate cancer. The deviations between our results for water and the TG-43U1 consensus dataset values were -2.6% for prostate V100, -13.0% for V150, and -5.8% for D90; -2.0% for rectum V100, and -5.1% for D0.1; -5.0% for urethra D10, and -5.1% for D30. The same differences between our water and prostate results were all under 0.3%. Uncertainties estimations were up to 2.9% for the gL(r) function, 13.4% for the F(r,θ) function and 7.0% for Λ, mainly due to seed geometry uncertainties. Uncertainties in extracting the TG-43U1 parameters in the MC simulations as well as in the literature comparison are of the same order of magnitude as the differences between dose distributions computed for water and prostate-like medium. The selection of the parameters for the PS should be done carefully, as it may considerably affect the dose distributions. The seeds internal geometry uncertainties are a major limiting factor in the MC parameters deduction.