195 resultados para kernel density estimations
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Introduction: The accurate identification of tissue electron densities is of great importance for Monte Carlo (MC) dose calculations. When converting patient CT data into a voxelised format suitable for MC simulations, however, it is common to simplify the assignment of electron densities so that the complex tissues existing in the human body are categorized into a few basic types. This study examines the effects that the assignment of tissue types and the calculation of densities can have on the results of MC simulations, for the particular case of a Siemen’s Sensation 4 CT scanner located in a radiotherapy centre where QA measurements are routinely made using 11 tissue types (plus air). Methods: DOSXYZnrc phantoms are generated from CT data, using the CTCREATE user code, with the relationship between Hounsfield units (HU) and density determined via linear interpolation between a series of specified points on the ‘CT-density ramp’ (see Figure 1(a)). Tissue types are assigned according to HU ranges. Each voxel in the DOSXYZnrc phantom therefore has an electron density (electrons/cm3) defined by the product of the mass density (from the HU conversion) and the intrinsic electron density (electrons /gram) (from the material assignment), in that voxel. In this study, we consider the problems of density conversion and material identification separately: the CT-density ramp is simplified by decreasing the number of points which define it from 12 down to 8, 3 and 2; and the material-type-assignment is varied by defining the materials which comprise our test phantom (a Supertech head) as two tissues and bone, two plastics and bone, water only and (as an extreme case) lead only. The effect of these parameters on radiological thickness maps derived from simulated portal images is investigated. Results & Discussion: Increasing the degree of simplification of the CT-density ramp results in an increasing effect on the resulting radiological thickness calculated for the Supertech head phantom. For instance, defining the CT-density ramp using 8 points, instead of 12, results in a maximum radiological thickness change of 0.2 cm, whereas defining the CT-density ramp using only 2 points results in a maximum radiological thickness change of 11.2 cm. Changing the definition of the materials comprising the phantom between water and plastic and tissue results in millimetre-scale changes to the resulting radiological thickness. When the entire phantom is defined as lead, this alteration changes the calculated radiological thickness by a maximum of 9.7 cm. Evidently, the simplification of the CT-density ramp has a greater effect on the resulting radiological thickness map than does the alteration of the assignment of tissue types. Conclusions: It is possible to alter the definitions of the tissue types comprising the phantom (or patient) without substantially altering the results of simulated portal images. However, these images are very sensitive to the accurate identification of the HU-density relationship. When converting data from a patient’s CT into a MC simulation phantom, therefore, all possible care should be taken to accurately reproduce the conversion between HU and mass density, for the specific CT scanner used. Acknowledgements: This work is funded by the NHMRC, through a project grant, and supported by the Queensland University of Technology (QUT) and the Royal Brisbane and Women's Hospital (RBWH), Brisbane, Australia. The authors are grateful to the staff of the RBWH, especially Darren Cassidy, for assistance in obtaining the phantom CT data used in this study. The authors also wish to thank Cathy Hargrave, of QUT, for assistance in formatting the CT data, using the Pinnacle TPS. Computational resources and services used in this work were provided by the HPC and Research Support Group, QUT, Brisbane, Australia.
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Introduction: The motivation for developing megavoltage (and kilovoltage) cone beam CT (MV CBCT) capabilities in the radiotherapy treatment room was primarily based on the need to improve patient set-up accuracy. There has recently been an interest in using the cone beam CT data for treatment planning. Accurate treatment planning, however, requires knowledge of the electron density of the tissues receiving radiation in order to calculate dose distributions. This is obtained from CT, utilising a conversion between CT number and electron density of various tissues. The use of MV CBCT has particular advantages compared to treatment planning with kilovoltage CT in the presence of high atomic number materials and requires the conversion of pixel values from the image sets to electron density. Therefore, a study was undertaken to characterise the pixel value to electron density relationship for the Siemens MV CBCT system, MVision, and determine the effect, if any, of differing the number of monitor units used for acquisition. If a significant difference with number of monitor units was seen then pixel value to ED conversions may be required for each of the clinical settings. The calibration of the MV CT images for electron density offers the possibility for a daily recalculation of the dose distribution and the introduction of new adaptive radiotherapy treatment strategies. Methods: A Gammex Electron Density CT Phantom was imaged with the MVCB CT system. The pixel value for each of the sixteen inserts, which ranged from 0.292 to 1.707 relative electron density to the background solid water, was determined by taking the mean value from within a region of interest centred on the insert, over 5 slices within the centre of the phantom. These results were averaged and plotted against the relative electron densities of each insert with a linear least squares fit was preformed. This procedure was performed for images acquired with 5, 8, 15 and 60 monitor units. Results: The linear relationship between MVCT pixel value and ED was demonstrated for all monitor unit settings and over a range of electron densities. The number of monitor units utilised was found to have no significant impact on this relationship. Discussion: It was found that the number of MU utilised does not significantly alter the pixel value obtained for different ED materials. However, to ensure the most accurate and reproducible MV to ED calibration, one MU setting should be chosen and used routinely. To ensure accuracy for the clinical situation this MU setting should correspond to that which is used clinically. If more than one MU setting is used clinically then an average of the CT values acquired with different numbers of MU could be utilized without loss in accuracy. Conclusions: No significant differences have been shown between the pixel value to ED conversion for the Siemens MV CT cone beam unit with change in monitor units. Thus as single conversion curve could be utilised for MV CT treatment planning. To fully utilise MV CT imaging for radiotherapy treatment planning further work will be undertaken to ensure all corrections have been made and dose calculations verified. These dose calculations may be either for treatment planning purposes or for reconstructing the delivered dose distribution from transit dosimetry measurements made using electronic portal imaging devices. This will potentially allow the cumulative dose distribution to be determined through the patient’s multi-fraction treatment and adaptive treatment strategies developed to optimize the tumour response.
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This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.
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The Low-Density Lipoprotein Receptor (LDLR) gene is a cell surface receptor that plays an important role in cholesterol homeostasis. We investigated the (TA)n polymorphism in exon 18 of the LDLR gene on chromosome 19p13.2 performing an association analysis in 244 typical migraine-affected patients, 151 suffering from migraine with aura (MA), 96 with migraine without aura (MO) and 244 unaffected controls. The populations consisted of Caucasians only, and controls were age- and sex-matched. The results showed no significant difference between groups for allele frequency distributions of the (TA)n polymorphism even after separation of the migraine-affected individuals into subgroups of MA and MO affected patients. This is in contradiction to Mochi et al. who found a positive association of this variant with MO. Our study discusses possible differences between the two studies and extends this research by investigating circulating cholesterol levels in a migraine-affected population.
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RFLPs at the low density lipoprotein receptor locus (LDLR) display marked linkage disequilibrium between each other. Cross-sectional analysis of a bi-alleleic ApaLI RFLP of LDLR showed that the 9.4- and 6.6-kb alleles were present in similar frequency between a group of 84 Caucasian essential hypertensive (HT) and a group of 96 normotensive subjects whose parents each had a similar blood pressure status at age > or = 50. After subdividing HTs into lean and obese, however, the frequency of the 6.6-kb allele in the 27 HTs with BMI > or = 26 kg/m2 was 0.63, compared with 0.39 for HTs with BMI < 26 (chi 2 = 8.8; P = 0.004). The difference in genotype frequencies was even more striking (chi 2 = 23; P = 0.00008), with a virtual absence of 9.4-kb homozygotes in the obese HT group (1 vs 22). Genetic variation at LDLR (19p13.2) is thus associated with obesity in HT.
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OBJECTIVE To determine whether a microsatellite polymorphism located towards the 3' end of the low density lipoprotein receptor gene (LDLR) is associated with obesity. DESIGN A cross-sectional case-control study. SUBJECTS One hundred and seven obese individuals, defined as a body mass index (BMI) ≤ 26 kg/m2, and 163 lean individuals, defined as a BMI < 26 kg/m2. MEASUREMENTS BMI, blood pressure, serum lipids, alleles of LDLR microsatellite (106 bp, 108 bp and 112 bp). RESULTS There was a significant association between variants of the LDLR microsatellite and obesity, in the overall tested population, due to a contributing effect in females (χ2 = 12.3, P = 0.002), but not in males (χ2 = 0.3, P = 0.87). In females, individuals with the 106 bp allele were more likely to be lean, while individuals with the 112 bp and/or 108 bp alleles tended to be obese. CONCLUSIONS These results suggest that in females, LDLR may play a role in the development of obesity.
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Obese (BMI ≥ 26 kg/m 2; n = 51) and lean (BMI <26 kg/m 2; n = 61) Caucasian patients with severe, familial essential hypertension, were compared with respect to genotype and allele frequencies of a HincII RFLP of the low density lipoprotein receptor gene (LDLR). A similar analysis was performed in obese (n = 28) and lean (n = 68) normotensives. A significant association of the C allele of the T→C variant responsible for this RFLP was seen with obesity (χ 2 = 4.6, P = 0.029) in the hypertensive, but not in the normotensive, group (odds ratio = 3.0 for the CC genotype and 2.7 for CT). Furthermore, BMI tracked with genotypes of this allele in the hypertensives (P = 0.046). No significant genotypic relationship was apparent for plasma lipids. Significant linkage disequilibrium was, moreover, noted between the HincII RFLP and an ApaLI RFLP (χ 2 = 33, P<0.0005) that has previously shown even stronger association with obesity (odds ratio 19.6 for cases homozygous for the susceptibility allele and 15.2 for het-erozygotes). The present study therefore adds to our previous evidence implicating LDLR as a locus for obesity in patients with essential hypertension.
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This project was a step forward in developing intrusion detection systems in distributed environments such as web services. It investigates a new approach of detection based on so-called "taint-marking" techniques and introduces a theoretical framework along with its implementation in the Linux kernel.
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As of June 2009, 361 genome-wide association studies (GWAS) had been referenced by the HuGE database. GWAS require DNA from many thousands of individuals, relying on suitable DNA collections. We recently performed a multiple sclerosis (MS) GWAS where a substantial component of the cases (24%) had DNA derived from saliva. Genotyping was done on the Illumina genotyping platform using the Infinium Hap370CNV DUO microarray. Additionally, we genotyped 10 individuals in duplicate using both saliva- and blood-derived DNA. The performance of blood- versus saliva-derived DNA was compared using genotyping call rate, which reflects both the quantity and quality of genotyping per sample and the “GCScore,” an Illumina genotyping quality score, which is a measure of DNA quality. We also compared genotype calls and GCScores for the 10 sample pairs. Call rates were assessed for each sample individually. For the GWAS samples, we compared data according to source of DNA and center of origin. We observed high concordance in genotyping quality and quantity between the paired samples and minimal loss of quality and quantity of DNA in the saliva samples in the large GWAS sample, with the blood samples showing greater variation between centers of origin. This large data set highlights the usefulness of saliva DNA for genotyping, especially in high-density single-nucleotide polymorphism microarray studies such as GWAS.
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This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.
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A qualitative analysis of the expected dilatation strain field in the vicinity of an array of grain-boundary (GB) dislocations is presented. The analysis provides a basis for the prediction of the critical current densities (jc) across low-angle YBa2Cu3O7- (YBCO) GBs as a function of their energy. The introduction of the GB energy allows the extension of the analysis to high-angle GBs using established models which predict the GB energy as a function of misorientation angle. The results are compared to published data for jc across [001]-tilt YBCO GBs for the full range of misorientations, showing a good fit. Since the GB energy is directly related to the GB structure, the analysis may allow a generalization of the scaling behavior of jc with the GB energy. © 1995 The American Physical Society.
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Using ZnO seed layers, an efficient approach for enhancing the heterointerface quality of electrodeposited ZnO–Cu2O solar cells is devised. We introduce a sputtered ZnO seed layer followed by the sequential electrodeposition of ZnO and Cu2O films. The seed layer is employed to control the growth and crystallinity and to augment the surface area of the electrodeposited ZnO films, thereby tuning the quality of the ZnO–Cu2O heterointerface. Additionally, the seed layer also assists in forming high quality ZnO films, with no pin-holes, in a high pH electrolyte solution. X-ray electron diffraction patterns, scanning electron and atomic force microscopy images, as well as photovoltaic measurements, clearly demonstrate that the incorporation of certain seed layers results in the alteration of the heterointerface quality, a change in the heterojunction area and the crystallinity of the films near the junction, which influence the current density of photovoltaic devices.
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Microvessel density (MVD) is a widely used surrogate measure of angiogenesis in pathological specimens and tumour models. Measurement of MVD can be achieved by several methods. Automation of counting methods aims to increase the speed, reliability and reproducibility of these techniques. The image analysis system described here enables MVD measurement to be carried out with minimal expense in any reasonably equipped pathology department or laboratory. It is demonstrated that the system translates easily between tumour types which are suitably stained with minimal calibration. The aim of this paper is to offer this technique to a wider field of researchers in angiogenesis.