928 resultados para Parameter
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OBJECTIVE Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS). METHODS We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.
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We report on a new measurement of the neutron beta-asymmetry parameter A with the instrument \perkeo. Main advancements are the high neutron polarization of P=99.7(1) from a novel arrangement of super mirror polarizers and reduced background from improvements in beam line and shielding. Leading corrections were thus reduced by a factor of 4, pushing them below the level of statistical error and resulting in a significant reduction of systematic uncertainty compared to our previous experiments. From the result A0=−0.11996(58), we derive the ratio of the axial-vector to the vector coupling constant λ=gA/gV=−1.2767(16)
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Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^
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The aim of the present study was to investigate the effects of different speech tasks (recitation of prose (PR), alliteration (AR) and hexameter (HR) verses) and a control task (mental arithmetic (MA) with voicing of the result) on endtidal CO2 (ET-CO2), cerebral hemodynamics; i.e. total hemoglobin (tHb) and tissue oxygen saturation (StO2). tHb and StO2 were measured with a frequency domain near infrared spectrophotometer (ISS Inc., USA) and ET-CO2 with a gas analyzer (Nellcor N1000). Measurements were performed in 24 adult volunteers (11 female, 13 male; age range 22 to 64 years) during task performance in a randomized order on 4 different days to avoid potential carry over effects. Statistical analysis was applied to test differences between baseline, 2 recitation and 5 recovery periods. The two brain hemispheres and 4 tasks were tested separately. Data analysis revealed that during the recitation tasks (PR, AR and HR) StO2 decreased statistically significant (p < 0.05) during PR and AR in the right prefrontal cortex (PFC) and during AR and HR in the left PFC. tHb showed a significant decrease during HR in the right PFC and during PR, AR and HR in the left PFC. During the MA task, StO2 increased significantly. A significant decrease in ET-CO2 was found during all 4 tasks with the smallest decrease during the MA task. In conclusion, we hypothesize that the observed changes in tHb and StO2 are mainly caused by an altered breathing during the tasks that led a lowering of the CO2 content in the blood provoked a cerebral CO2 reaction, i.e. a vasoconstriction of blood vessels due to decreased CO2 pressure and thereby decrease in cerebral blood volume. Therefore, breathing changes should be monitored during brain studies involving speech when using functional near infrared spectroscopy (fNIRS) to ensure a correct interpretation of changes in hemodynamics and oxygenation.
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Numerical models of the intervertebral disc, which address mechanical questions commonly make use of the difference in water content between annulus and nucleus, and thus fluid and solid parts are separated. Despite this simplification, models remain complex due to the anisotropy and nonlinearity of the annulus and regional variations of the collagen fibre density. Additionally, it has been shown that cross-links make a large contribution to the stiffness of the annulus. Because of this complex composite structure, it is difficult to reproduce several sets of experimental data with one single set of material parameters. This study addresses the question to which extent the ultrastructure of the intervertebral disc should be modelled so that its moment-angle behaviour can be adequately described. Therefore, a hyperelastic constitutive law, based on continuum mechanical principles was derived, which does not only consider the anisotropy from the collagen fibres, but also interactions among the fibres and between the fibres and the ground substance. Eight ovine lumbar intervertebral discs were tested on a custom made spinal loading simulator in flexion/extension, lateral bending and axial rotation. Specimen-specific geometrical models were generated using CT images and T2 maps to distinguish between annulus fibrosus and nucleus pulposus. For the identification of the material parameters the annulus fibrosus was described with two scenarios: with and without fibre-matrix and fibre-fibre interactions. Both scenarios showed a similar behaviour on a load displacement level. Comparing model predictions to the experimental data, the mean RMS of all specimens and all load cases was 0.54±0.15° without the interaction and 0.54±0.19° when the fibre-matrix and fibre-fibre interactions were included. However, due to the increased stiffness when cross-links effects were included, this scenario showed more physiological stress-strain relations in uniaxial and biaxial stress states. Thus, the present study suggests that fibre-matrix and fibre-fibre interactions should be considered in the constitutive law when the model addresses questions concerning the stress field of the annulus fibrosus.
Resumo:
BACKGROUND: To investigate if non-rigid image-registration reduces motion artifacts in triggered and non-triggered diffusion tensor imaging (DTI) of native kidneys. A secondary aim was to determine, if improvements through registration allow for omitting respiratory-triggering. METHODS: Twenty volunteers underwent coronal DTI of the kidneys with nine b-values (10-700 s/mm2 ) at 3 Tesla. Image-registration was performed using a multimodal nonrigid registration algorithm. Data processing yielded the apparent diffusion coefficient (ADC), the contribution of perfusion (FP ), and the fractional anisotropy (FA). For comparison of the data stability, the root mean square error (RMSE) of the fitting and the standard deviations within the regions of interest (SDROI ) were evaluated. RESULTS: RMSEs decreased significantly after registration for triggered and also for non-triggered scans (P < 0.05). SDROI for ADC, FA, and FP were significantly lower after registration in both medulla and cortex of triggered scans (P < 0.01). Similarly the SDROI of FA and FP decreased significantly in non-triggered scans after registration (P < 0.05). RMSEs were significantly lower in triggered than in non-triggered scans, both with and without registration (P < 0.05). CONCLUSION: Respiratory motion correction by registration of individual echo-planar images leads to clearly reduced signal variations in renal DTI for both triggered and particularly non-triggered scans. Secondarily, the results suggest that respiratory-triggering still seems advantageous.J. Magn. Reson. Imaging 2014. (c) 2014 Wiley Periodicals, Inc.
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Assays measuring platelet aggregation (thrombus formation) at arterial shear rate mostly use collagen as only platelet-adhesive surface. Here we report a multi-surface and multi-parameter flow assay to characterize thrombus formation in whole blood from healthy subjects and patients with platelet function deficiencies. A systematic comparison is made of 52 adhesive surfaces with components activating the main platelet-adhesive receptors, and of eight output parameters reflecting distinct stages of thrombus formation. Three types of thrombus formation can be identified with a predicted hierarchy of the following receptors: glycoprotein (GP)VI, C-type lectin-like receptor-2 (CLEC-2)>GPIb>α6β1, αIIbβ3>α2β1>CD36, α5β1, αvβ3. Application with patient blood reveals distinct abnormalities in thrombus formation in patients with severe combined immune deficiency, Glanzmann's thrombasthenia, Hermansky-Pudlak syndrome, May-Hegglin anomaly or grey platelet syndrome. We suggest this test may be useful for the diagnosis of patients with suspected bleeding disorders or a pro-thrombotic tendency.
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A measurement of the parity-violating decay asymmetry parameter, αb , and the helicity amplitudes for the decay Λ 0 b →J/ψ(μ + μ − )Λ 0 (pπ − ) is reported. The analysis is based on 1400 Λ 0 b and Λ ¯ 0 b baryons selected in 4.6 fb −1 of proton–proton collision data with a center-of-mass energy of 7 TeV recorded by the ATLAS experiment at the LHC. By combining the Λ 0 b and Λ ¯ 0 b samples under the assumption of CP conservation, the value of α b is measured to be 0.30±0.16(stat)±0.06(syst) . This measurement provides a test of theoretical models based on perturbative QCD or heavy-quark effective theory.
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New data from the T2K neutrino oscillation experiment produce the most precise measurement of the neutrino mixing parameter θ 23 . Using an off-axis neutrino beam with a peak energy of 0.6 GeV and a data set corresponding to 6.57×10 20 protons on target, T2K has fit the energy-dependent ν μ oscillation probability to determine oscillation parameters. The 68% confidence limit on sin 2 (θ 23 ) is 0.514 +0.055 −0.056 (0.511±0.055 ), assuming normal (inverted) mass hierarchy. The best-fit mass-squared splitting for normal hierarchy is Δm 2 32 =(2.51±0.10)×10 −3 eV 2 /c 4 (inverted hierarchy: Δm 2 13 =(2.48±0.10)×10 −3 eV 2 /c 4 ). Adding a model of multinucleon interactions that affect neutrino energy reconstruction is found to produce only small biases in neutrino oscillation parameter extraction at current levels of statistical uncertainty.
A perturbed parameter model ensemble to investigate Mt. Pinatubo's 1991 initial sulfur mass emission
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Purpose. The purpose of this study was to investigate statistical differences with MR perfusion imaging features that reflect the dynamics of Gadolinium-uptake in MS lesions using dynamic texture parameter analysis (DTPA). Methods. We investigated 51 MS lesions (25 enhancing, 26 nonenhancing lesions) of 12 patients. Enhancing lesions () were prestratified into enhancing lesions with increased permeability (EL+; ) and enhancing lesions with subtle permeability (EL−; ). Histogram-based feature maps were computed from the raw DSC-image time series and the corresponding texture parameters were analyzed during the inflow, outflow, and reperfusion time intervals. Results. Significant differences () were found between EL+ and EL− and between EL+ and nonenhancing inactive lesions (NEL). Main effects between EL+ versus EL− and EL+ versus NEL were observed during reperfusion (mainly in mean and standard deviation (SD): EL+ versus EL− and EL+ versus NEL), while EL− and NEL differed only in their SD during outflow. Conclusion. DTPA allows grading enhancing MS lesions according to their perfusion characteristics. Texture parameters of EL− were similar to NEL, while EL+ differed significantly from EL− and NEL. Dynamic texture analysis may thus be further investigated as noninvasive endogenous marker of lesion formation and restoration.
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This paper proposes asymptotically optimal tests for unstable parameter process under the feasible circumstance that the researcher has little information about the unstable parameter process and the error distribution, and suggests conditions under which the knowledge of those processes does not provide asymptotic power gains. I first derive a test under known error distribution, which is asymptotically equivalent to LR tests for correctly identified unstable parameter processes under suitable conditions. The conditions are weak enough to cover a wide range of unstable processes such as various types of structural breaks and time varying parameter processes. The test is then extended to semiparametric models in which the underlying distribution in unknown but treated as unknown infinite dimensional nuisance parameter. The semiparametric test is adaptive in the sense that its asymptotic power function is equivalent to the power envelope under known error distribution.