993 resultados para Longitudinal imaging
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BACKGROUND AND PURPOSE Inflammation is a recognized risk factor for the vulnerable atherosclerotic plaque. The study explores the relationship between the degree of Magnetic Resonance (MR)"defined inflammation using Ultra Small Super-Paramagnetic Iron Oxide (USPIO) particles and the severity of luminal stenosis in asymptomatic carotid plaques. METHODS Seventy-one patients with an asymptomatic carotid stenosis of ĝ‰¥40% underwent multi-sequence USPIO-enhanced MR imaging. Stenosis severity was measured according to the NASCET and ECST methods. RESULTS No demonstrable relationship between inflammation as measured by USPIO-enhanced signal change and the degree of luminal stenosis was found. CONCLUSIONS Inflammation and stenosis are likely to be independent risk factors, although this needs to be further validated.
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Objective: The aim of this study was to explore whether there is a relationship between the degree of MR-defined inflammation using ultra small super-paramagnetic iron oxide (USPIO) particles, and biomechanical stress using finite element analysis (FEA) techniques, in carotid atheromatous plaques. Methods and Results: 18 patients with angiographically proven carotid stenoses underwent multi-sequence MR imaging before and 36 h after USPIO infusion. T2 * weighted images were manually segmented into quadrants and the signal change in each quadrant normalised to adjacent muscle was calculated after USPIO administration. Plaque geometry was obtained from the rest of the multi-sequence dataset and used within a FEA model to predict maximal stress concentration within each slice. Subsequently, a new statistical model was developed to explicitly investigate the form of the relationship between biomechanical stress and signal change. The Spearman's rank correlation coefficient for USPIO enhanced signal change and maximal biomechanical stress was -0.60 (p = 0.009). Conclusions: There is an association between biomechanical stress and USPIO enhanced MR-defined inflammation within carotid atheroma, both known risk factors for plaque vulnerability. This underlines the complex interaction between physiological processes and biomechanical mechanisms in the development of carotid atheroma. However, this is preliminary data that will need validation in a larger cohort of patients.
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The authors report an in vivo human examination of carotid atheroma by using the inversion-recovery ON resonance (IRON) sequence, which is able to produce positive contrast after the infusion of an ultrasmall super paramagnetic iron oxide (USPIO) contrast medium. This technique provides a method of potentially identifying inflammatory burden within carotid atheroma. This may be particularly useful in patients who currently do not meet criteria for intervention (ie, moderate symptomatic stenosis or <70% asymptomatic stenosis) to further risk-stratify this important patient cohort. A 63-year-old man was imaged at 1.5 T before and 36 hours after USPIO infusion by using the IRON sequence. Regions of interest showing profound signal loss at T2*-weighted imaging corresponded well with regions of positive contrast at IRON imaging after the administration of USPIO. These regions also showed a profound decrease in T2* measurements after USPIO infusion, whereas surrounding tissue did not. It has been shown that such strong signal loss on T2*-weighted images after USPIO infusion is indicative of USPIO uptake.
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Object. Individuals with carotid atherosclerosis develop symptoms following rupture of vulnerable plaques. Biomechanical stresses within this plaque may increase vulnerability to rupture. In this report the authors describe the use of in vivo carotid plaque imaging and computational mechanics to document the magnitude and distribution of intrinsic plaque stresses. Methods. Ten (five symptomatic and five asymptomatic) individuals underwent plaque characterization magnetic resonance (MR) imaging. Plaque geometry and composition were determined by multisequence review. Intrinsic plaque stress profiles were generated from 3D meshes by using finite element computational analysis. Differences in principal (shear) stress between normal and diseased sections of the carotid artery and between symptomatic and asymptomatic plaques were noted. Results. There was a significant difference in peak principal stress between diseased and nondiseased segments of the artery (mean difference 537.65 kPa, p < 0.05). Symptomatic plaques had higher mean stresses than asymptomatic plaques (627.6 kPa compared with 370.2 kPa, p = 0.05), which were independent of luminal stenosis and plaque composition. Conclusions. Significant differences in plaque stress exist between plaques from symptomatic individuals and those from asymptomatic individuals. The MR imaging-based computational analysis may therefore be a useful aid to identification of vulnerable plaques in vivo.
Resumo:
Inflammation is a recognized risk factor for the vulnerable atherosclerotic plaque. USPIO-enhanced MRI imaging is a promising non-i nvasive method to identify high-risk atheromatous plaque inflammation in vivo in humans, in which areas of focal signal loss on MR images have been shown to correspond to the location of activated macrophages, typically at the shoulder regions of the plaque. This is the first report in humans describing simultaneous USPIO uptake within atheroma in two different arterial territories and again emphasises that atherosclerosis is a truly systemic disease. With further work, USPIO-enhanced MR imaging may be useful in identifying inflamed vulnerable atheromatous plaques in vivo, so refining patient selection for intervention and allowing appropriate early aggressive pharmacotherapy to prevent plaque rupture.
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The thermal boundary layer along an isothermal cylinder in a porous 3edium is studied numerically by a finite difference scheme and also using the method of extended perturbation series. The series in terms of the transverse curvature parameter ξ extended to seven terms and is subsequently improved by applying the Shanks transformation twice and thrice, respectively. Results for heat transfer characteristics are found in very good agreement.
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Selection criteria and misspecification tests for the intra-cluster correlation structure (ICS) in longitudinal data analysis are considered. In particular, the asymptotical distribution of the correlation information criterion (CIC) is derived and a new method for selecting a working ICS is proposed by standardizing the selection criterion as the p-value. The CIC test is found to be powerful in detecting misspecification of the working ICS structures, while with respect to the working ICS selection, the standardized CIC test is also shown to have satisfactory performance. Some simulation studies and applications to two real longitudinal datasets are made to illustrate how these criteria and tests might be useful.
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A new photothermal imaging process which utilizes no silver has been demonstrated in obliquely deposited Se-Ge films. Band-gap irradiation of Se-Ge films has been found to give rise to phases of the type SeOx, GeO, and Se as borne by x-ray initiated Auger electron spectroscopy and x-ray photoelectron spectroscopy. Annealing of SeOx leads to the formation of SeO2. The large (several orders of magnitude) difference in vapor pressures of SeO2 and Se-Ge films results in differential evaporation of the films when annealed around 200 °C, thereby leading to imaging. Such a large contrast in evaporation rates between the exposed and unexposed regions has great potential applications in high resolution image storage and phase holography. Applied Physics Letters is copyrighted by The American Institute of Physics.
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This paper proposes a linear quantile regression analysis method for longitudinal data that combines the between- and within-subject estimating functions, which incorporates the correlations between repeated measurements. Therefore, the proposed method results in more efficient parameter estimation relative to the estimating functions based on an independence working model. To reduce computational burdens, the induced smoothing method is introduced to obtain parameter estimates and their variances. Under some regularity conditions, the estimators derived by the induced smoothing method are consistent and have asymptotically normal distributions. A number of simulation studies are carried out to evaluate the performance of the proposed method. The results indicate that the efficiency gain for the proposed method is substantial especially when strong within correlations exist. Finally, a dataset from the audiology growth research is used to illustrate the proposed methodology.
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A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.
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The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.
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In analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the 'sandwich' method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain 'bootstrapped' realizations of the parameter estimates for statistical inference. Our extensive simulation studies indicate that the variance estimators by our proposed methods can not only correct the bias of the sandwich estimator but also improve the confidence interval coverage. We applied the proposed method to a data set from a clinical trial of antibiotics for leprosy.
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The surface properties of solid state pharmaceutics are of critical importance. Processing modifies the surfaces and effects surface roughness, which influences the performance of the final dosage form in many different levels. Surface roughness has an effect on, e.g., the properties of powders, tablet compression and tablet coating. The overall goal of this research was to understand the surface structures of pharmaceutical surfaces. In this context the specific purpose was to compare four different analysing techniques (optical microscopy, scanning electron microscopy, laser profilometry and atomic force microscopy) in various pharmaceutical applications where the surfaces have quite different roughness scale. This was done by comparing the image and roughness analysing techniques using powder compacts, coated tablets and crystal surfaces as model surfaces. It was found that optical microscopy was still a very efficient technique, as it yielded information that SEM and AFM imaging are not able to provide. Roughness measurements complemented the image data and gave quantitative information about height differences. AFM roughness data represents the roughness of only a small part of the surface and therefore needs other methods like laser profilometer are needed to provide a larger scale description of the surface. The new developed roughness analysing method visualised surface roughness by giving detailed roughness maps, which showed local variations in surface roughness values. The method was able to provide a picture of the surface heterogeneity and the scale of the roughness. In the coating study, the laser profilometer results showed that the increase in surface roughness was largest during the first 30 minutes of coating when the surface was not yet fully covered with coating. The SEM images and the dispersive X-ray analysis results showed that the surface was fully covered with coating within 15 to 30 minutes. The combination of the different measurement techniques made it possible to follow the change of surface roughness and development of polymer coating. The optical imaging techniques gave a good overview of processes affecting the whole crystal surface, but they lacked the resolution to see small nanometer scale processes. AFM was used to visualize the nanoscale effects of cleaving and reveal the full surface heterogeneity, which underlies the optical imaging. Ethanol washing changed small (nanoscale) structure to some extent, but the effect of ethanol washing on the larger scale was small. Water washing caused total reformation of the surface structure at all levels.
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This paper deals with new results obtained in regard to the reconstruction properties of side-band Fresnel holograms (SBFH) of self-imaging type objects (for example, gratings) as compared with those of general objects. The major finding is that a distribution I2, which appears on the real-image plane along with the conventional real-image I1, remains a 2Z distribution (where 2Z is the axial distance between the object and its self-imaging plane) under a variety of situations, while its nature and focusing properties differ from one situation to another. It is demonstrated that the two distributions I1 and I2 can be used in the development of a novel technique for image subtraction.