991 resultados para T2


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OBJECTIVE: Childhood-onset type 1 diabetes is associated with neurocognitive deficits, but there is limited evidence to date regarding associated neuroanatomical brain changes and their relationship to illness variables such as age at disease onset. This report examines age-related changes in volume and T2 relaxation time (a fundamental parameter of magnetic resonance imaging that reflects tissue health) across the whole brain. RESEARCH DESIGN AND METHODS: Type 1 diabetes, N = 79 (mean age 20.32 ± 4.24 years), and healthy control participants, N = 50 (mean age 20.53 ± 3.60 years). There were no substantial group differences on socioeconomic status, sex ratio, or intelligence quotient. RESULTS: Regression analyses revealed a negative correlation between age and brain changes, with decreasing gray matter volume and T2 relaxation time with age in multiple brain regions in the type 1 diabetes group. In comparison, the age-related decline in the control group was small. Examination of the interaction of group and age confirmed a group difference (type 1 diabetes vs. control) in the relationship between age and brain volume/T2 relaxation time. CONCLUSIONS: We demonstrated an interaction between age and group in predicting brain volumes and T2 relaxation time such that there was a decline in these outcomes in type 1 diabetic participants that was much less evident in control subjects. Findings suggest the neurodevelopmental pathways of youth with type 1 diabetes have diverged from those of their healthy peers by late adolescence and early adulthood but the explanation for this phenomenon remains to be clarified.

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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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PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.

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We develop several hardware and software simulation blocks for the TinyOS-2 (TOSSIM-T2) simulator. The choice of simulated hardware platform is the popular MICA2 mote. While the hardware simulation elements comprise of radio and external flash memory, the software blocks include an environment noise model, packet delivery model and an energy estimator block for the complete system. The hardware radio block uses the software environment noise model to sample the noise floor. The packet delivery model is built by establishing the SNR-PRR curve for the MICA2 system. The energy estimator block models energy consumption by Micro Controller Unit(MCU), Radio, LEDs, and external flash memory. Using the manufacturerpsilas data sheets we provide an estimate of the energy consumed by the hardware during transmission, reception and also track several of the MCUs states with the associated energy consumption. To study the effectiveness of this work, we take a case study of a paper presented in [1]. We obtain three sets of results for energy consumption through mathematical analysis, simulation using the blocks built into PowerTossim-T2 and finally laboratory measurements. Since there is a significant match between these result sets, we propose our blocks for T2 community to effectively test their application energy requirements and node life times.

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We develop several hardware and software simulation blocks for the TinyOS-2 (TOSSIM-T2) simulator. The choice of simulated hardware platform is the popular MICA2 mote. While the hardware simulation elements comprise of radio and external flash memory, the software blocks include an environment noise model, packet delivery model and an energy estimator block for the complete system. The hardware radio block uses the software environment noise model to sample the noise floor.The packet delivery model is built by establishing the SNR-PRR curve for the MICA2 system. The energy estimator block models energy consumption by Micro Controller Unit(MCU), Radio,LEDs, and external flash memory. Using the manufacturer’s data sheets we provide an estimate of the energy consumed by the hardware during transmission, reception and also track several of the MCUs states with the associated energy consumption. To study the effectiveness of this work, we take a case study of a paper presented in [1]. We obtain three sets of results for energy consumption through mathematical analysis, simulation using the blocks built into PowerTossim-T2 and finally laboratory measurements. Since there is a significant match between these result sets, we propose our blocks for T2 community to effectively test their application energy requirements and node life times.

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[ES]El estándar de radiodifusión de televisión digital terrestre DVB-T (Digital Video Broadcasting - Terrestrial) es uno de los estándares más extendidos en todo el mundo. Su sucesor, DVB-T2, ha sido desplegado en 24 países y adoptado por otros 32 a lo largo de los últimos cinco años. Este despliegue ha coincidido con el rápido desarrollo de la telefonía móvil, con la que comparte la banda UHF. Debido a las limitaciones del espectro, es necesario estudiar la posibilidad de ofrecer los servicios de DVB-T2 en la banda VHF. El objetivo de este trabajo de fin de grado es estudiar los criterios de planificación de las redes DVB-T2 en la banda VHF. Para ello se analizan las áreas afectadas por el cambio de banda, como son la estimación del campo eléctrico, los características de los componentes de transmisión y recepción de la señal y los parámetros estándar. Además, se calculan las intensidades mínimas de campo y los alcances máximos de cobertura para diferentes configuraciones.

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[Es]Este documento explica el procedimiento seguido para desarrollar la última etapa de un decodificador de DVB-T2, que consiste en la extracción de un archivo de vídeo desde un archivo binario resultante del resto del decodificador. Este decodificador se trata del software de un receptor desarrollado por el departamento de TSR (Tratamiento de Señal y Radiocomunicaciones) de la Escuela de Ingenieros de Bilbao en el año 2010. Dicho software es capaz de analizar la señal recibida de DVB-T2 para calcular la tasa de errores y conocer otros parámetros relevantes como el tipo de modulación utilizado. No obstante, para analizar de manera subjetiva las mejoras de DVB-T2 e incluso para determinar de qué manera afectan los errores a la calidad de la imagen es necesario visualizar el video transmitido. Por esta razón se ha comenzado un proyecto en el que el objetivo es programar un nuevo software que proporcione un archivo que contenga el video en cuestión. Este software se ha programado en lenguaje del programa Matlab, y toma el fichero resultante del receptor como entrada, para procesarlo y obtener uno nuevo con el vídeo. De modo que una vez programado y probado para su corrección, se aplica a continuación del receptor del departamento TSR. Una vez obtenido el vídeo es posible comparar la calidad de la imagen con diferentes tasas de error en la comunicación, simulando transmisiones en diferentes ámbitos cada uno con su correspondiente ruido. De esta manera, se estima con muy alta precisión el comportamiento de una transmisión real dependiendo de la climatología y otros factores que afecten a la relación señal a ruido.

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The 2009 International Society of Urological Pathology consensus conference in Boston made recommendations regarding the standardization of pathology reporting of radical prostatectomy specimens. Issues relating to the substaging of pT2 prostate cancers according to the TNM 2002/2010 system, reporting of tumor size/volume and zonal location of prostate cancers were coordinated by working group 2. A survey circulated before the consensus conference demonstrated that 74% of the 157 participants considered pT2 substaging of prostate cancer to be of clinical and/or academic relevance. The survey also revealed a considerable variation in the frequency of reporting of pT2b substage prostate cancer, which was likely a consequence of the variable methodologies used to distinguish pT2a from pT2b tumors. Overview of the literature indicates that current pT2 substaging criteria lack clinical relevance and the majority (65.5%) of conference attendees wished to discontinue pT2 substaging. Therefore, the consensus was that reporting of pT2 substages should, at present, be optional. Several studies have shown that prostate cancer volume is significantly correlated with other clinicopathological features, including Gleason score and extraprostatic extension of tumor; however, most studies fail to demonstrate this to have prognostic significance on multivariate analysis. Consensus was reached with regard to the reporting of some quantitative measure of the volume of tumor in a prostatectomy specimen, without prescribing a specific methodology. Incorporation of the zonal and/or anterior location of the dominant/index tumor in the pathology report was accepted by most participants, but a formal definition of the identifying features of the dominant/index tumor remained undecided.

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In coronary magnetic resonance angiography, a magnetization-preparation scheme for T2 -weighting (T2 Prep) is widely used to enhance contrast between the coronary blood-pool and the myocardium. This prepulse is commonly applied without spatial selection to minimize flow sensitivity, but the nonselective implementation results in a reduced magnetization of the in-flowing blood and a related penalty in signal-to-noise ratio. It is hypothesized that a spatially selective T2 Prep would leave the magnetization of blood outside the T2 Prep volume unaffected and thereby lower the signal-to-noise ratio penalty. To test this hypothesis, a spatially selective T2 Prep was implemented where the user could freely adjust angulation and position of the T2 Prep slab to avoid covering the ventricular blood-pool and saturating the in-flowing spins. A time gap of 150 ms was further added between the T2 Prep and other prepulses to allow for in-flow of a larger volume of unsaturated spins. Consistent with numerical simulation, the spatially selective T2 Prep increased in vivo human coronary artery signal-to-noise ratio (42.3 ± 2.9 vs. 31.4 ± 2.2, n = 22, P < 0.0001) and contrast-to-noise-ratio (18.6 ± 1.5 vs. 13.9 ± 1.2, P = 0.009) as compared to those of the nonselective T2 Prep. Additionally, a segmental analysis demonstrated that the spatially selective T2 Prep was most beneficial in proximal and mid segments where the in-flowing blood volume was largest compared to the distal segments. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.