Contribution of the apparent diffusion coefficient in perilesional edema for the assessment of brain tumors

OBJECTIVES: Diffusion-weighted MRI is sensitive to molecular motion and has been applied to the diagnosis of stroke. Our intention was to investigate its usefulness in patients with brain tumor and, in particular, in the perilesional edema. METHODS: We performed MRI of the brain, including diffusion-weighted imaging and mapping of the apparent diffusion coefficient (ADC), in 16 patients with brain tumors (glioblastomas, low-grade gliomas and metastases). ADC values were determined by the use of regions of interest positioned in areas of high signal intensities as seen on T2-weighted images and ADC maps. Measurements were taken in the tumor itself, in the area of perilesional edema and in the healthy contralateral brain. RESULTS: ADC mapping showed higher values of peritumoral edema in patients with glioblastoma (1.75 x 10(-3)mm(2)/s) and metastatic lesions (1.61 x 10(-3)mm(2)/s) compared with those who had low-grade glioma (1.40 x10(-3)mm(2)/s). The higher ADC values in the peritumoral zone were associated with lower ADC values in the tumor itself. CONCLUSIONS: The higher ADC values in the more malignant tumors probably reflect vasogenic edema, thereby allowing their differentiation from other lesions.

Diffusion-weighted imaging of the parotid gland: Influence of the choice of b-values on the apparent diffusion coefficient value

PURPOSE: To determine how the ADC value of parotid glands is influenced by the choice of b-values. MATERIALS AND METHODS: In eight healthy volunteers, diffusion-weighted echo-planar imaging (DW-EPI) was performed on a 1.5 T system, with b-values (in seconds/mm2) of 0, 50, 100, 150, 200, 250, 300, 500, 750, and 1000. ADC values were calculated by two alternative methods (exponential vs. logarithmic fit) from five different sets of b-values: (A) all b-values; (B) b=0, 50, and 100; (C) b=0 and 750; (D) b=0, 500, and 1000; and (E) b=500, 750, and 1000. RESULTS: The mean ADC values for the different settings were (in 10(-3) mm2/second, exponential fit): (A) 0.732+/-0.019, (B) 2.074+/-0.084, (C) 0.947+/-0.020, (D) 0.890+/-0.023, and (E) 0.581+/-0.021. ADC values were significantly (P <0.001) different for all pairwise comparisons of settings (A-E) of b-values, except for A vs. D (P=0.172) and C vs. D (P=0.380). The ADC(B) was significantly higher than ADC(C) or ADC(D), which was significantly higher than ADC(E). ADC values from exponential vs. logarithmic fit (P=0.542), as well as left vs. right parotid gland (P=0.962), were indistinguishable. CONCLUSION: The ADC values calculated from low b-value settings were significantly higher than those calculated from high b-value settings. These results suggest that not only true diffusion but also perfusion and saliva flow may contribute to the ADC.

Comparative Analysis of Evolving Software Systems Using the Gini Coefficient

Software metrics offer us the promise of distilling useful information from vast amounts of software in order to track development progress, to gain insights into the nature of the software, and to identify potential problems. Unfortunately, however, many software metrics exhibit highly skewed, non-Gaussian distributions. As a consequence, usual ways of interpreting these metrics --- for example, in terms of "average" values --- can be highly misleading. Many metrics, it turns out, are distributed like wealth --- with high concentrations of values in selected locations. We propose to analyze software metrics using the Gini coefficient, a higher-order statistic widely used in economics to study the distribution of wealth. Our approach allows us not only to observe changes in software systems efficiently, but also to assess project risks and monitor the development process itself. We apply the Gini coefficient to numerous metrics over a range of software projects, and we show that many metrics not only display remarkably high Gini values, but that these values are remarkably consistent as a project evolves over time.

Effects of Supplementing High or Low Quality Forages with Corn or Corn Processing Co-Products Upon Digestibility of Dry Matter and Energy by Steers

A digestibility trial, utilizing eight crossbred steers weighing initially 741 lbs. was conducted in an 8 x 8 Latin square design. High-fiber corn by-products were compared with corn as energy sources when fed in mixed diets with either lowor high-quality forage. Ground, dry corn stover and ground alfalfa hay were both fed alone or with corn grain, dried corn gluten feed (CGF), and dried corn distillers grains plus solubles (DDG) in a 1:1 ratio (dry basis). Total tract dry matter digestibility (DMD) was increased for both forages when fed with concentrates. Total tract DMD was similar in stover-based and alfalfa-based diets fed with CGF and DDG. However, stover+corn was lower in DMD than either stover+CGF and stover+DDG. Conversely, alfalfa+corn was higher in DMD than alfalfa+CGF or alfalfa+DDG. Feeding stover with corn tended to decrease digestibility of neutral detergent fiber (NDF), while feeding stover with CGF or DDG increased NDFD. There was no effect upon NDF digestion of alfalfa-based diets when fed with any of the concentrates. Feeding either forage with a concentrate increased digestible energy (DE). Stover+CGF and stover+DDG were similar in DE and were both higher in DE than stover+corn. Alfalfa+DDG tended to be higher than alfalfa+CGF and was similar to alfalfa+corn in DE. Alfalfa+CGF was lower in DE compared with alfalfa+corn. Results are interpreted to indicate that stover is more susceptible to negative feed interactions caused by corn grain than is alfalfa. Additionally, highfiber corn co-products fed with stover resulted in a positive associative effect but essentially had no associative effect when fed with alfalfa.

The Effects of High-Oil Corn or Typical Corn with or without Supplemental Fat on Diet Digestibility in Finishing Steers

Two 3 x 3 latin squares were utilized in an 84-day digestion trial with ruminally- and duodenallycannulated steers. Diets consisted of 73 to 78% whole corn grain, 12.3% corn silage and 2.0% N, with treatment differences being high-oil corn- (HOC), isogenetic typical-corn- (TC), or isogenetic typical-corn + fat- (TC+F) based diets. The HOC and TC+F diets were formulated to provide the same ether extract (EE) content. All diets were fed at 90% of ad libitum intake. Chromic oxide was used as a digestibility marker. Total tract dry matter (DM) (P=.08), organic matter (OM) (P=.08) and nitrogen (N) (P=.06) digestibilities tended to be greater for TC than HOC diets, whereas starch neutral detergent fiber (NDF), acid detergent fiber (ADF), and ether extract digestibilities were similar (P>.10). There were no differences (P>.10) in total tract dry matter, organic matter, starch, NDF, ADF, ether extract, or nitrogen digestibilities between TC+F and HOC diets or TC and TC+F diets. Ruminal digestion of dry matter, organic matter, starch, NDF, ADF, and feed nitrogen was similar (P>.10) among treatments. Microbial-nitrogen flow and efficiencies were also similar (P>.10) among treatments. Results indicate finishing steer diets composed of primarily HOC are equally or less digestible than similar diets composed of TC, and adding fat to TC diets did not affect the digestibility of the diet when fed to finishing steers.

An estimate of heavy quark momentum diffusion coefficient in gluon plasma

We calculate the momentum diffusion coefficient for heavy quarks in SU(3) gluon plasma at temperatures 1-2 times the deconfinement temperature. The momentum diffusion coefficient is extracted from a Monte Carlo calculation of the correlation function of color electric fields, in the leading order of expansion in heavy quark mass. Systematics of the calculation are examined, and compared with perturbtion theory and other estimates.

Towards the continuum limit in transport coefficient computations

The analytic continuation needed for the extraction of transport coefficients necessitates in principle a continuous function of the Euclidean time variable. We report on progress towards achieving the continuum limit for 2-point correlator measurements in thermal SU(3) gauge theory, with specific attention paid to scale setting. In particular, we improve upon the determination of the critical lattice coupling and the critical temperature of pure SU(3) gauge theory, estimating r0Tc ≃ 0.7470(7) after a continuum extrapolation. As an application the determination of the heavy quark momentum diffusion coefficient from a correlator of colour-electric fields attached to a Polyakov loop is discussed.

Nonperturbative estimate of the heavy quark momentum diffusion coefficient

We estimate the momentum diffusion coefficient of a heavy quark within a pure SU(3) plasma at a temperature of about 1.5Tc. Large-scale Monte Carlo simulations on a series of lattices extending up to 1923×48 permit us to carry out a continuum extrapolation of the so-called color-electric imaginary-time correlator. The extrapolated correlator is analyzed with the help of theoretically motivated models for the corresponding spectral function. Evidence for a nonzero transport coefficient is found and, incorporating systematic uncertainties reflecting model assumptions, we obtain κ=(1.8–3.4)T3. This implies that the “drag coefficient,” characterizing the time scale at which heavy quarks adjust to hydrodynamic flow, is η−1D=(1.8–3.4)(Tc/T)2(M/1.5  GeV)  fm/c, where M is the heavy quark kinetic mass. The results apply to bottom and, with somewhat larger systematic uncertainties, to charm quarks.

A Bayesian approach to estimating the intraclass correlation coefficient

A Bayesian approach to estimating the intraclass correlation coefficient was used for this research project. The background of the intraclass correlation coefficient, a summary of its standard estimators, and a review of basic Bayesian terminology and methodology were presented. The conditional posterior density of the intraclass correlation coefficient was then derived and estimation procedures related to this derivation were shown in detail. Three examples of applications of the conditional posterior density to specific data sets were also included. Two sets of simulation experiments were performed to compare the mean and mode of the conditional posterior density of the intraclass correlation coefficient to more traditional estimators. Non-Bayesian methods of estimation used were: the methods of analysis of variance and maximum likelihood for balanced data; and the methods of MIVQUE (Minimum Variance Quadratic Unbiased Estimation) and maximum likelihood for unbalanced data. The overall conclusion of this research project was that Bayesian estimates of the intraclass correlation coefficient can be appropriate, useful and practical alternatives to traditional methods of estimation. ^

(Table 1) Attenuation coefficient of lateral propagating light in sea ice, southern Beaufort Sea

The attenuation property of a lateral propagating light (LPL) in sea ice was measured using an artificial lamp in the Canadian Arctic during the 2007/2008 winter. A measurement method is proposed and applied whereby a recording instrument is buried in the sea ice and an artificial lamp is moved across the instrument. The apparent attenuation coefficient µ(lamda) for the lateral propagating light is obtained from the measured logarithmic relative variation rate. With the exception of blue and red lights, the attenuation coefficient changed little with wavelength, but changed considerably with depth. The vertical decrease of the attenuation coefficient was found to be correlated with salinity: the greater the salinity, the greater the attenuation coefficient. A clear linear relation of salinity and the lateral attenuation coefficient with R2 = 0.939 exists to address the close correlation of the attenuation of LPL with the scattering from the brine. The observed attenuation coefficient of LPL is much larger than that of the vertical propagation light, which we speculate to be caused by scattering. Part of this scattered component is transmitted out of the sea ice from the upper and lower surfaces.