The LRA of EBT-XD is greatly reduced when compared to EBT3. This in combination with its accuracy from 0 to 3000 cGy and minimal energy dependence from 6 to 18 MV makes EBT-XD film well suited for dosimetric measurements in high dose SRS/SBRT applications.
Daily weight gains and food intakes were measured in male, 120-g rats fed graded levels of dietary casein. After 14 d, serum and brain amino acid concentrations were measured. All physiological responses were tested for a functional relationship to dietary casein concentration. Food intake, weight gain and many serum amino acid profiles were shown to be saturable functions of percent casein in the diet. In general, essential amino acids increased in serum with increasing dietary casein concentration while nonessential amino acids decreased with increasing dietary casein concentration. Brain amino acid concentrations were shown to be linear functions of serum levels with the exceptions of phenylalanine and the acidic amino acids. Most amino acids showed a smaller range of values in brain than in serum. The exceptions were the levels of threonine, glutamine, serine and histidine, which were three times greater in brain than in serum. Brain levels of the neutral amino acids tryptophan and tyrosine were highly correlated with the amino acid/neutral amino acid ratios in serum, whereas leucine was negatively correlated. Brain histidine, which was inversely correlated with dietary casein, was found to correlate with specific food intake patterns. The four-parameter mathematical model for physiological responses was able to predict all the observed saturation type responses in the experiment.
In three separate experiments, growing, male Sprague-Dawley rats were fed diets which contained: 1) graded levels of fiber 0-70%, 2) graded levels of pyridoxine 1-10 mg/kg diet, and 3) graded levels of casein 0-30%. The following physiological responses were measured in each respective experiment: 1) food intake, weight gain, serum triglycerides, 2) food intake, weight gain, SGPT levels, and 3) weight specific food intake, weight gain, relative testes weight. Diets were fed as a single source, and in each case, physiological response could be predicted as a function of dietary nutrient concentration. When self-selection is prevented, rats establish new steady-state response profiles, which are sigmoidal in shape and dependent on the interaction of the rats' genetic potential with the environmental configuration.
To investigate the dependency of dose-volume histogram (DVH) behavior and precision on underlying discretization using shapes and dose distributions with known analytical DVHs for five commercial DVH calculators. Methods: DVHs and summary metrics were extracted from all five systems using synthetic cone and cylinder objects for which the true volume and DVH curves were known. Trends in the curves and metrics were explored by varying the underlying voxelization of the CT image, structure set, and dose grid as well by varying the geometry of the structure and direction of a linear dose gradient. Using synthetic structures allowed for comparison with ground truth DVH curves to assess their accuracy while an algorithm was additionally developed to assess the precision of each system. The precision was calculated with a novel algorithm that treats any "stair step" behavior in a DVH curve as an uncertainty band and calculates the width, characterized as a percent difference, of the band for various DVH metrics. The underlying voxelization was additionally changed and DVHs were extracted for two clinical examples. The details of how each system calculated DVHs were also investigated and tendencies in the calculated curves, metrics, and precision were related to choices made in the calculation methodology. Results: Calculation methodology differences that had a noticeable impact on the DVH curves and summary metrics include supersampling beyond the input grids and interpretation of the superior and inferior ends of the structures. Among the systems studied, the median precision ranged from 0.902% to 3.22%, and interquartile ranges varied from 1.09% to 3.91%. Conclusions: Commercial dose-evaluation solutions can calculate different DVH curves, structure volume measures, and dose statistics for the same input data due to differences in their calculation methodologies. This study highlights the importance of understanding and investigating the DVH calculation when considering a new clinical system and when using more than one system for data transfer. K E Y W O R D S dose-volume histogram, DVH analysis, treatment planning systems
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