This study compares 3D dose distributions obtained with voxel S values (VSVs) for soft tissue, calculated by several methods at their current state-of-the-art, varying the degree of image blurring. The methods were: 1) convolution of Dose Point Kernel (DPK) for water, using a scaling factor method; 2) an analytical model (AM), tting the deposited energy as a function of the source-target distance; 3) a rescaling method (RSM) based on a set of high-resolution VSVs for each isotope; 4) local energy deposition (LED). VSVs calculated by direct Monte Carlo simulations were assumed as reference. Dose distributions were calculated considering spheroidal clusters with various sizes (251, 1237 and 4139 voxels of 3 mm size), uniformly lled with 131 I, 177 Lu, 188 Re or 90 Y. The activity distributions were blurred with Gaussian lters of various widths (6, 8 and 12 mm). Moreover, 3D-dosimetry was performed for 10 treatments with 90 Y derivatives. Cumulative Dose Volume Histograms (cDVHs) were compared, studying the differences in D 95% , D 50% or D max (∆D 95% , ∆D 50% and ∆D max) and dose pro les.
Purpose: Many centers aim to plan liver transarterial radioembolization (TARE) with dosimetry, even without CT-based attenuation correction (AC), or with unoptimized scatter correction (SC) methods. This work investigates the impact of presence vs absence of such corrections, and limited spatial resolution, on 3D dosimetry for TARE. Methods: Three voxelized phantoms were derived from CT images of real patients with different body sizes. Simulations of 99m Tc-SPECT projections were performed with the SIMIND code, assuming three activity distributions in the liver: uniform, inside a "liver's segment," or distributing multiple uptaking nodules ("nonuniform liver"), with a tumoral liver/healthy parenchyma ratio of 5:1. Projection data were reconstructed by a commercial workstation, with OSEM protocol not specifically optimized for dosimetry (spatial resolution of 12.6 mm), with/without SC (optimized, or with parameters predefined by the manufacturer; dual energy window), and with/without AC. Activity in voxels was calculated by a relative calibration, assuming identical microspheres and 99m Tc-SPECT counts spatial distribution. 3D dose distributions were calculated by convolution with lesions and healthy parenchyma from different reconstructions were compared with those obtained from the reference biodistribution (the "gold standard," GS), assessing differences for D95%, D70%, and D50% (i.e., minimum value of the absorbed dose to a percentage of the irradiated volume). γ tool analysis with tolerance of 3%/13 mm was used to evaluate the agreement between GS and simulated cases. The influence of deep-breathing was studied, blurring the reference biodistributions with a 3D anisotropic gaussian kernel, and performing the simulations once again. Results: Differences of the dosimetric indicators were noticeable in some cases, always negative for lesions and distributed around zero for parenchyma. Application of AC and SC reduced systematically the differences for lesions by 5%-14% for a liver segment, and by 7%-12% for a nonuniform liver. For parenchyma, the data trend was less clear, but the overall range of variability passed from −10%/40% for a liver segment, and −10%/20% for a nonuniform liver, to −13%/6% in both cases. Applying AC, SC with preset parameters gave similar results to optimized SC, as confirmed by γ tool analysis. Moreover, γ analysis confirmed that solely AC and SC are not sufficient to obtain accurate 3D dose distribution. With breathing, the accuracy worsened severely for all dosimetric indicators, above all for lesions: with AC and optimized SC, −38%/−13% in liver's segment, −61%/−40% in the nonuniform liver. For parenchyma, D50% resulted always less sensitive to breathing and sub-optimal correction methods (difference overall range: −7%/13%). Conclusions: Reconstruction protocol optimization, AC, SC, PVE and respiratory motion corrections should be implemented to obtain the best possible dosimetric accuracy. On the other side, thanks to the relative calibration, D50% inaccuracy for the healthy paren...
In this paper we discuss a novel mathematical approach to authorship attribution which we implemented recently to face a concrete problem of author recognition. The fundamental ideas for our methods came from statistical mechanics and information theory. We combine two approaches. Both of them use similarity measures between couples of texts as indicators of stylistic closeness: the first one is based on the comparison of frequencies of fixed length substrings (n-grams) throughout the texts; the second one relies on a suitable use of compression algorithms as relative entropy approximators, in the spirit of the so-called Ziv-Merhav theorem. The two methods were separately developed and then combined, together with a suitable and theoretically founded ranking analysis, to produce an original authorship attribution procedure that yielded very successful results on the specific problem to which it was applied. This ranking analysis could be of interest also in other application fields
The best predictor of myelotoxicity and blood cells nadir was obtained scaling the RM absorbed dose in terms of the estimated TV. It seems clear that the increase in skeletal uptake due to the presence of bone metastases and the assumption of full physical retention cause an overestimation of the RM absorbed dose. Nevertheless, an improvement of the dose–toxicity correlation is easily achievable by simple methods, also leading to possible improvement in multifactorial analyses of myelotoxicity.
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