A model of cellular dosimetry for macroscopic tumors in radiopharmaceutical therapy.

PURPOSE: In the radiopharmaceutical therapy approach to the fight against cancer, in particular when it comes to translating laboratory results to the clinical setting, modeling has served as an invaluable tool for guidance and for understanding the processes operating at the cellular level and how these relate to macroscopic observables. Tumor control probability (TCP) is the dosimetric end point quantity of choice which relates to experimental and clinical data: it requires knowledge of individual cellular absorbed doses since it depends on the assessment of the treatment's ability to kill each and every cell. Macroscopic tumors, seen in both clinical and experimental studies, contain too many cells to be modeled individually in Monte Carlo simulation; yet, in particular for low ratios of decays to cells, a cell-based model that does not smooth away statistical considerations associated with low activity is a necessity. The authors present here an adaptation of the simple sphere-based model from which cellular level dosimetry for macroscopic tumors and their end point quantities, such as TCP, may be extrapolated more reliably. METHODS: Ten homogenous spheres representing tumors of different sizes were constructed in GEANT4. The radionuclide 131I was randomly allowed to decay for each model size and for seven different ratios of number of decays to number of cells, N(r): 1000, 500, 200, 100, 50, 20, and 10 decays per cell. The deposited energy was collected in radial bins and divided by the bin mass to obtain the average bin absorbed dose. To simulate a cellular model, the number of cells present in each bin was calculated and an absorbed dose attributed to each cell equal to the bin average absorbed dose with a randomly determined adjustment based on a Gaussian probability distribution with a width equal to the statistical uncertainty consistent with the ratio of decays to cells, i.e., equal to Nr-1/2. From dose volume histograms the surviving fraction of cells, equivalent uniform dose (EUD), and TCP for the different scenarios were calculated. Comparably sized spherical models containing individual spherical cells (15 microm diameter) in hexagonal lattices were constructed, and Monte Carlo simulations were executed for all the same previous scenarios. The dosimetric quantities were calculated and compared to the adjusted simple sphere model results. The model was then applied to the Bortezomib-induced enzyme-targeted radiotherapy (BETR) strategy of targeting Epstein-Barr virus (EBV)-expressing cancers. RESULTS: The TCP values were comparable to within 2% between the adjusted simple sphere and full cellular models. Additionally, models were generated for a nonuniform distribution of activity, and results were compared between the adjusted spherical and cellular models with similar comparability. The TCP values from the experimental macroscopic tumor results were consistent with the experimental observations for BETR-treated 1 g EBV-expressing lymphoma tumors in mice. CONCLUSIONS: The adjusted spherical model presented here provides more accurate TCP values than simple spheres, on par with full cellular Monte Carlo simulations while maintaining the simplicity of the simple sphere model. This model provides a basis for complementing and understanding laboratory and clinical results pertaining to radiopharmaceutical therapy.

Quantitative analysis of crystal/grain sizes and their distributions in 2D and 3D

We review methods to estimate the average crystal (grain) size and the crystal (grain) size distribution in solid rocks. Average grain sizes often provide the base for stress estimates or rheological calculations requiring the quantification of grain sizes in a rock's microstructure. The primary data for grain size data are either 1D (i.e. line intercept methods), 2D (area analysis) or 3D (e.g., computed tomography, serial sectioning). These data have been used for different data treatments over the years, whereas several studies assume a certain probability function (e.g., logarithm, square root) to calculate statistical parameters as the mean, median, mode or the skewness of a crystal size distribution. The finally calculated average grain sizes have to be compatible between the different grain size estimation approaches in order to be properly applied, for example, in paleo-piezometers or grain size sensitive flow laws. Such compatibility is tested for different data treatments using one- and two-dimensional measurements. We propose an empirical conversion matrix for different datasets. These conversion factors provide the option to make different datasets compatible with each other, although the primary calculations were obtained in different ways. In order to present an average grain size, we propose to use the area-weighted and volume-weighted mean in the case of unimodal grain size distributions, respectively, for 2D and 3D measurements. The shape of the crystal size distribution is important for studies of nucleation and growth of minerals. The shape of the crystal size distribution of garnet populations is compared between different 2D and 3D measurements, which are serial sectioning and computed tomography. The comparison of different direct measured 3D data; stereological data and direct presented 20 data show the problems of the quality of the smallest grain sizes and the overestimation of small grain sizes in stereological tools, depending on the type of CSD. (C) 2011 Published by Elsevier Ltd.

A model of cellular dosimetry for macroscopic tumors in radiopharmaceutical therapy.

PURPOSE: In the radiopharmaceutical therapy approach to the fight against cancer, in particular when it comes to translating laboratory results to the clinical setting, modeling has served as an invaluable tool for guidance and for understanding the processes operating at the cellular level and how these relate to macroscopic observables. Tumor control probability (TCP) is the dosimetric end point quantity of choice which relates to experimental and clinical data: it requires knowledge of individual cellular absorbed doses since it depends on the assessment of the treatment's ability to kill each and every cell. Macroscopic tumors, seen in both clinical and experimental studies, contain too many cells to be modeled individually in Monte Carlo simulation; yet, in particular for low ratios of decays to cells, a cell-based model that does not smooth away statistical considerations associated with low activity is a necessity. The authors present here an adaptation of the simple sphere-based model from which cellular level dosimetry for macroscopic tumors and their end point quantities, such as TCP, may be extrapolated more reliably. METHODS: Ten homogenous spheres representing tumors of different sizes were constructed in GEANT4. The radionuclide 131I was randomly allowed to decay for each model size and for seven different ratios of number of decays to number of cells, N(r): 1000, 500, 200, 100, 50, 20, and 10 decays per cell. The deposited energy was collected in radial bins and divided by the bin mass to obtain the average bin absorbed dose. To simulate a cellular model, the number of cells present in each bin was calculated and an absorbed dose attributed to each cell equal to the bin average absorbed dose with a randomly determined adjustment based on a Gaussian probability distribution with a width equal to the statistical uncertainty consistent with the ratio of decays to cells, i.e., equal to Nr-1/2. From dose volume histograms the surviving fraction of cells, equivalent uniform dose (EUD), and TCP for the different scenarios were calculated. Comparably sized spherical models containing individual spherical cells (15 microm diameter) in hexagonal lattices were constructed, and Monte Carlo simulations were executed for all the same previous scenarios. The dosimetric quantities were calculated and compared to the adjusted simple sphere model results. The model was then applied to the Bortezomib-induced enzyme-targeted radiotherapy (BETR) strategy of targeting Epstein-Barr virus (EBV)-expressing cancers. RESULTS: The TCP values were comparable to within 2% between the adjusted simple sphere and full cellular models. Additionally, models were generated for a nonuniform distribution of activity, and results were compared between the adjusted spherical and cellular models with similar comparability. The TCP values from the experimental macroscopic tumor results were consistent with the experimental observations for BETR-treated 1 g EBV-expressing lymphoma tumors in mice. CONCLUSIONS: The adjusted spherical model presented here provides more accurate TCP values than simple spheres, on par with full cellular Monte Carlo simulations while maintaining the simplicity of the simple sphere model. This model provides a basis for complementing and understanding laboratory and clinical results pertaining to radiopharmaceutical therapy.

High cefepime plasma concentrations and neurological toxicity in febrile neutropenic patients with mild impairment of renal function.

High-dose cefepime therapy is recommended for febrile neutropenia. Safety issues have been raised in a recent meta-analysis reporting an increased risk of mortality during cefepime therapy. Cefepime-related neurological toxicity has been associated with overdosing due to severe renal dysfunction. This study aimed to investigate the association between cefepime plasma concentrations and neurological toxicity in febrile neutropenic patients. Cefepime trough concentrations (by high-performance liquid chromatography) were retrospectively analyzed for 30 adult febrile neutropenic patients receiving the recommended high-dose regimen (6 g/day for a glomerular filtration rate [GFR] of >50 ml/min). The dose adjustment to renal function was evaluated by the ratio of the cefepime daily dose per 100 ml/min of glomerular filtration. The association between cefepime plasma concentrations and neurological toxicity was assessed on the basis of consistent neurological symptoms and/or signs (by NCI criteria). The median cefepime concentration was 8.7 mg/liter (range, 2.1 to 38 mg/liter) at a median of 4 days (range, 2 to 15 days) after the start of therapy. Neurological toxicity (altered mental status, hallucinations, or myoclonia) was attributed to cefepime in 6/30 (20%) patients (median GFR, 45 ml/min; range, 41 to 65 ml/min) receiving a median dose of 13.2 g/day per 100 ml/min GFR (range, 9.2 to 14.3 g/day per 100 ml/min GFR). Cefepime discontinuation resulted in complete neurological recovery for five patients and improvement for one patient. A multivariate logistic regression model confirmed high cefepime concentrations as an independent predictor of neurological toxicity, with a 50% probability threshold at ≥22 mg/liter (P = 0.05). High cefepime plasma concentrations are associated with neurological toxicity in febrile neutropenic patients with mild renal dysfunction. Careful adherence to normalized dosing per 100 ml/min GFR is crucial. Monitoring of plasma concentrations may contribute to preventing neurological toxicity of high-dose therapy for this life-threatening condition.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

The influence of environmental conditions on immune responses, morphology and recapture probability of nestling house martins (Delichon urbica)

Nestling birds produced later in the season are hypothesized to be of poor quality with a low probability of survival and recruitment. In a Spanish population of house martins (Delichon urbica), we first compared reproductive success, immune responses and morphological traits between the first and the second broods. Second, we investigated the effects of an ectoparasite treatment and breeding date on the recapture rate the following year. Due probably to a reverse situation in weather conditions during the experiment, with more rain during rearing of the first brood, nestlings reared during the second brood were in better condition and had stronger immune responses compared with nestlings from the first brood. Contrary to other findings on house martins, we found a similar recapture rate for chicks reared during the first and the second brood. Furthermore, ectoparasitic house martin bugs had no significant effect on the recapture rate. Recaptured birds had similar morphology but higher immunoglobulin levels when nestlings compared with non-recaptured birds. This result implies that a measure of immune function is a better predictor of survival than body condition per se.

Three-dimensional ordered-subset expectation maximization iterative protocol for evaluation of left ventricular volumes and function by quantitative gated SPECT: a dynamic phantom study.

The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.

The contact region between three domains of the extracellular loop of ASIC1a is critical for channel function.

Acid-sensing ion channels are members of the epithelial Na(+) channel/degenerin family. They are neuronal nonvoltage-gated Na(+) channels that are activated by extracellular acidification. In this study, we investigated the role of a highly conserved region of the extracellular part of ASIC1a that forms the contact between the finger domain, the adjacent beta-ball, and the upper palm domain in ASIC1a. The finger domain contributes to the pH-dependent gating and is linked via this contact zone to the rest of the protein. We found that mutation to Cys of residues in this region led to decreased channel expression and current amplitudes. Exposure of the engineered Cys residues to Cd(2+) or to charged methane thiosulfonate sulfhydryl reagents further reduced current amplitudes. This current inhibition was not due to changes in acid-sensing ion channel pH dependence or unitary conductance and was likely due to a decrease of the probability of channel opening. For some mutants, the effect of sulfhydryl reagents depended on the pH of exposure in the range 7.4 to 6.8, suggesting that this zone undergoes conformational changes during inactivation. Our study identifies a region in ASIC1a whose integrity is required for normal channel function.

Probabilistic electrical resistivity tomography of a CO2 sequestration analog

Electrical resistivity tomography (ERT) is a well-established method for geophysical characterization and has shown potential for monitoring geologic CO2 sequestration, due to its sensitivity to electrical resistivity contrasts generated by liquid/gas saturation variability. In contrast to deterministic inversion approaches, probabilistic inversion provides the full posterior probability density function of the saturation field and accounts for the uncertainties inherent in the petrophysical parameters relating the resistivity to saturation. In this study, the data are from benchtop ERT experiments conducted during gas injection into a quasi-2D brine-saturated sand chamber with a packing that mimics a simple anticlinal geological reservoir. The saturation fields are estimated by Markov chain Monte Carlo inversion of the measured data and compared to independent saturation measurements from light transmission through the chamber. Different model parameterizations are evaluated in terms of the recovered saturation and petrophysical parameter values. The saturation field is parameterized (1) in Cartesian coordinates, (2) by means of its discrete cosine transform coefficients, and (3) by fixed saturation values in structural elements whose shape and location is assumed known or represented by an arbitrary Gaussian Bell structure. Results show that the estimated saturation fields are in overall agreement with saturations measured by light transmission, but differ strongly in terms of parameter estimates, parameter uncertainties and computational intensity. Discretization in the frequency domain (as in the discrete cosine transform parameterization) provides more accurate models at a lower computational cost compared to spatially discretized (Cartesian) models. A priori knowledge about the expected geologic structures allows for non-discretized model descriptions with markedly reduced degrees of freedom. Constraining the solutions to the known injected gas volume improved estimates of saturation and parameter values of the petrophysical relationship. (C) 2014 Elsevier B.V. All rights reserved.

Effect on renal function of tenofovir co-administered with either efavirenz or boosted lopinavir or boosted atazanavir: the Swiss HIV Cohort Study

Reduced re'nal function has been reported with tenofovir disoproxil fumarate (TDF). It is not clear whether TDF co-administered with a boosted protease inhibitor (PI) leads to a greater decline in renal function than TDF co-administered with a non-nucleoside reverse transcriptase inhibitor (NNRTI).Methods: We selected ail antiretroviral therapy-naive patients in the Swiss HIV Cohort Study (SHCS) with calibrated or corrected serum creatinine measurements starting antiretroviral therapy with TDF and either efavirenz (EFV) or the ritonavir-boosted PIs, lopinavir (LPV/r) or atazanavir (ATV/r). As a measure of renal function, we used the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation to estimate the glomerular filtration rate (eGFR). We calculated the difference in eGFR over time between two therapies using a marginal model for repeated measures. In weighted analyses, observations were weighted by the product of their point of treatment and censoring weights to adjust for differences both in the sort of patients starting each therapy and in the sort of patients remaining on each therapy over time.Results: By March 2011, 940 patients with at least one creatinine measurement on a first therapy with either TDF and EFV (n=484), TDF and LPVlr (n=269) or TDF and ATV/r (n=187) had been followed for a median of 1. 7, 1.2 and 1.3 years, respectively. Table 1 shows the difference in average estimated GFR (eGFR) over time since starting cART for two marginal models. The first model was not adjusted for potential confounders; the second mode! used weights to adjust for confounders. The results suggest a greater decline in renal function during the first 6 months if TDF is used with a PI rather than with an NNRTI, but no further difference between these therapies after the first 6 months. TDF and ATV/r may lead to a greater decline in the first 6 months than TDF and LPVlr.Conclusions: TDF co-administered with a boosted PI leads to a greater de cline in renal function over the first 6 months of therapy than TDF co-administered with an NNRTI; this decline may be worse with ATV/r than with LPV/r.