Monte Carlo evaluation of the relationship between absorbed dose and contrast-to-noise ratio in coherent scatter breast CT

2015 ◽  
Author(s):  
B. Ghammraoui ◽  
L. M. Popescu ◽  
A. Badal
Keyword(s):  
Monte Carlo ◽  
Absorbed Dose ◽  
Breast Ct ◽  
Coherent Scatter ◽  
Monte Carlo Evaluation ◽  
Noise Ratio ◽  
The Relationship

SU-F-I-53: Coded Aperture Coherent Scatter Spectral Imaging of the Breast: A Monte Carlo Evaluation of Absorbed Dose

2016 ◽  
Vol 43 (6Part8) ◽  
pp. 3398-3399 ◽  
Author(s):  
R Morris ◽  
M Lakshmanan ◽  
G Fong ◽  
A Kapadia ◽  
J Greenberg
Keyword(s):  
Monte Carlo ◽  
Absorbed Dose ◽  
Spectral Imaging ◽  
Coded Aperture ◽  
Coherent Scatter ◽  
Monte Carlo Evaluation

Coded aperture coherent scatter imaging for breast cancer detection: a Monte Carlo evaluation

2016 ◽  
Author(s):  
Manu N. Lakshmanan ◽  
Robert E. Morris ◽  
Joel A. Greenberg ◽  
Ehsan Samei ◽  
Anuj J. Kapadia
Keyword(s):  
Breast Cancer ◽  
Monte Carlo ◽  
Cancer Detection ◽  
Breast Cancer Detection ◽  
Coded Aperture ◽  
Coherent Scatter ◽  
Monte Carlo Evaluation

scholarly journals A Monte Carlo Determination of Dose and Range Uncertainties for Preclinical Studies with a Proton Beam

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1889
Author(s):  
Arthur Bongrand ◽  
Charbel Koumeir ◽  
Daphnée Villoing ◽  
Arnaud Guertin ◽  
Ferid Haddad ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Proton Beam ◽  
Dose Response ◽  
Small Animal ◽  
Absorbed Dose ◽  
Normal Tissue Damage ◽  
Dose Homogeneity ◽  
And Control ◽  
The Impact

Proton therapy (PRT) is an irradiation technique that aims at limiting normal tissue damage while maintaining the tumor response. To study its specificities, the ARRONAX cyclotron is currently developing a preclinical structure compatible with biological experiments. A prerequisite is to identify and control uncertainties on the ARRONAX beamline, which can lead to significant biases in the observed biological results and dose–response relationships, as for any facility. This paper summarizes and quantifies the impact of uncertainty on proton range, absorbed dose, and dose homogeneity in a preclinical context of cell or small animal irradiation on the Bragg curve, using Monte Carlo simulations. All possible sources of uncertainty were investigated and discussed independently. Those with a significant impact were identified, and protocols were established to reduce their consequences. Overall, the uncertainties evaluated were similar to those from clinical practice and are considered compatible with the performance of radiobiological experiments, as well as the study of dose–response relationships on this proton beam. Another conclusion of this study is that Monte Carlo simulations can be used to help build preclinical lines in other setups.

Development of SiO2 based doped with LiF, Cr2O3, CoO4 and B2O3 glasses for gamma and fast neutron shielding

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Bünyamin Aygün ◽  
Erdem Şakar ◽  
Abdulhalik Karabulut ◽  
Bünyamin Alım ◽  
Mohammed I. Sayyed ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Fast Neutron ◽  
Cross Sections ◽  
Gamma Ray ◽  
Absorbed Dose ◽  
Neutron Shielding ◽  
Shielding Properties ◽  
Effective Neutron ◽  
Simulation Codes

AbstractIn this study, the fast neutron and gamma-ray absorption capacities of the new glasses have been investigated, which are obtained by doping CoO,CdWO4,Bi2O3, Cr2O3, ZnO, LiF,B2O3 and PbO compounds to SiO2 based glasses. GEANT4 and FLUKA Monte Carlo simulation codes have been used in the planning of the samples. The glasses were produced using a well-known melt-quenching technique. The effective neutron removal cross-sections, mean free paths, half-value layer, and transmission numbers of the fabricated glasses have been calculated through both GEANT4 and FLUKA Monte Carlo simulation codes. Experimental neutron absorbed dose measurements have been carried out. It was found that GS4 glass has the best neutron protection capacity among the produced glasses. In addition to neutron shielding properties, the gamma-ray attenuation capacities, were calculated using newly developed Phy-X/PSD software. The gamma-ray shielding properties of GS1 and GS2 are found to be equivalent to Pb-based glass.

A Monte Carlo evaluation of growth mixture modeling

2021 ◽  
pp. 1-14
Author(s):  
Tiffany M. Shader ◽  
Theodore P. Beauchaine
Keyword(s):  
Monte Carlo ◽  
Growth Mixture Modeling ◽  
Mixture Modeling ◽  
Fit Indices ◽  
Linear Quadratic ◽  
Growth Mixture ◽  
True Number ◽  
Monte Carlo Evaluation ◽  
Wrong Number ◽  
State Of Affairs

Abstract Growth mixture modeling (GMM) and its variants, which group individuals based on similar longitudinal growth trajectories, are quite popular in developmental and clinical science. However, research addressing the validity of GMM-identified latent subgroupings is limited. This Monte Carlo simulation tests the efficiency of GMM in identifying known subgroups (k = 1–4) across various combinations of distributional characteristics, including skew, kurtosis, sample size, intercept effect size, patterns of growth (none, linear, quadratic, exponential), and proportions of observations within each group. In total, 1,955 combinations of distributional parameters were examined, each with 1,000 replications (1,955,000 simulations). Using standard fit indices, GMM often identified the wrong number of groups. When one group was simulated with varying skew and kurtosis, GMM often identified multiple groups. When two groups were simulated, GMM performed well only when one group had steep growth (whether linear, quadratic, or exponential). When three to four groups were simulated, GMM was effective primarily when intercept effect sizes and sample sizes were large, an uncommon state of affairs in real-world applications. When conditions were less ideal, GMM often underestimated the correct number of groups when the true number was between two and four. Results suggest caution in interpreting GMM results, which sometimes get reified in the literature.

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