Theoretical substantiation of biological efficacy enhancement for β-delayed particle decay 9 C beam: A Monte Carlo study in combination with analysis with the local effect model approach

2016 ◽  
Vol 43 (3) ◽  
pp. 1200-1211
Author(s):  
Liheng Tian ◽  
Qiang Li ◽  
Xinguo Liu ◽  
Zhongying Dai ◽  
Tingyan Fu ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Local Effect ◽  
Biological Efficacy ◽  
Theoretical Substantiation ◽  
Particle Decay ◽  
Effect Model ◽  
Model Approach

scholarly journals Radiobiological Outcomes, Microdosimetric Evaluations and Monte Carlo Predictions in Eye Proton Therapy

2021 ◽  
Vol 11 (19) ◽  
pp. 8822
Author(s):  
Giada Petringa ◽  
Marco Calvaruso ◽  
Valeria Conte ◽  
Pavel Bláha ◽  
Valentina Bravatà ◽  
...  
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Proton Therapy ◽  
Nuclear Physics ◽  
Local Effect ◽  
Clinical Settings ◽  
Effect Model ◽  
Pigmented Epithelium ◽  
Semi Empirical

CATANA (Centro di AdroTerapia ed Applicazioni Nucleari Avanzate) was the first Italian protontherapy facility dedicated to the treatment of ocular neoplastic pathologies. It is in operation at the LNS Laboratories of the Italian Institute for Nuclear Physics (INFN-LNS) and to date, 500 patients have been successfully treated. Even though proton therapy has demonstrated success in clinical settings, there is still a need for more accurate models because they are crucial for the estimation of clinically relevant RBE values. Since RBE can vary depending on several physical and biological parameters, there is a clear need for more experimental data to generate predictions. Establishing a database of cell survival experiments is therefore useful to accurately predict the effects of irradiations on both cancerous and normal tissue. The main aim of this work was to compare RBE values obtained from in-vitro experimental data with predictions made by the LEM II (Local Effect Model), Monte Carlo approaches, and semi-empirical models based on LET experimental measurements. For this purpose, the 92.1 uveal melanoma and ARPE-19 cells derived from normal retinal pigmented epithelium were selected and irradiated in the middle of clinical SOBP of the CATANA proton therapy facility. The remarkable results show the potentiality of using microdosimetric spectrum, Monte Carlo simulations and LEM model to predict not only the RBE but also the survival curves.

The FLUKA Monte Carlo code coupled with the local effect model for biological calculations in carbon ion therapy

2010 ◽  
Vol 55 (15) ◽  
pp. 4273-4289 ◽  
Author(s):  
A Mairani ◽  
S Brons ◽  
F Cerutti ◽  
A Fassò ◽  
A Ferrari ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Local Effect ◽  
Monte Carlo Code ◽  
Carbon Ion Therapy ◽  
Carbon Ion ◽  
Effect Model ◽  
Ion Therapy

Analyzing Observed Composite Differences Across Groups

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz
Keyword(s):  
Monte Carlo ◽  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Monte Carlo Study ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Latent Mean Differences ◽  
Partial Invariance ◽  
Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

Detecting Between-Groups Heteroscedasticity in MMR: A Monte Carlo Study

2011 ◽  
Author(s):  
Patrick J. Rosopa ◽  
Amber N. Schroeder ◽  
Jessica Doll
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study

Monte Carlo study of 50 nm-long single and dual-gate MODFETs: suppression of short-channel effects

1993 ◽  
Vol 3 (9) ◽  
pp. 1719-1728
Author(s):  
P. Dollfus ◽  
P. Hesto ◽  
S. Galdin ◽  
C. Brisset
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Short Channel Effects ◽  
Short Channel ◽  
Channel Effects ◽  
Dual Gate

MONTE CARLO STUDY OF EPITAXIAL OVERLAYER WITH SUBSTANTIAL LATTICE MISMATCH

1987 ◽  
Vol 48 (C5) ◽  
pp. C5-199-C5-202
Author(s):  
T. MIYASAKI ◽  
K. AIZAWA ◽  
H. AOKI ◽  
C. ITOH ◽  
M. OKAZAKI
Keyword(s):  
Monte Carlo ◽  
Lattice Mismatch ◽  
Monte Carlo Study
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