Determinação de Espectros de Energia de Elétrons Clínicos a partir de Curvas de Porcentagem de Dose em Profundidade (PDP) utilizando o Método de Recozimento Simulado Clássico
DOI:
https://doi.org/10.29384/rbfm.2016.v10.n3.p7-10Keywords:
RadioterapiaAbstract
As curvas de porcentagem de dose em profundidade representam um conjunto importante de dados para feixes de elétrons pois descrevem claramente as propriedades dosimétricas destes. Usando uma teoria de transporte acurada ou o método Monte Carlo encontram-se diferenças obvias entre a PDP de feixes de elétrons monoenergéticos e a de feixes de elétrons clínicos à energia nominal do acelerador em um objeto simulador de água. Em radioterapia, o espectro de energia de elétrons deve ser considerado para aprimorar a acurácia do cálculo da dose toda vez que o feixe de elétrons que atinge a superfície do objeto simulador de água após atravessar às estruturas do acelerador e o ar, não é mais monoenergetico. Existem três abordagens principais para extrair o espectro de energia de elétrons desde curvas de PDP: Método Monte Carlo, Medição Direta e Reconstrução Inversa. Neste trabalho será apresentado o método de Recozimento Simulado Clássico como uma abordagem prática, consistente e simples de reconstrução inversa como sendo uma boa alternativa aos outros dois métodos.
Downloads
References
Luo Z and Jette D. On the possibility of determining an effective energy spectrum of clinical electron beams from percentage depth dose (PDD) data of broad beams. Phys.Med.Biol. 44 N177-N182. 1999.
Brahme, A., and H. Svensson. "Radiation beam charac-teristics of a 22 MeV microtron." Acta radiologica: on-cology, radiation, physics, biology 18.3: 244-272. 1979.
Gui Li et al, in: Realization and Comparison of Several Regression Algorithms for Electron Energy Spectrum Reconstruction. Chin.Phys.Lett. Vol 25, No.7, 2710. 2008.
Gui Li et al, in: Electron spectrum reconstruction as nonlinear programming model using micro-adjusting algorithm. APCMBE 2008, IFMBE Proccedings 19, pp. 451-454, 2008.
Carletti C, Meoli P and Cravero W. A modified simulated annealing algorithm for parameter determination for a hybrid virtual model. Phys.Med.Biol 51 3941-3952. 2006.
Faddegon B and Blevis I. Electron spectra derived from depth dose distribution. Med. Phys. 27, 514-526.2000.
Deng J, Jiang S, Pawlicki J and Ma C. Derivation of electron and photon energy spectra from electron beam central axis depth dose curves. Phys. Med, Biol. 46, 1429-1449. 2001.
Klevenhagen, S. C. "An algorithm to include the brems-strahlung contamination in the determination of the ab-sorbed dose in electron beams." Physics in medicine and biology 39.7, 1103. 1994.
Chvetsov A and Sandison G. Angular correction in reconstruction of electron spectra from depth dose dis-tributions. Med.Phys. 30, 2155-2158. 2003.
Chvetsov A and Sandison G, in: Reconstruction of electron spectra using singular component decompo-sition. Med.Phys. 29, 578-591. 2002.
Luo Z. A numerical method for solving the Fredholm integral equation of the first kind and its application to restore the folded radiation spectrum. Nucl. Instrum. Methods A 255 152. 1987.
Kirkpatric S et al. Optimization by Simulated Annealing. Science New Series Vol 220 No 4598. p. 671-680. 1983.
Won Y. Yang, Wenwu Cao, Tae-Sang Chung, John Morris. Applied Numerical Methods Using MATLAB. John Whiley & Sons, 2005.
Lorena LA. Otimização Combinatória, CAP 254. Labora-tório Associado de Computação e Matemática Aplica-da, INPE, Brasil. 2007.
Haeser G e Gomez M. Aspectos teóricos de Simulated Annealing e um algoritmo duas fazes em otimização global. Mat. Apl. Comput., 9, No. 3, 395-404. 2008.
Mathworks.com [homepage on the Internet]. Oviedo, Espanha: Simulated Annealing Optimization [cit-ed/acesso U2016/Abr/7]. Disponível em http://www.mathworks.com/ matlabcen-tral/fileexchange/33109-simulated-annealing-optimization/content/sim_anl.m.
Per Christian Hansen. Regularization Tools: A Matlab Package for Analysis and Solution of Discrete Ill-Posed Problems. Numerical Algorithms 6, 1-35. 1994.
Rogers D, Faddegon B, Ding G, Ma C-M, We J and Mackie T. BEAM: a Monte Carlo code to simulate radio-therapy treatment units. Med.Phys. 22 503-24. 1995.
Chai, Tianfeng, and Roland R. Draxler. "Root mean square error (RMSE) or mean absolute error (MAE)? –Arguments against avoiding RMSE in the literature." Geoscientific Model Development 7.3: 1247-1250. 2014.
Faddegon, B. A., and I. Blevis. "Electron spectra de-rived from depth dose distributions." Medical physics 27.3: 514-526. 2000.
Low, Daniel A., et al. A technique for the quantitative evaluation of dose distributions. Medical physics 25.5: 656-661. 1998.
Downloads
Published
How to Cite
Issue
Section
License
The submission of original articles to the Brazilian Journal of Medical Physics implies the transfer, by the authors, of the rights of print and digital publication. Copyright for published articles remains with the author, with journal rights on first publication. Authors may only use the same results in other publications by clearly indicating this journal as the original publisher. As we are an open access journal, free use of articles in educational, scientific, non-commercial applications is allowed, as long as the source is cited.
The Brazilian Journal of Medical Physics is under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).
