Parameter estimation for a mechanistic model of high dose irradiation damage using Nelder-Mead simplex method and genetic algorithm

Radiation therapy is one of the cancer cells treatments that use high-energy radiation to shrink tumors and kill cancer cells. Radiation therapy kills cancer cells by damaging their DNA directly or creates charged particles within the cells that can in turn damage the DNA. As a side effect of the tr...

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Bibliographic Details
Main Authors: Mohd. Siam, Fuaada, Ahmad Kamal, Mohamad Hidayad, Johar, Farhana
Format: Article
Language:English
Published: Penerbit UTM Press 2016
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Online Access:http://eprints.utm.my/id/eprint/71406/1/FuaadaMohdSiam2016_Parameterestimationforamechanistic.pdf
http://eprints.utm.my/id/eprint/71406/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006063979&doi=10.11113%2fjt.v78.10146&partnerID=40&md5=e80c3d30d849080f4d67060fc267c5c4
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Institution: Universiti Teknologi Malaysia
Language: English
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Summary:Radiation therapy is one of the cancer cells treatments that use high-energy radiation to shrink tumors and kill cancer cells. Radiation therapy kills cancer cells by damaging their DNA directly or creates charged particles within the cells that can in turn damage the DNA. As a side effect of the treatment, the radiation therapy can also damage the normal cell that located at parts of our body. The main goals of radiation therapy are to maximize the damaging of tumors cell and minimize the damage of normal tissue cell. Hence, in this study, we adopt an existing model of high dose irradiation damage. The purpose of this study is to estimate the six parameters of the model which are involved. Two optimization algorithms are used in order to estimate the parameters: Nelder-Mead (NM) simplex method and Genetic Algorithm (GA). Both methods have to achieve the objective function which is to minimize the sum of square error (SSE) between the experimental data and the simulation data. The performances of both algorithms are compared based on the computational time, number of iteration and value of sum of square error. The optimization process is carried out using MATLAB programming built-in functions. The parameters estimation results shown that Nelder-Mead simplex method is more superior compare to Genetic Algorithm for this problem.