Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative

This paper presents an improved numerical simulation and optimization of radiotherapy cancer treatments. The model used was obtained by integrating the Caputo fractional derivative and the linear-quadratic with the repopulation model into the previous radiotherapy cancer treatment model. Taking adva...

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Main Authors: Faraloya, M. F., Shafie, S., Siam, F. M., M., R., Ajadi, S. O.
Format: Article
Published: Universiti Putra Malaysia 2021
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Online Access:http://eprints.utm.my/id/eprint/94276/
https://einspem.upm.edu.my/journal/abstract/vol15issue2/Article%201[Feraloya%20et%20al.].pdf
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spelling my.utm.942762022-03-31T14:45:06Z http://eprints.utm.my/id/eprint/94276/ Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative Faraloya, M. F. Shafie, S. Siam, F. M. M., R. Ajadi, S. O. QA Mathematics This paper presents an improved numerical simulation and optimization of radiotherapy cancer treatments. The model used was obtained by integrating the Caputo fractional derivative and the linear-quadratic with the repopulation model into the previous radiotherapy cancer treatment model. Taking advantage of the existing model factors and parameters, especially the clinical data of six cancer patients treated with radiotherapy, the resulting model equations were simulated in MATLAB. The Caputo fractional derivatives were evaluated by using the fractional differential equation code (FDE12.m). The biologically effective dose formula was used to obtain six regression equations that were used for determining the appropriate fractional-order for each radiation protocol. Thereafter, the simulations were done in four cases. First, the fractionated doses of six patients were varied from 1.0 Gy to 6.0 Gy. Secondly, the fractionated doses were also varied from 1.0 Gy and 6.0 Gy but with 20 fractions. Thirdly, the doses of the six patients were unaltered but the number of fractions was varied from 25 to 35 fractions. Finally, a single regression equation was used to simulate the six patients’ cancer treatment. The simulations had minimal errors and it was concluded that the simulated results are better predictions of the different radiation protocols. Universiti Putra Malaysia 2021 Article PeerReviewed Faraloya, M. F. and Shafie, S. and Siam, F. M. and M., R. and Ajadi, S. O. (2021) Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative. Malaysian Journal of Mathematical Sciences, 15 (2). pp. 161-187. ISSN 1823-8343 https://einspem.upm.edu.my/journal/abstract/vol15issue2/Article%201[Feraloya%20et%20al.].pdf
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
spellingShingle QA Mathematics
Faraloya, M. F.
Shafie, S.
Siam, F. M.
M., R.
Ajadi, S. O.
Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative
description This paper presents an improved numerical simulation and optimization of radiotherapy cancer treatments. The model used was obtained by integrating the Caputo fractional derivative and the linear-quadratic with the repopulation model into the previous radiotherapy cancer treatment model. Taking advantage of the existing model factors and parameters, especially the clinical data of six cancer patients treated with radiotherapy, the resulting model equations were simulated in MATLAB. The Caputo fractional derivatives were evaluated by using the fractional differential equation code (FDE12.m). The biologically effective dose formula was used to obtain six regression equations that were used for determining the appropriate fractional-order for each radiation protocol. Thereafter, the simulations were done in four cases. First, the fractionated doses of six patients were varied from 1.0 Gy to 6.0 Gy. Secondly, the fractionated doses were also varied from 1.0 Gy and 6.0 Gy but with 20 fractions. Thirdly, the doses of the six patients were unaltered but the number of fractions was varied from 25 to 35 fractions. Finally, a single regression equation was used to simulate the six patients’ cancer treatment. The simulations had minimal errors and it was concluded that the simulated results are better predictions of the different radiation protocols.
format Article
author Faraloya, M. F.
Shafie, S.
Siam, F. M.
M., R.
Ajadi, S. O.
author_facet Faraloya, M. F.
Shafie, S.
Siam, F. M.
M., R.
Ajadi, S. O.
author_sort Faraloya, M. F.
title Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative
title_short Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative
title_full Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative
title_fullStr Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative
title_full_unstemmed Numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative
title_sort numerical simulation and optimization of radiotherapy cancer treatments using the caputo fractional derivative
publisher Universiti Putra Malaysia
publishDate 2021
url http://eprints.utm.my/id/eprint/94276/
https://einspem.upm.edu.my/journal/abstract/vol15issue2/Article%201[Feraloya%20et%20al.].pdf
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score 13.160551