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Radiotherapy Bed Model 2D Pareto- Multiobjective Evolutionary Optimization for Prostate Cancer Hyperfractionated Treatment

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  • Francisco Casesnoves

    (PhD Engineering, MSc Physics-Mathematics, Physician. Independent Research Scientist. International Association of Advanced Materials, Sweden. UniScience Global Scientific Member, Wyoming, USA)

Abstract

Constrained evolutionary algorithms for BED-LQ model (Biological Effective Dose) in Prostate cancer Hyperfractionation radiotherapy TPO are optimized with Pareto-Multiobjective (PMO) methods. Genetic Algorithm (GA) software is developed based on hyperfractionation constraints with in vitro main parameters dataset. Programming method results take in handle subroutines functions and matrix-algebra method for setting constraints. Results show PMO 2D imaging charts and numerical values of PMO Prostate cancer hyperfractionated TPO parameters. Applications for prostate tumors radiotherapy and stereotactic radiosurgery treatments are briefed.

Suggested Citation

  • Francisco Casesnoves, 2023. "Radiotherapy Bed Model 2D Pareto- Multiobjective Evolutionary Optimization for Prostate Cancer Hyperfractionated Treatment," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 51(2), pages 42430-42439, June.
    • Handle: RePEc:abf:journl:v:51:y:2023:i:2:p:42430-42439
    DOI: 10.26717/BJSTR.2023.51.008064
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