RADIOTHERAPY BED MODEL MULTIOBJECTIVE PARETO-INTERIOR DUAL-OPTIMIZATION FOR PROSTATE CANCER HYPERFRACTIONATED TREATMENT PLANNING AND ISODOSELINES INVENTION

In a previous publication, constrained evolutionary algorithms for IN-VITRO-BED-LQ model (Linear Quadratic Biological Effective Dose Model) in prostate cancer Hyperfractionation radiotherapy TPO were optimized with Pareto-Multiobjective (PMO) methods. This study improves the research witha further comparative IN-VIVO-BED-LQ model optimization followed by a precision-refinement with Interior Optimization (IO) methods. Complex software is developed based on hyperfractionation constraints, but with in vivo main parameters dataset, and IO programming. Results with software design algorithmic method take in handle subroutines functions and matrix-algebra method for setting constraints and 3D IO surfaces. Results with 3D Interior Optimization by using the Genetic Algorithms (GA) previous numbersshow get very good precision with new-invention of isodoselines sharp determination. Solutions dataset is shortly compared with previous in vitro study. Findings prove comparative PMO 2D imaging charts and numerical values of PMO prostate cancer hyperfractionated TPO parameters. Applications for prostate tumors radiotherapy planning, especially with new Surfactal-Isodoselines, brain prostate metastases and stereotactic radiosurgery treatments are briefe