Francisco Casesnoves1*
1PhD Engineering, MSc Physics-Mathematics, Physician.
Bioengineering Laboratory Director. Independent Research Scientist.
International Association of Advanced Materials, Sweden. UniScience Global
Scientific Member, Wyoming, USA. Some former important affiliations: SIAM
(Society for Industrial and Applied Mathematics) and ASME (American Society of
Mechanical Engineers)
*For Correspondence
casesnoves.research.emailbox@gmail.com
Several radiotherapy optimization
methods were developed in a large number of contributions. Among them, 2D-3D
Interior and Graphical Optimization. Likewise, and recently,
Pareto-Multiobjective Optimization applied/set on Genetic Algorithms methods
were implemented in a series of publications. Modern computational intelligence
Genetic Algorithms, combined with Inverse Objective Functions, provide fast and
precise calculations for Biological Effective Dose hyperfractionated
dose-delivery planning techniques. Just remark that the design of the chapter
is mainly focused on hyperfractionated BED-TPO because that is the publication
series focus. There are very few discussions about the controversy of
hyperfractionated versus hypofractionated TPO, that is/was not the objective of
the research. In this line, this work constitutes a selection-compilation of
results, significant paragraphs/algorithms/images of the articles series for
prevalent/incident tumors whose cancer treatment often involves radiation
therapy. Selected series of 2D-3D image processing charts are included.
Selected chosen formulas, objective functions, algorithms, and radiotherapy
models are explained. The selection criteria were focused on including varied
important parts of radiotherapy TPO models foundations, models, algorithms, and
efficacious formulas applications. Beam modification static wedges dosimetry
with AAA model and Omega factor is included with essential initial formulation,
Part 5. That is set after all main Parts 1-4, and intended for easy-learning of
every mathematical-computational Part. Every section is presented with the
improved results for each and every tumor related to computational
BED-hyperfractionated Treatment Planning Optimization (TPO). Along all text, it
is emphasized the clarity and practical tools to obtain acceptable/fast TPO
results applied on modern radiation oncology. Today, Artificial Intelligence
applications for Treatment Planning Optimization have become important and
useful.
Keywords
Radiation Dose, Attenuation Exponential Factor (AEF), Simulations, Nonlinear Optimization, Matrix Algebra, Spherical-Spatial Analytical Geometry, Organ at Risk (OAR), Multi-Leaf Collimator (MLC), Wedge Filter (WF), Conformal Wedge Filter, Anisotropic Analytic Model AAA, Intensity Modulated Radiotherapy (IMRT), Intense Modulated Protontherapy (IMPT), Fluence Factor (FF), Treatment Planning Optimization (TPO), Breast Tumor (BT) Computarized Thomography (CT)
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