Optimal number and sizes of the doses in fractionated radiotherapy according to the LQ model.
Breast Neoplasms
/ pathology
Cell Proliferation
/ radiation effects
Cell Survival
/ radiation effects
Computer Simulation
Dose Fractionation, Radiation
Female
Humans
Male
Mathematical Concepts
Models, Biological
Neoplasms
/ pathology
Nonlinear Dynamics
Prostatic Neoplasms
/ pathology
Radiation Tolerance
Radiotherapy Planning, Computer-Assisted
/ statistics & numerical data
cancer radiotherapy
linear-quadratic LQ model
non-linear programming
Journal
Mathematical medicine and biology : a journal of the IMA
ISSN: 1477-8602
Titre abrégé: Math Med Biol
Pays: England
ID NLM: 101182345
Informations de publication
Date de publication:
14 03 2019
14 03 2019
Historique:
received:
08
01
2017
accepted:
10
12
2017
pubmed:
19
1
2018
medline:
7
5
2019
entrez:
19
1
2018
Statut:
ppublish
Résumé
We address a non-linear programming problem to find the optimal scheme of dose fractionation in cancer radiotherapy. Using the LQ model to represent the response to radiation of tumour and normal tissues, we formulate a constrained non-linear optimization problem in terms of the variables number and sizes of the dose fractions. Quadratic constraints are imposed to guarantee that the damages to the early and late responding normal tissues do not exceed assigned tolerable levels. Linear constraints are set to limit the size of the daily doses. The optimal solutions are found in two steps: i) analytical determination of the optimal sizes of the fractional doses for a fixed, but arbitrary number of fractions n; ii) numerical simulation of a sequence of the previous optima for n increasing, and for specific tumour classes. We prove the existence of a finite upper bound for the optimal number of fractions. So, the optimum with respect to n is found by means of a finite number of comparisons amongst the optimal values of the objective function at the first step. In the numerical simulations, the radiosensitivity and repopulation parameters of the normal tissue are fixed, while we investigate the behaviour of the optimal solution for wide variations of the tumour parameters, relating our optima to real clinical protocols. We recognize that the optimality of hypo or equi-fractionated treatment schemes depends on the value of the tumour radiosensitivity ratio compared to the normal tissue radiosensitivity. Fast growing, radioresistant tumours may require particularly short optimal treatments.
Identifiants
pubmed: 29346681
pii: 4807290
doi: 10.1093/imammb/dqx020
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1-53Informations de copyright
© The Author(s) 2018. Published by Oxford University Press on behalf of The Institute of Mathematics and its Applications. All rights reserved.