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Optimization of antitumor radiotherapy fractionation via mathematical modeling with account of 4 R's of radiobiology.
Kuznetsov, Maxim; Kolobov, Andrey.
Afiliação
  • Kuznetsov M; P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 53 Leninskiy Prospekt, Moscow 119991, Russia; Peoples' Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Street, Moscow 117198, Russia. Electronic address: kuznetsovmb@mail.ru.
  • Kolobov A; P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 53 Leninskiy Prospekt, Moscow 119991, Russia.
J Theor Biol ; 558: 111371, 2023 02 07.
Article em En | MEDLINE | ID: mdl-36462667
ABSTRACT
A spatially-distributed continuous mathematical model of solid tumor growth and treatment by fractionated radiotherapy is presented. The model explicitly accounts for the factors, widely referred to as 4 R's of radiobiology, which influence the efficacy of radiotherapy fractionation protocols tumor cell repopulation, their redistribution in cell cycle, reoxygenation and repair of sublethal damage of both tumor and normal tissues. With the use of special algorithm the fractionation protocols that provide increased tumor control probability, compared to standard clinical protocol, are found for various physiologically-based values of model parameters under the constraints of fixed overall normal tissue damage and maximum admissible fractional dose. In particular, it is shown that significant gain in treatment efficacy can be achieved for tumors of low malignancy by the use of protracted hyperfractionated protocols. The optimized non-uniform protocols are characterized by gradual escalation of fractional doses in their last parts, which start after the levels of oxygen and nutrients significantly elevate throughout the tumor and accelerated tumor proliferation manifests itself, which is a well-known experimental phenomenon.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radiobiologia / Neoplasias Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: J Theor Biol Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radiobiologia / Neoplasias Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: J Theor Biol Ano de publicação: 2023 Tipo de documento: Article