Optimal radiation fractionation for low-grade gliomas: Insights from a mathematical model

被引:23
作者
Galochkina, Tatiana [1 ]
Bratus, Alexander [2 ]
Perez-Garcia, Victor M. [3 ]
机构
[1] Fed Med Biol Agcy Russia, Fed Res Clin Ctr, Moscow 115682, Russia
[2] Moscow MV Lomonosov State Univ, Fac Computat Math & Cybernet, Moscow 119991, Russia
[3] Univ Castilla La Mancha, ETSI lnd & Inst Matemat Aplicada Ciencia & Ingn, Dept Matemat, E-13071 Ciudad Real, Spain
关键词
Low-grade gliomas; Radiotherapy; Mathematical models of tumor growth; Mathematical model of tumor response; GLIOBLASTOMA; GROWTH; RADIOTHERAPY; SURVIVAL; THERAPY; CHEMOTHERAPY; TUMORS;
D O I
10.1016/j.mbs.2015.05.006
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We study optimal radiotherapy fractionations for low-grade glioma using mathematical models. Both spaceindependent and space-dependent models are studied. Two different optimization criteria have been developed, the first one accounting for the global effect of the tumor mass on the disease symptoms and the second one related to the delay of the malignant transformation of the tumor. The models are studied theoretically and numerically using the method of feasible directions. We have searched for optimal distributions of the daily doses d(j) in the standard protocol of 30 fractions using both models and the two different optimization criteria. The optimal results found in all cases are minor deviations from the standard protocol and provide only marginal potential gains. Thus, our results support the optimality of current radiation fractionations over the standard 6 week treatment period. This is also in agreement with the observation that minor variations of the fractionation have failed to provide measurable gains in survival or progression free survival, pointing out to a certain optimality of the current approach. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:1 / 9
页数:9
相关论文
共 44 条
[1]   Oedema-based model for diffuse low-grade gliomas: application to clinical cases under radiotherapy [J].
Badoual, M. ;
Gerin, C. ;
Deroulers, C. ;
Grammaticos, B. ;
Llitjos, J. -F. ;
Oppenheim, C. ;
Varlet, P. ;
Pallud, J. .
CELL PROLIFERATION, 2014, 47 (04) :369-380
[2]   OPTIMAL CONTROL OF MULTIPLICATIVE CONTROL-SYSTEMS ARISING FROM CANCER-THERAPY [J].
BAHRAMI, K ;
KIM, M .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1975, 20 (04) :537-542
[3]   A mathematical model of brain tumour response to radiotherapy and chemotherapy considering radiobiological aspects [J].
Barazzuol, Lara ;
Burnet, Neil G. ;
Jena, Raj ;
Jones, Bleddyn ;
Jefferies, Sarah J. ;
Kirkby, Norman F. .
JOURNAL OF THEORETICAL BIOLOGY, 2010, 262 (03) :553-565
[4]   Biocomputing: Numerical simulation of glioblastoma growth and comparison with conventional irradiation margins [J].
Bondiau, Pierre-Yves ;
Konukoglu, Ender ;
Clatz, Olivier ;
Delingette, Herve ;
Frenay, Marc ;
Paquis, Philippe .
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2011, 27 (02) :103-108
[5]   IMRT: a review and preview [J].
Bortfeld, Thomas .
PHYSICS IN MEDICINE AND BIOLOGY, 2006, 51 (13) :R363-R379
[6]  
Capasso V., 1993, LECT NOTES BIOMATH, V97, P149
[7]  
GARCIA DM, 1985, CANCER-AM CANCER SOC, V55, P919, DOI 10.1002/1097-0142(19850301)55:5<919::AID-CNCR2820550502>3.0.CO
[8]  
2-4
[9]   Improving the time-machine: estimating date of birth of grade II gliomas [J].
Gerin, C. ;
Pallud, J. ;
Grammaticos, B. ;
Mandonnet, E. ;
Deroulers, C. ;
Varlet, P. ;
Capelle, L. ;
Taillandier, L. ;
Bauchet, L. ;
Duffau, H. ;
Badoual, M. .
CELL PROLIFERATION, 2012, 45 (01) :76-90
[10]   Hallmarks of Cancer: The Next Generation [J].
Hanahan, Douglas ;
Weinberg, Robert A. .
CELL, 2011, 144 (05) :646-674