A spatio-temporal simulation model of the response of solid tumours to radiotherapy in vivo: parametric validation concerning oxygen enhancement ratio and cell cycle duration.
Advanced bio-simulation methods are expected to substantially improve radiotherapy treatment planning. To this end a novel spatio-temporal patient-specific simulation model of the in vivo response of malignant tumours to radiotherapy schemes has been recently developed by our group. This paper discusses recent improvements to the model: an optimized algorithm leading to conformal shrinkage of the tumour as a response to radiotherapy, the introduction of the oxygen enhancement ratio (OER), a realistic initial cell phase distribution and finally an advanced imaging-based algorithm simulating the neovascularization field. A parametric study of the influence of the cell cycle duration Tc, OER, OERbeta for the beta LQ parameter on tumour growth. shrinkage and response to irradiation under two different fractionation schemes has been made. The model has been applied to two glioblastoma multiforme (GBM) cases, one with wild type (wt) and another one with mutated (mt) p53 gene. Furthermore, the model has been applied to a hypothetical GBM tumour with alpha and beta values corresponding to those of generic radiosensitive tumours. According to the model predictions, a whole tumour with shorter Tc tends to repopulate faster, as is to be expected. Furthermore, a higher OER value for the dormant cells leads to a more radioresistant whole tumour. A small variation of the OERbeta value does not seem to play a major role in the tumour response. Accelerated fractionation proved to be superior to the standard scheme for the whole range of the OER values considered. Finally, the tumour with mt p53 was shown to be more radioresistant compared to the tumour with wt p53. Although all simulation predictions agree at least qualitatively with the clinical experience and literature, a long-term clinical adaptation and quantitative validation procedure is in progress.
Antipas
Vassilis P
VP
In Silico Oncology Group, Microwave and Fiber Optics Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece. vantipas@central.ntua.gr
Stamatakos
Georgios S
GS
Uzunoglu
Nikolaos K
NK
Dionysiou
Dimitra D
DD
Dale
Roger G
RG
D000465:Algorithms; D001932:Brain Neoplasms / Q000235:genetics / Q000532:radiotherapy; D002453:Cell Cycle; D002455:Cell Division; D003198:Computer Simulation; D019583:Dose Fractionation, Radiation; D004307:Dose-Response Relationship, Radiation; D016158:Genes, p53; D005909:Glioblastoma / Q000235:genetics / Q000532:radiotherapy; D006801:Humans; D009369:Neoplasms / Q000532:radiotherapy*; D009389:Neovascularization, Pathologic; D010100:Oxygen / Q000378:metabolism; D011836:Radiation Tolerance; D011853:Radiobiology; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted; D020266:Radiotherapy, Conformal / Q000379:methods; D013997:Time Factors
D010100:Oxygen