A four-dimensional computer simulation model of the in vivo response to radiotherapy of glioblastoma multiforme: Studies on the effect of clonogenic cell density

Stamatakos, GS; Antipas, VP; Uzunoglu, NK; Dale, RG

dc.contributor.author	Stamatakos, GS	en
dc.contributor.author	Antipas, VP	en
dc.contributor.author	Uzunoglu, NK	en
dc.contributor.author	Dale, RG	en
dc.date.accessioned	2014-03-01T01:23:24Z
dc.date.available	2014-03-01T01:23:24Z
dc.date.issued	2006	en
dc.identifier.issn	0007-1285	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16949
dc.subject	Cell Cycle	en
dc.subject	Complex Dynamics	en
dc.subject	Computer Simulation	en
dc.subject	Dynamic System	en
dc.subject	Educational Tool	en
dc.subject	glioblastoma multiforme	en
dc.subject	Radiation Therapy	en
dc.subject	Self Organization	en
dc.subject	Simulation Model	en
dc.subject	Treatment Planning	en
dc.subject	Wild Type	en
dc.subject.classification	Radiology, Nuclear Medicine & Medical Imaging	en
dc.subject.other	protein p53	en
dc.subject.other	algorithm	en
dc.subject.other	article	en
dc.subject.other	cancer cell culture	en
dc.subject.other	cancer growth	en
dc.subject.other	cell cycle	en
dc.subject.other	cell density	en
dc.subject.other	cell population	en
dc.subject.other	cell proliferation	en
dc.subject.other	clonogenesis	en
dc.subject.other	computer model	en
dc.subject.other	computer simulation	en
dc.subject.other	gene mutation	en
dc.subject.other	glioblastoma	en
dc.subject.other	human	en
dc.subject.other	image analysis	en
dc.subject.other	in vivo study	en
dc.subject.other	oxygenation	en
dc.subject.other	prediction	en
dc.subject.other	quantitative analysis	en
dc.subject.other	radiosensitivity	en
dc.subject.other	treatment planning	en
dc.subject.other	tumor vascularization	en
dc.subject.other	validation process	en
dc.subject.other	wild type	en
dc.subject.other	Algorithms	en
dc.subject.other	Brain	en
dc.subject.other	Brain Neoplasms	en
dc.subject.other	Cell Count	en
dc.subject.other	Cell Cycle	en
dc.subject.other	Cell Death	en
dc.subject.other	Cell Hypoxia	en
dc.subject.other	Cell Proliferation	en
dc.subject.other	Clone Cells	en
dc.subject.other	Computer Simulation	en
dc.subject.other	Dose-Response Relationship, Radiation	en
dc.subject.other	Glioblastoma	en
dc.subject.other	Humans	en
dc.subject.other	Treatment Outcome	en
dc.title	A four-dimensional computer simulation model of the in vivo response to radiotherapy of glioblastoma multiforme: Studies on the effect of clonogenic cell density	en
heal.type	journalArticle	en
heal.identifier.primary	10.1259/bjr/30604050	en
heal.identifier.secondary	http://dx.doi.org/10.1259/bjr/30604050	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	Tumours behave as complex, self-organizing, opportunistic dynamic systems. In an attempt to better understand and describe the highly complicated tumour behaviour, a novel four-dimensional simulation model of in vivo tumour growth and response to radiotherapy has been developed. This paper presents the latest improvements to the model as well as a parametric validation of it. Improvements include an advanced algorithm leading to conformal tumour shrinkage, a quantitative consideration of the influence of oxygenation on radiosensitivity and a more realistic, imaging based description of the neovasculature distribution. The tumours selected for the validation of the model are a wild type and a mutated p53 gene glioblastomas multiforme. According to the model predictions, a whole tumour with larger cell cycle duration tends to repopulate more slowly. A lower oxygen enhancement ratio value leads to a more radiosensitive whole tumour. Higher clonogenic cell density (CCD) produces a higher number of proliferating tumour cells and, therefore, a more difficult tumour to treat. Simulation predictions agree at least semi-quantitatively with clinical experience, and particularly with the outcome of the Radiation Therapy Oncology Group (RTOG) Study 83-02. It is stressed that the model allows a quantitative study of the interrelationship between the competing influences in a complex, dynamic tumour environment. Therefore, the model can already be useful as an educational tool with which to study, understand and demonstrate the role of various parameters in tumour growth and response to irradiation. A long term quantitative clinical adaptation and validation of the model aiming at its integration into the treatment planning procedure is in progress. © 2006 The British Institute of Radiology.	en
heal.publisher	BRITISH INST RADIOLOGY	en
heal.journalName	British Journal of Radiology	en
dc.identifier.doi	10.1259/bjr/30604050	en
dc.identifier.isi	ISI:000237511700006	en
dc.identifier.volume	79	en
dc.identifier.issue	941	en
dc.identifier.spage	389	en
dc.identifier.epage	400	en