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Treatment modelling: the influence of micro-environmental conditions.
Stockholm University, Faculty of Science, Medical Radiation Physics (together with KI).
2008 (English)In: Acta Oncol, ISSN 1651-226X, Vol. 47, no 5, 896-905 p.Article in journal (Other academic) Published
Abstract [en]

The interest in theoretical modelling of radiation response has grown steadily from a fast method to estimate the gain of new treatment strategies to an individualisation tool that may be used as part of the treatment planning algorithms. While the advantages of biological optimisation of plans are obvious, accurate theoretical models and realistic information about the micro-environmental conditions in tissues are needed. This paper aimed to investigate the clinical implications of taking into consideration the details of the tumour microenvironmental conditions. The focus was on the availability of oxygen and other nutrients to tumour cells and the relationship between cellular energy reserves and DNA repair ability as this is thought to influence the response of the various hypoxic cells. The choice of the theoretical models for predicting the response (the linear quadratic model or the inducible repair model) was also addressed. The modelling performed in this project has shown that the postulated radiobiological differences between acute and chronic hypoxia have some important clinical implications which may help to understand the mechanism behind the current success rates of radiotherapy. The results also suggested that it is important to distinguish between the two types of hypoxia in predictive assays and other treatment simulations.

Place, publisher, year, edition, pages
2008. Vol. 47, no 5, 896-905 p.
Keyword [en]
Anoxia, Cell Hypoxia, DNA Repair, Humans, Models; Biological, Monte Carlo Method, Neoplasms/genetics/*metabolism/*radiotherapy, Oxygen Consumption, Poisson Distribution, Predictive Value of Tests, Radiation Effects, Radiotherapy Planning; Computer-Assisted/*methods, Relative Biological Effectiveness
Identifiers
URN: urn:nbn:se:su:diva-17679ISI: 000257081200010PubMedID: 18568485OAI: oai:DiVA.org:su-17679DiVA: diva2:184200
Available from: 2009-01-19 Created: 2009-01-19 Last updated: 2011-01-10Bibliographically approved

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