The search for the optimal choice of treatment time, dose and fractionation regimen is one of the major challenges in radiation therapy. Several aspects of the radiation response of tumours and normal tissues give different indications of how the parameters defining a fractionation schedule should be altered relative to each other which often results in contradictory conclusions. For example, the increased sensitivity to fractionation in late-reacting as opposed to early-reacting tissues indicates that a large number of fractions is beneficial, while the issue of accelerated repopulation of tumour cells starting at about three weeks into a radiotherapy treatment would suggest as short overall treatment time as possible. Another tumour-to-normal tissue differential relevant to the sensitivity as well as the fractionation and overall treatment time is the issue of tumour hypoxia and reoxygenation. The tumour oxygenation is one of the most influential factors impacting on the outcome of many types of treatment modalities. Hypoxic cells are up to three times as resistant to radiation as well-oxygenated cells, presenting a significant obstacle to overcome in radiotherapy as solid tumours often contain hypoxic areas as a result of their poorly functioning vasculature. Furthermore, the oxygenation is highly dynamic, with changes being observed both from fraction to fraction and over a time period of weeks as a result of fast and slow reoxygenation of acute and chronic hypoxia. With an increasing number of patients treated with hypofractionated stereotactic body radiotherapy (SBRT), the clinical implications of a substantially reduced number of fractions and hence also treatment time thus have to be evaluated with respect to the oxygenation status of the tumour. One of the most promising tools available for the type of study aiming at determining the optimal radiotherapy approach with respect to fractionation is radiobiological modelling. With clinically validated in vitro-derived tissue-specific radiobiological parameters and well-established survival models, in silico modelling offers a wide range of opportunities to test various hypotheses with respect to time, dose, fractionation and details of the tumour microenvironment. Any type of radiobiological modelling study intended to provide a realistic representation of a clinical tumour should therefore take into account details of both the spatial and temporal tumour oxygenation. This thesis presents the results of three-dimensional radiobiological modelling of the response of tumours with heterogeneous oxygenation to various fractionation schemes, and oxygenation levels and dynamics using different survival models. The results of this work indicate that hypoxia and its dynamics play a major role in the outcome of radiotherapy, and that neglecting the oxygenation status of tumours treated with e.g. SBRT may compromise the treatment outcome substantially. Furthermore, the possibilities offered by incorporating modelling into the clinical routine are explored and demonstrated by the development of a new calibration function for converting the uptake of the hypoxia-PET tracer 18F-HX4 to oxygen partial pressure, and applying it for calculations of the doses needed to overcome hypoxia-induced radiation resistance. By hence demonstrating how the clinical impact of hypoxia on dose prescription and the choice of fractionation schedule can be investigated, this project will hopefully advance the evolution towards routinely incorporating functional imaging of hypoxia into treatment planning. This is ultimately expected to result in increased levels of local control with more patients being cured from their cancer. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 6: Manuscript.</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-148301 |
| Date | January 2017 |
| Creators | Kjellsson Lindblom, Emely |
| Publisher | Stockholms universitet, Fysikum, Stockholm : Department of Physics, Stockholm University |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Doctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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