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Proton radiotherapy uncertainties arising from computed tomography

Proton radiotherapy is a cancer treatment which has the potential to offer greater cure rates and/or fewer serious side effects than conventional radiotherapy. Its availability in the UK is currently limited to a single low-energy fixed beamline for the treatment of ocular tumours, but a number of facilities designed to treat deep-seated tumours are in development. This thesis focusses on the quantitative use of x-ray computed tomography (CT) images in planning proton radiotherapy treatments. It arrives at several recommendations that can be used to inform clinical protocols for the acquisition of planning scans, and their subsequent use in treatment planning systems. The primary tool developed is a software CT scanner, which simulates images of an anthropomorphic virtual phantom, informed by measurements taken on a clinical scanner. The software is used to investigate the accuracy of the stoichiometric method for calibrating CT image pixel values to proton stopping power, with particular attention paid to the impact of beam hardening and photon starvation artefacts. The strength of the method adopted is in allowing comparison between CT-estimated and exactly-calculated proton stopping powers derived from the same physical data (specified in the phantom), leading to results that are difficult to obtain otherwise. A number of variations of the stoichiometric method are examined, identifying the best-performing calibration phantom and CT tube voltage (kVp). Improvements in accuracy are observed when using a second-pass beam hardening correction algorithm. Also presented is a method for identifying the proton paths where stopping power uncertainties are likely to be greatest. Estimates of the proton range uncertainties caused by CT artefacts and calibration errors are obtained for a range of realistic clinical scenarios. The current practice of including planning margins equivalent to 3.5% of the range is found to ensure coverage in all but the very worst of cases. Results herein suggest margins could be reduced to <2% if the best-performing protocol is followed; however, an analysis specific to the CT scanner and treatment site in question should be carried out before such a change is made in the clinic.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:595863
Date January 2014
CreatorsWarren, Daniel Rosevear
ContributorsPeach, Ken J.; Hill, Mark A.
PublisherUniversity of Oxford
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://ora.ox.ac.uk/objects/uuid:ab59f596-e277-490a-a7c1-1cb81b47b9a9

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