Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.570096
Title: Quantification of geometric uncertainties in image guided radiotherapy
Author: Sykes, Jonathan
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2010
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Abstract:
The aim of this thesis is to determine if the geometric uncertainties that are introduced into the image guided radiotherapy (IGRT) process by Cone Beam CT (CBCT) based IGRT equipment are sufficiently small that they do not pose a significant risk of geometrical error in treatment delivery. This was performed by quantifying and investigating the geometric uncertainties introduced by; (1) calibration of the image geometry, (2) correction of patient position performed by automatic treatment couch systems and (3) automatic image registration of the localisation image with a reference image. In addition, the feasibility of providing user feedback on the likelihood of accurate image registration was investigated. A method was developed using supervised machine learning based on the shape of the image registration algorithm's similarity metric surface. The geometric uncertainties introduced by image calibration and couch positioning were both shown to be less than 1 mm and therefore do not contribute significantly to the overall uncertainties in the IGRT process. Image registration performance for image guidance based on the bony anatomy of the skull was shown to be reproducible, accurate and robust with errors typically less than 1 mm. Moreover, image registration performance did not deteriorate significantly as imaging dose was reduced. For image guidance based on the soft tissues of the prostate, image registration performance was satisfactory for some CBCT images resulting in errors less than 2 mm. However, with the majority of CBCT images, image registration was highly irreproducible with high frequencies of failure. The user feedback of image registration quality was able to correctly classify 84% of image registrations into categories of good, acceptable and unacceptable. No unacceptable classifications were classed as good. CBCT based IGRT equipment does not introduce significant risks into the IGRT process however, appropriate quality assurance measures should be implemented to safeguard against equipment failure and drift since previous system calibration. Automatic image registration of the soft-tissues of the prostate cannot be relied upon for clinical use and therefore it should be used in conjunction with manual methods.
Supervisor: Magee, D. ; Brettle, D. ; Thwaites, D. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.570096  DOI: Not available
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