Adaptive radiotherapy (ART) aims to adapt the treatment plan to account for inter-fraction anatomical variations, based on online acquired images. However, ART workflows are not –yet– routinely used in clinical practice, primarily due to the dramatic increase of the workload required and the inadequate understanding of optimal methods to maximise clinical benefit. This thesis reports on investigations of procedures for the automation of the ART process and the identification of optimal adaptation methodologies. Investigated auto-segmentation algorithms were found insufficient for an automated workflow, while a hybrid deformable image registration (DIR), incorporating both intensity based and feature-based components, revealed the most accurate and robust performance. An evaluation method was proposed for interfraction treatment monitoring through dose accumulation following DIR. The robustness of several treatment methods to observable anatomical changes were investigated, highlighting cases whereby substantial dosimetric consequences may arise. Offline ART workflows were explored, specifically investigating the effects of treatment monitoring frequency, adaptation method (simple re-plan or re-optimisation addressing cumulative dose), and adaptation timing. Contrary to simple re-planning, re-optimisation demonstrated its ability to compensate for under-/over-dose, however, non-uniform dose distributions and hot-spots may be generated. Therefore established planning techniques are applicable for re-planning while advanced approaches are required for treatment re-optimisation accounting for radiobiological consequences.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:683607 |
| Date | January 2016 |
| Creators | Roussakis, Yiannis G. |
| Publisher | University of Birmingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.bham.ac.uk//id/eprint/6611/ |
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