Anatomical changes can have significant clinical impact during head and neck radiotherapy. Adaptive radiotherapy (ART) may be applied to account for such changes. Implementation of ART to alter dose delivery requires deformable image registration (DIR) to assess 3D deformations. This study evaluates the performance and accuracy of a commercial DIR system for clinical applications.
The investigations in this project were carried out using images of induced changes in two standard radiotherapy phantoms (RANDO® and CIRS®) and one in-house built phantom. CT image data before and after deformation of the phantoms were processed using Eclipse / SmartAdapt® v.10 system employing a Demons-based algorithm. A DIR protocol was designed, and algorithm performance was assessed quantitatively, using volume analysis and the Dice Similarity Index (DSI), and also evaluated qualitatively. In addition, algorithm performance was assessed for 5 head and neck cancer patients using clinical CT images. Each original planning CT image containing contours of 10 volumes of interest including treatment target volumes and organs at risk was deformed to match a second CT image acquired during the course of the treatment. The original structures were deformed, copied onto the target image and compared to reference contours drawn by 3 radiation oncologists.
Phantom investigations gave varied results with average DSI scores ranging from 0.69 to 0.93, with an overall average of 0.86 ± 0.08. These quantitative results were reflected qualitatively, with generally accurate matching between reference and DIR-generated structures. Although air gaps in the phantoms compromised algorithm performance and gave rise to physically aberrant results. Clinical results were generally better with a DSI range of 0.75-0.99 and an overall average of 0.89 ± 0.05, suggesting high DIR accuracy. Qualitatively, some minor contour deformations were noted, as well as artefacts in the axial direction that were due to the CT slice resolution (3 mm) that was used to scan the patients. In addition, contour propagation between images using DIR reduced the time required by physicians to contour the images of head and neck cancer patients by ~47%.
This study demonstrated that deformable image registration using a Modified Demons algorithm yields clinically acceptable results and time-saving benefits in contouring that improve clinical workflow. The study also showed that it is feasible to incorporate deformable image registration as part of an adaptive radiotherapy strategy for head and neck cancer, provided further studies are designed to carry out accurate and verifiable dose deformation.
| Identifer | oai:union.ndltd.org:canterbury.ac.nz/oai:ir.canterbury.ac.nz:10092/8083 |
| Date | January 2013 |
| Creators | Ramadaan, Ihab Safa |
| Publisher | University of Canterbury. Physics and Astronomy |
| Source Sets | University of Canterbury |
| Language | English |
| Detected Language | English |
| Type | Electronic thesis or dissertation, Text |
| Rights | Copyright Ihab Safa Ramadaan, http://library.canterbury.ac.nz/thesis/etheses_copyright.shtml |
| Relation | NZCU |
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