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Metal Artifact Reduction in Computed Tomographic (CT) Images for Radiotherapy Treatment Planning Open Access


Other title
Radiotherapy Treatment Planning
Metal Artifacts
Computed Tomography
Metal Artifact Reduction
Type of item
Degree grantor
University of Alberta
Author or creator
Paudel, Moti R
Supervisor and department
Rathee, Satyapal (Oncology)
Examining committee member and department
Mackenzie, Marc (Oncology)
Molloy, Janelle (Radiation Medicine, University of Kentucky)
Sloboda, Ron (Oncology)
Wilman, Alan (Biomedical Engeneering)
Fallone, Gino (Oncology, and Physics)
Department of Oncology
Medical Physics
Date accepted
Graduation date
Doctor of Philosophy
Degree level
High density/high atomic number metallic objects create shading and streaking metal artifacts in the CT image that can cause inaccurate delineation of anatomical structures or inaccurate radiation dose calculation. We developed techniques for reducing metal artifacts in both megavoltage CT (MVCT) and kilovoltage CT (kVCT) images. We remodelled the iterative maximum polychromatic algorithm for CT (IMPACT) by adding a model for pair/triplet production and incorporating the energy dependent response of the detectors and successfully applied it to two MVCT systems. In the corrected image of a phantom, the error in the measured electron density of a plexiglass background was <1%. The mean deviation of measured electron density (0.295 1.695 relative to water) for a range of materials was <3%. For the kVCT beam, a thickness ≥13 mm of steel plate resulted in photon starvation at the detector. The modifications, similar to those for MVCT, made to kVCT in the IMPACT algorithm did not improve its performance due to photon starvation. An algorithm (MVCT-NMAR) was developed that uses prior information from MVCT images to correct artifacts in kVCT. The MVCT-NMAR greatly reduced the metal artifacts in kVCT without deforming structures and did not introduce secondary artifacts except for a few faint streaks. The radiation doses calculated on those corrected images were closer to the doses in a reference image due to the more accurate CT numbers. These improvements were significant when compared to the commercial metal artifact correction method (OMAR algorithm in Philips CT scanner). The MVCT-NMAR algorithm was further improved to remove remaining fine streakings and applied to the images of five patients. The technique greatly reduced the metal artifacts and avoided secondary artifacts. Those were significant improvements over the commercial OMAR correction method and depended upon accurate registration of the MVCT and kVCT images. Large dose reduction outside the planning target volume was observed for a prostate cancer patient when these images were used without the requirement that beams avoid passing through prostheses in TomoTherapyTM treatment plans. Thus the use of MVCT NMAR corrected images in radiotherapy treatment planning may raise the quality of cancer treatments for patients having metallic implants.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
M. R. Paudel, M. Mackenzie, B. G. Fallone, and S. Rathee, “Evaluation of metal artifacts in MVCT systems using a model based correction method,” Med. Phys. 39, 6297-6308 (2012).M. R. Paudel, M. Mackenzie, B. G. Fallone, and S. Rathee, “Evaluation of NMAR in kVCT using MVCT prior images for radiotherapy treatment planning,” Med. Phys. 40, 081701 (2013).

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