ERA

Download the full-sized PDF of Intrafractional Tumour-Tracked Irradiation using a Linac-MRDownload the full-sized PDF

Analytics

Share

Permanent link (DOI): https://doi.org/10.7939/R3CZ32D3Q

Download

Export to: EndNote  |  Zotero  |  Mendeley

Communities

This file is in the following communities:

Graduate Studies and Research, Faculty of

Collections

This file is in the following collections:

Theses and Dissertations

Intrafractional Tumour-Tracked Irradiation using a Linac-MR Open Access

Descriptions

Other title
Subject/Keyword
intrafractional
tumour
tracking
linac-MR
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Yun, Jihyun
Supervisor and department
Co-supervisor: Dr. Marc Mackenzie (Oncology)
Supervisor: Dr. B. Gino Fallone (Physics/Oncology)
Examining committee member and department
Dr. Ron S. Sloboda (Physics/Oncology)
Dr. B. Gino Fallone (Physics/Oncology)
Dr. Sharon Morsink (Physics)
Dr. Don Robinson (Physics/Oncology)
Dr. Marc Mackenzie (Oncology)
Dr. Keith Wachowicz (Oncology)
Dr. Steve Jiang (Radiation Oncology), University of California, San Diego
Dr. Satyapal Rathee (Oncology)
Department
Department of Physics
Specialization
Medical Physics
Date accepted
2013-07-09T11:47:10Z
Graduation date
2013-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Intrafractional tumour tracking is of considerable interest as a means to minimize the PTV in treating mobile tumours. By utilizing the intrafractional MR imaging feature of linac-MR, this thesis seeks to develop a direct, non-surrogate based intrafractional tumour tracking system, and physically demonstrate its feasibility by delivering highly conformal dose to a moving target undergoing simulated lung tumour motions. An autocontouring algorithm was developed to determine the shape and position of a lung tumour from each intrafractional MR image. Because our linac-MR systems are equipped with low field MRI (0.2/0.5 T), the algorithm was initially evaluated using a lung motion phantom simulating low field MR images by using a single 3 T scanner. Also, an initial in-vivo study was performed to verify the feasibility of lung tumour autocontouring using real patient data. Motion prediction software was developed to compensate for the tumour motions during system delay (time interval between detection of current tumour position and beam delivery) in MRI-based tracking. Prediction accuracy was evaluated using 1D superior–inferior lung tumour motions of 29 lung cancer patients for system delays of 120 – 520 ms. In our prototype linac-MR, MLC motors are operated in the close proximity of the MRI. Due to this, we investigated (1) appropriate RF shielding around the motors to mitigate the negative effects of RF motor noise in MR images, and (2) the effect of strong external magnetic field on the functionality of MLC motors. Intrafractional tumour-tracked irradiation to a moving target was physically demonstrated using the prototype linac-MR. Two different motion patterns (sine and modified cosine) were used to simulate lung tumour motions. Comparing the film measurement results from moving target irradiation with our tracking system to static target irradiation, 50 % beam width revealed minimal differences of < 0.5 mm, while the increase in 80 % - 20 % penumbra width was limited to 0.4 and 1.7 mm in the sine and modified cosine patterns, respectively. The performance of our tracking system shown in this research illustrates potential dosimetric advantages of intrafractional MR tumour tracking in treating mobile tumours as shown for the phantom study.
Language
English
DOI
doi:10.7939/R3CZ32D3Q
Rights
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
J. Yun, E. Yip, K. Wachowicz, S. Rathee, M. Mackenzie, D. Robinson, and B. G. Fallone, "Evaluation of a lung tumor autocontouring algorithm for intrafractional tumor tracking using low-field MRI: A phantom study," Med. Phys. 39(3), 1481-1494 (2012)J. Yun, M. Mackenzie, S. Rathee, D. Robinson, and B. G. Fallone, "An artificial neural network (ANN)-based lung-tumor motion predictor for intrafractional MR tumor tracking," Med. Phys. 39(7), 4423-4433 (2012)J. Yun, J. St. Aubin, S. Rathee, and B. G. Fallone, "Brushed permanent magnet DC MLC motor operation in an external magnetic field," Med. Phys. 37(5), 2131-2134 (2010)J. Yun, K. Wachowicz, M. Mackenzie, S. Rathee, D. Robinson, and B. G. Fallone, "First demonstration of intrafractional tumor-tracked irradiation using 2D phantom MR images on a prototype linac-MR," Med. Phys. 40(5), 051718 (12pp.) (2013)M. Lamey, J. Yun, S. Rathee, and B. G. Fallone, "Radio frequency noise from an MLC: a feasibility study of the use of an MLC for linac-MR systems," Phys. Med. Biol. 55(4), 981-994 (2010)

File Details

Date Uploaded
Date Modified
2014-04-29T20:13:50.447+00:00
Audit Status
Audits have not yet been run on this file.
Characterization
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 6980432
Last modified: 2015:10:12 15:40:16-06:00
Filename: YUN_JIHYUN_Fall 2013.pdf
Original checksum: 528efbd9f3ad9ac0e4973f689d1669ab
Well formed: false
Valid: false
Status message: Invalid page tree node offset=1191179
Status message: Unexpected error in findFonts java.lang.ClassCastException: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject cannot be cast to edu.harvard.hul.ois.jhove.module.pdf.PdfDictionary offset=3664
Page count: 100
Activity of users you follow
User Activity Date