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Volumetric Quantitative Brain Magnetic Resonance Imaging - Application to Cancer

  • Author / Creator
    Jutras, Jean-David
  • Quantitative Magnetic Resonance Imaging (qMRI) is occupying an increasingly prominent role in the study of the brain, by virtue of its sensitivity to physiological and anatomical changes. However, because qMRI techniques tend to suffer from long scan durations and/or post-processing times, as well as a propensity for various systematic errors and image artifacts, they still remain somewhat separated from the standard clinical practice. This doctoral dissertation proposes new solutions for overcoming some of these challenges, especially within the context of radiation treatment planning and post-treatment monitoring of brain cancer. This application requires: 1) geometrical fidelity, 2) high resolution and contrast-to-noise ratios, and 3) accurate dose simulation directly on MRI voxels. To meet these requirements, time-efficient image acquisition strategies and post-processing pipelines are newly designed and optimized for generating quantitative proton-density, T1, T2, T2*, magnetization transfer and synthetic Computed Tomography maps. In chapter 3, bipolar multi-echo gradient echo sequences are optimized for structural brain imaging and multi-parameter mapping, yielding SNR gains of 1.3- to 1.6-fold while reducing geometrical distortions by 3-fold over their conventional single-echo counterparts. In chapter 4, closed-form analytical solutions are derived to enable fast T2 mapping from bSSFP sequences while minimizing errors arising from off-resonance and magnetization-transfer effects. In chapter 5, we propose a new correction technique for transmit and receive RF inhomogeneity in proton-density and T1 maps using a bias-field correction algorithm, outperforming conventional B1 mapping. Finally, chapter 6 presents an improved automatic tissue classification method using an ultra-short TE MRI sequence, generating continuous-valued synthetic CT images for the purpose of automatic dose simulation in radiation treatment planning. The synthetic CT images yield equivalent dose distributions (~1% difference in dose volume histograms) in brain cancer patients. The imaging methodologies developed throughout this thesis are also tested both on healthy volunteers and cancer patients with primary brain tumors. Although the focus of this thesis is primarily on cancer care, the qMRI techniques developed and discussed throughout are applicable to brain imaging for numerous other diseases.

  • Subjects / Keywords
  • Graduation date
    2017-06:Spring 2017
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3NC5SR0T
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Oncology
  • Specialization
    • Medical Physics
  • Supervisor / co-supervisor and their department(s)
    • De Zanche, Nicola (Oncology)
  • Examining committee members and their departments
    • Wilman, Alan H. (Biomedical Engineering)
    • De Zanche, Nicola (Oncology)
    • Rathee, Satyapal (Oncology)
    • Yahyah, Atiyah (Oncology)
    • Fallone, B. Gino (Oncology)
    • Thompson, Richard (Biomedical Engineering)
    • Frayne, Richard (Radiology and Clinical Neuroscience, University of Calgary)
    • Wachowicz, Keith (Oncology)