Biochemical Imaging of Gliomas Using MR Spectroscopic Imaging for Radiotherapy Treatment Planning

• Author / Creator

  Heikal, Amr A

• This thesis discusses the main obstacles facing wide clinical implementation of magnetic resonance spectroscopic imaging (MRSI) as a tumor delineation tool for radiotherapy treatment planning, particularly for gliomas. These main obstacles are identified as 1. observer bias and poor interpretational reproducibility of the results of MRSI scans, and 2. the long scan times required to conduct MRSI scans. An examination of an existing user-independent MRSI tumor delineation technique known as the choline-to-NAA index (CNI) is conducted to assess its utility in providing a tool for reproducible interpretation of MRSI results. While working with spatial resolutions typically twice those on which the CNI model was originally designed, a region of statistical uncertainty was discovered between the tumor and normal tissue populations and as such a modification to the CNI model was introduced to clearly identify that region. To address the issue of long scan times, a series of studies were conducted to adapt a scan acceleration technique, compressed sensing (CS), to work with MRSI and to quantify the effects of such a novel technique on the modulation transfer function (MTF), an important quantitative imaging metric. The studies included the development of the first phantom based method of measuring the MTF for MRSI data, a study of the correlation between the k-space sampling patterns used for compressed sensing and the resulting MTFs, and the introduction of a technique circumventing some of side-effects of compressed sensing by exploiting the conjugate symmetry property of k-space. The work in this thesis provides two essential steps towards wide clinical implementation of MRSI-based tumor delineation. The proposed modifications to the CNI method coupled with the application of CS to MRSI address the two main obstacles outlined. However, there continues to be room for improvement and questions that need to be answered by future research.

• Subjects / Keywords

  • Compressed Sensing
  • MR scectroscopic imaging
  • MTF

• Graduation date

  Spring 2014

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3NS0M619

• 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.