Magnetic resonance spectroscopic imaging for improved treatment planning of prostate cancer

Prostate cancer is the most common malignancy afflicting Canadian men in 2011. Physicians use digital rectal exams (DRE), blood tests for prostate specific antigen (PSA) and transrectal ultrasound (TRUS)-guided biopsies for the initial diagnosis of prostate cancer. None of these tests detail the spatial extent of prostate cancer - information critical for using new therapies that can target cancerous prostate. With an MRI technique called proton magnetic resonance spectroscopic imaging (1H-MRSI), biochemical analysis of the entire prostate can be done without the need for biopsy, providing detailed information beyond the non-specific changes in hardness felt by an experienced urologist in a DRE, the presence of PSA in blood, or the "blind-guidance" of TRUS-guided biopsy. A hindrance to acquiring high quality 1H-MRSI data comes from signal originating from fatty tissue surrounding prostate that tends to mask or distort signal from within the prostate, thus reducing the overall clinical usefulness of 1H-MRSI data. This thesis has three major areas of focus: 1) The development of an optimized 1H-MRSI technique, called conformal voxel magnetic resonance spectroscopy (CV-MRS), to deal the with removal of unwanted lipid contaminating artifacts at short and long echo times. 2) An in vivo human study to test the CV-MRS technique, including healthy volunteers and cancer patients scheduled for radical prostatectomy or radiation therapy. 3) A study to determine the efficacy of using the 1H-MRSI data for optimized radiation treatment planning using modern delivery techniques like intensity modulated radiation treatment. Data collected from the study using the optimized CV-MRS method show significantly reduced lipid contamination resulting in high quality spectra throughout the prostate. Combining the CV-MRS technique with spectral-spatial excitation further reduced lipid contamination and opened up the possibility of detecting metabolites with short T2 relaxation times. Results from the in vivo study were verified with post-histopathological data. Lastly, 1H-MRSI data was incorporated into the radiation treatment planning software and used to assess tumour control by escalating the radiation to prostate lesions that were identified by 1H-MRSI. In summary, this thesis demonstrates the clinical feasibility of using advanced spectroscopic imaging techniques for improved diagnosis and treatment of prostate cancer.