Phosphorus magnetic resonance spectroscopy and spectroscopic imaging (31P-MRS/MRSI) non-invasively provide very important information regarding energy metabolism as they can detect high energy metabolites and membrane phospholipids in vivo. They have repeatedly proven their utility in the study of healthy and disease conditions, as many disorders are related to imbalances in bioenergetic processes. However, they are not often used in a clinic setting as there are technical challenges that lead to very long acquisition times. To address this issue, the present work focused on the implementation of two fast phosphorus magnetic resonance spectroscopic imaging (31P-MRSI) pulse sequences. The first one, "fidEPSI" uses a flyback echo planar readout trajectory calculated in real time to achieve an acceleration factor up to x10. The second, "fidepsiCS" further accelerates the acquisition by combining the flyback EPSI readout with a compressed sensing (CS) sampling scheme. For this latter approach two different data reconstruction processes were compared. Both sequences were tested in phantoms as well as in skeletal muscle and brain tissues of healthy volunteers. The results showed feasibility of the flyback Echo Planar Spectroscopic Imaging (EPSI) to acquire good quality data in a fraction of the time when compared to traditional phase encoded MRSI. Furthermore, the compressed sensing approach was used in an exercise-recovery paradigm to evaluate skeletal muscle high energy phosphate dynamics, achieving a temporal resolution of 9 seconds. Additionally, the comparison of CS reconstruction algorithms suggested that a low-rank approach is more suitable for 31P-MRSI data, compared to traditional thresholding, due to the fact that it exploits the sparsity of the NMR signal as the least number of spectral peaks rather than the fewest amount of non-zero values. Overall, this thesis presents new accelerated methods for the acquisition of 31P-MRSI, and its use in the evaluation of energy metabolism. / Thesis / Doctor of Philosophy (PhD)

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 asses 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.

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 asses 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.

A few abnormal cells found in a small piece of prostate tissue are most consequential for a man’s future. The prevalence of prostate cancer (PCa) is increasing globally. The main instigating factor for this cancer is not yet known, but it appears to be the consequence of many variables such as an increasingly older population, more frequent PSA-testing, and factors involving lifestyle. Prostate cancer screening, as an equivalent for breast cancer screening, has been suggested but unfortunately there are no accurate diagnostic tools available for this type of screening. The reason for this is simply that the prostate is one of the most difficult organs to diagnose and, consequently, PCa screening would generate far too many false-positive and false-negative results.  The prostate is not easily accessible as it is deeply-seated in the male pelvic area, wrapped around the urethra and surrounded by sensitive vital organs.  Furthermore, PCa is frequently multi-focal, and the cancer cells have a tendency of assimilating among normal cells and, thus, do not always form solid lumps.  Therefore, prostate tumors are often not felt by digital rectal examination (DRE) or identified by imaging.  The PSA-test is not reliable as it is more prostate-specific than cancer-specific.  Due to increasing prostate awareness, more early-stage and locally confined PCa are being detected. This is saving lives, although there is a high risk of over treatment and unnecessary side-effects.  The increased detection of PCa requires sophisticated diagnostic methods and highly skilled clinicians who can discern between indolent and aggressive cancers.  The current “gold-standard” for PCa diagnosis is biopsy grading by pathologists using the Gleason score system, which is a difficult task.  Therefore, innovative methods to improve the precision of prostate diagnosis, by increased biopsy sensitivity and tumor localization, are of essence. In light of these difficulties, the metabolomic approach using 1D and 2D high-resolution magic angle spinning (HRMAS) NMR spectroscopy combined with histopathology on intact prostatectomy specimens was evaluated in this research project.  The non-destructive nature of HRMAS NMR enables spectroscopic analysis of intact tissue samples with consecutive histological examinations under light microscope. Metabolomics aids in the unraveling and the discovery of organ-specific endogenous metabolites that have the potential to be reliable indicators of organ function and viability, extrinsic and intrinsic perturbations, as well as valuable markers for treatment response. The results may, therefore, be applied clinically to characterize an organ by utilizing biomarkers that have the capacity to distinguish between disease and health. The aim was to characterize the human and the rat prostate in terms of its intermediary metabolism, which I show here to differ between species and anatomical regions.  Furthermore, the aim is to seek the verification of HRMAS NMR derived metabolites which are known to be a part of the prostate metabolome such as, citrate, choline, and the polyamines which were performed, but also the identification of metabolites not previously identified as part of the local prostate metabolism, such as Omega-6, which was detected in tumors.  The extended aim was to elucidate novel bio-markers with clinical potential. In this study, the common phyto-nutrient, inositol, which appears to possess protective properties, was identified as being a potentially important PCa bio-marker for the distinction between the more indolent Gleason score 6 and the more aggressive Gleason score 7 in non-malignant prostate tissues with tumors elsewhere in the organ. Further studies in this area of PCa research are therefore warranted.

L'objectif de cette thèse est de proposer de nouveaux algorithmes pour surmonter les limitations actuelles et de relever les défis ouverts dans le traitement de l'imagerie spectroscopique par résonance magnétique (ISRM). L'ISRM est une modalité non invasive capable de fournir la distribution spatiale des composés biochimiques (métabolites) utilisés comme biomarqueurs de la maladie. Les informations fournies par l'ISRM peuvent être utilisées pour le diagnostic, le traitement et le suivi de plusieurs maladies telles que le cancer ou des troubles neurologiques. Cette modalité se montre utile en routine clinique notamment lorsqu'il est possible d'en extraire des informations précises et fiables. Malgré les nombreuses publications sur le sujet, l'interprétation des données d'ISRM est toujours un problème difficile en raison de différents facteurs tels que le faible rapport signal sur bruit des signaux, le chevauchement des raies spectrales ou la présence de signaux de nuisance. Cette thèse aborde le problème de l'interprétation des données d'ISRM et la caractérisation de la rechute des patients souffrant de tumeurs cérébrales. Ces objectifs sont abordés à travers une approche méthodologique intégrant des connaissances a priori sur les données d'ISRM avec une régularisation spatio-spectrale. Concernant le cadre applicatif, cette thèse contribue à l'intégration de l'ISRM dans le workflow de traitement en radiothérapie dans le cadre du projet européen SUMMER (Software for the Use of Multi-Modality images in External Radiotherapy) financé par la Commission européenne (FP7-PEOPLE-ITN). / The aim of this thesis is to propose new algorithms to overcome the current limitations and to address the open challenges in the processing of magnetic resonance spectroscopic imaging (MRSI) data. MRSI is a non-invasive modality able to provide the spatial distribution of relevant biochemical compounds (metabolites) commonly used as biomarkers of disease. Information provided by MRSI can be used as a valuable insight for the diagnosis, treatment and follow-up of several diseases such as cancer or neurological disorders. Obtaining accurate and reliable information from in vivo MRSI signals is a crucial requirement for the clinical utility of this technique. Despite the numerous publications on the topic, the interpretation of MRSI data is still a challenging problem due to different factors such as the low signal-to-noise ratio (SNR) of the signals, the overlap of spectral lines or the presence of nuisance components. This thesis addresses the problem of interpreting MRSI data and characterizing recurrence in tumor brain patients. These objectives are addressed through a methodological approach based on novel processing methods that incorporate prior knowledge on the MRSI data using a spatio-spectral regularization. As an application, the thesis addresses the integration of MRSI into the radiotherapy treatment workflow within the context of the European project SUMMER (Software for the Use of Multi-Modality images in External Radiotherapy) founded by the European Commission (FP7-PEOPLE-ITN framework).

<p>Lipids and sodium (²³Na) are two essential components of the human body. They play a role in almost all biological systems. However, an increase in their levels is associated with metabolic diseases. The elevation of their contents can cause similar health disorders. Examples of prevalent disorders that share an increase of musculoskeletal lipids and ²³Na are hypertension and diabetes. However, the relationship between in vivo lipid and sodium levels in pathophysiology has not been studied enough and therefore is still unclear. Additionally, the available quantification methods to facilitate such a study may not be practical. They are either invasive, not sensitive enough, or require an impractical measurement time.</p> <p>Therefore, in this work, our aims were to develop practical in vivo methods to quantify the absolute sodium concentration as well as the concentration of each lipid component individually, and to study the correlation between them within the skeletal muscles.</p> <p>Since lipids and ²³Na have different nuclear magnetic resonance properties, their quantification by magnetic resonance (MR) techniques face different challenges. Thus, we optimized different MR spectroscopic imaging (MRSI) techniques for lipids and ²³Na. </p> <p>Our proposed proton MRSI was able to provide eight lipid fat fraction (FF) maps representing each musculoskeletal lipid component (fatty acid) detected by our MRSI technique, and demonstrated a superior sensitivity compared to the conventional MR imaging methods.</p> <p>For ²³Na, our developed ²³Na-MRSI was able to measure and map the absolute ²³Na concentration with values agreeing with those reported previously in biopsy studies, and with a high repeatability (CV < 6 %) within significantly shorter acquisition time compared to other available techniques.</p> <p> Finally, the ²³Na concentration and the fat fractions of each lipid component within healthy skeletal muscles were measured and correlated using our developed MRSI methods. Our findings suggest a positive regional relationship between ²³Na and lipids and negative correlation between ²³Na and BMI under healthy conditions.</p>