The accuracy and precision of measurements of pulsating flow obtained with phase contrast magnetic resonance imaging (PC MRI) was studied. Measurements were carried out using known flow rates through a phantom connected to a pump that created pulsation in the flow. Repeated measurements were made in both the negative and positive encoding direction, using both breath-hold and non breath hold sequences. The obtained data was analyzed using code written in MATLAB and also using the FLOW software that is offered by the manufacturer of the MRI system. A range of different flow velocities was scanned, and results show that the overall accuracy of the measurements is relatively good, with an average error of between 1.2% to 5.7% using the clinically employed flow calculation software. There is however indication of a systematic phase offset in the data that influences the measurements. The effect of the offset on the results depends on the direction of flow and the sequence used. The results also show the importance of properly selecting the area over which the flow rate is calculated.

Heart diseases are the leading cause of death in developed countries, hence, understanding of the hemodynamics of the heart is critically important to enable methods for cardiovascular diagnosis. Assessment of intracardiac blood pressure is highly interesting as blood flow is driven by the pressure differences. Phase-contrast magnetic resonance imaging (PC-MRI) is a tool for measuring blood flow and has a wide range of cardiovascular applications. Based on previous studies, an approach to estimate the relative pressure fields in the human heart from three-dimensional time-resolved PC-MRI velocity data was implemented and evaluated. The relative pressure fields were obtained by solving the pressure Poisson equation, using a multi-grid approach. The method was evaluated on a numerical phantom and on PC-MRI data from one healthy subject and one patient with dilated cardiomyopathy. The pressure field was visualized in combination with blood flow data and morphological images. Results indicate that the used approach works well for cardiac relative pressure estimation and are in agreement with findings from previous research. The complete spatial and temporal coverage of relative pressure enables a higher understanding of physiology and pathophysiology of the human heart and is expected to give new insights for clinical investigations.

Prostate cancer is prevalent among men and one of the few cancer sites where local therapies currently target the entire organ instead of tumour. MRI holds promise in accurately depicting regions of cancer burden within the prostate gland and guiding tumour-targeted diagnostics and therapeutics. The clinical performance of a novel stereotactic MRI-guided needle navigation system for prostate cancer targeting was evaluated. Mean absolute in-plane stereotactic needle-targeting error for 10 patients was 2.2 mm and mean absolute depth error was 6.5 mm, highlighting a need to improve technical accuracy of the system. Consequently, alternative stereotactic registration techniques were investigated. Metrics of performance were in-plane stereotactic needle-targeting error, depth error, and registration time. A Z-shaped fiducial motif using automated registration performed best in phantom experiments with an in-plane error of 2.0 mm and depth error of 1.0 mm. These results will guide further software and hardware development to improve clinical performance.

Prostate cancer is prevalent among men and one of the few cancer sites where local therapies currently target the entire organ instead of tumour. MRI holds promise in accurately depicting regions of cancer burden within the prostate gland and guiding tumour-targeted diagnostics and therapeutics. The clinical performance of a novel stereotactic MRI-guided needle navigation system for prostate cancer targeting was evaluated. Mean absolute in-plane stereotactic needle-targeting error for 10 patients was 2.2 mm and mean absolute depth error was 6.5 mm, highlighting a need to improve technical accuracy of the system. Consequently, alternative stereotactic registration techniques were investigated. Metrics of performance were in-plane stereotactic needle-targeting error, depth error, and registration time. A Z-shaped fiducial motif using automated registration performed best in phantom experiments with an in-plane error of 2.0 mm and depth error of 1.0 mm. These results will guide further software and hardware development to improve clinical performance.

Molecular Imaging provides new aspects in cancer diagnosis and treatment. With the ap-plication of imaging and biological techniques, molecular imaging can monitor molecular and cellular changes of different diseases. To interpret the mechanism of disease, more and more at-tention is focused on the development of new probes for molecular imaging. Magnetic resonance imaging (MRI) is a powerful, non-invasive clinical diagnostic tool with high spatial resolution without the limitation of the depth of tissues. Applications of MRI contrast agents can amply the MRI signal during imaging. Many studies have been devoted to developing targeted MR contrast agents. Proteins and peptides have been widely used for target-ing cancer cells in cancer diagnosis and treatments. GRP, gastrin-releasing peptide, is one of a well-characterized group of mammalian bombesin-like peptides. GRP acts through its cell surface receptors, GRP receptor (GRPR). It has been reported that there is a high density of GRP receptors in the majority of prostate carci-noma. In contrast, the GRPRs are not highly expressed in normal cells of most tissues. Thus, this tumor specific expression pattern provides an advantage for cancer targeting. A novel class of MRI contrast agent was designed by adding the Gd3+ binding sites into a stable host protein, the domain 1 of rat CD2. Due to the unique features of the designed metal binding properties, the protein contrast agent (ProCA1) exhibits more than 10-fold enhanced MRI relaxivity compared to that of the more commonly used Gd-DTPA. The high relaxivity of the designed protein contrast agent largely overcomes the major barrier of low sensitivity of MRI techniques. A peptide of ten amino acids from the C-terminal of GRP was grafted onto ProCA1. GRP-grafted protein contrast agents (ProCA1.GRPs) showed the targeting capability to the GRPRs which are over-expressed on prostate cancer cells. Cell MRI Imaging demonstrated that ProCA1.GRP(52) grafted between Lys51 and Ser52 had better targeting capability than C-terminal one. Administration of ProCA1.GRP into xenograft tumor model enhances the contrast in the GRPR+ prostate tumor under MRI and optical imaging. Study demonstrated a potential application for disease marker targeted MR imaging by using our developed protein contrast agent.

The application of magnetic resonance imaging (MRI) to non-invasively assess disease biomarkers has been hampered by lack of desired contrast agents with high relaxivity, targeting capability, and optimized pharmacokinetics. We developed a novel MRI probe which targets HER2, a biomarker for various cancers and a target for anti-cancer therapies. This multimodal HER2-targeted MRI probe integrates a rationally designed protein contrast agent with a high affinity HER2 affibody and near IR dye. Our probe can differentially monitor tumors with different HER2 levels in both cells and xenograft mice. In addition to its 10-fold higher dose efficiency compared to clinically-approved agent DTPA, our developed agent also exhibits advantages in crossing the endothelial boundary, tissue distribution, and tumor tissue retention as demonstrated by even distribution of the imaging probe across the entire tumor mass. Additionally, a second series of protein contrast agents that included affibody against EFGR developed with the capability to specifically target EGFR. These contrast agents have been utilized to monitor drug treatments and quantitatively analyze biomarker expression level. Furthermore, we anticipate these agents will provide powerful tools for quantitative assessment of molecular markers, and improved resolution for diagnosis, prognosis and drug discovery.

<p>An inescapable component to survival in a dynamic environment is detecting and reacting to signals of danger. One of the most elegant processes animals possess to handle this complex task is classical conditioning, wherein stimuli associated with an aversive event acquire the capacity to elicit defensive behaviors. This process helps ensure quick reactions prior to the occurrence of an imminent threat. A problem of living in a dynamic environment, however, is that reliable signals of danger are rarely re-encountered in the exact same form from one situation to the next. Thus, to be truly adaptive it is imperative for defensive responses to extend beyond a specific instance towards other exemplars that might portend the same negative outcome. While the phenomenon of stimulus generalization was recognized in the earliest studies of conditioning from Pavlov's laboratory, a century of conditioning research has not resolved how humans and other animals actually meet this challenge. The research presented herein employs a combination of psychophysiological and functional imaging methods to examine how humans recruit neurocognitive systems to determine what stimuli do (and do not) pose a threat. Results show that human fear generalization is a complex phenomenon affected by the perceptual and conceptual nature of the stimulus. Brain regions and functional networks involved in fear generalization comprise cortical areas involved in coding the representation of conditioned stimuli and subcortical regions involved conditioned learning and the production of behavioral responses, most notably the amygdala. These results reveal the importance of stimulus-specific factors in fear learning and generalization, provide support for anatomically constrained models of fear generalization, and contribute to the development of model systems of fear generalization processes in human anxiety disorders.</p> / Dissertation

Diffusion weighted imaging (DWI) is a branch within the field of magnetic resonance imaging (MRI) that relies on the diffusion of water molecules for its contrast. Its clinical applications include the early diagnosis of ischemic stroke and mapping of the nerve tracts of the brain. The recent development of filter exchange imaging (FEXI) and the introduction of the apparent exchange rate (AXR) present a new DWI based technique that uses the exchange of water between compartments as contrast. FEXI could offer new clinical possibilities in diagnosis, differentiation and treatment follow-up of conditions involving edema or altered membrane permeability, such as tumors, cerebral edema, multiple sclerosis and stroke. Necessary steps in determining the potential of AXR as a new biomarker include running comparative studies between controls and different patient groups, looking for conditions showing large AXR-changes. However, before designing such studies, the experimental protocol of FEXI should be optimized to minimize the experimental variance. Such optimization would improve the data quality, shorten the scan time and keep the required study group sizes smaller.  Here, optimization was done using an active imaging approach and the Cramer-Rao lower bound (CRLB) of Fisher information theory. Three optimal protocols were obtained, each specialized at different tissue types, and the CRLB method was verified by bootstrapping. A test-retest study of 18 volunteers was conducted in order to investigate the reproducibility of the AXR as measured by one of the protocols, adapted for the scanner. Group sizes required were calculated based on both CRLB and the variability of the test-retest data, as well as choices in data analysis such as region of interest (ROI) size. The result of this study is new protocols offering a reduction in coefficient of variation (CV) of around 30%, as compared to previously presented protocols. Calculations of group sizes required showed that they can be used to decide whether any patient group, in a given brain region, has large alterations of AXR using as few as four individuals per group, on average, while still keeping the scan time below 15 minutes. The test-retest study showed a larger than expected variability however, and uncovered artifact like changes in AXR between measurements. Reproducibility of AXR values ranged from modest to acceptable, depending on the brain region. Group size estimations based on the collected data showed that it is still possible to detect AXR difference larger than 50% in most brain regions using fewer than ten individuals. Limitations of this study include an imprecise knowledge of model priors and a possibly suboptimal modeling of the bias caused by weak signals. Future studies on FEXI methodology could improve the method further by addressing these matters and possibly also the unknown source of variability. For minimal variability, comparative studies of AXR in patient groups could use a protocol among those presented here, while choosing large ROI sizes and calculating the AXR based on averaged signals.

Magnetic resonance imaging (MRI) is the leading imaging technique for disease diagnostics. MRI contrast agents facilitate MRI technique to obtain tissue-specific image with improved sensitivity and signal-to-noise ratio. However, the applications of current MRI contrast agents are hampered by their uncontrolled blood circulation time, low relaxivity, and low specificity. To address such need, I have developed a series of analitical methods to determine and evaluate the strong metal binding affinity and metal selectivity of developed protein-based contrast agents (ProCAs). In addition, we have successed designed contrast agents ProCA3 series based on key determinats for metal binding sites and relaxivity. We have dementrated that one of the ProCA3 variants, ProCA32, has a high Gd3+ affinity less than 10-21 M and high metal selectivity with relxivity of more than 30 mM-1s-1 per Gd and 60 mM-1s-1 per particle. Moreover, we have demonstrated that ProCA3 variants have proper blood circulation time, high relaxivity, high metal selectivity and low toxicity, which facilitate MR imaging of multiple organs, such as liver, kidney, and blood vessels, as well as tumors. ProCA32 is also able to image liver metastases a tumor size less than 0.25 mm, which is more than fourty times more sensitive than that of clinical diagnostics of liver metastases using MRI and our developed methodology. We have further created ProCA3 variants with targeting peptide moieties such as ProCA3.bomb or ProCA3.affi to against cancer biomarkers such as GRPR and HER2 with capability to imaging tumor biomarker expressions in vivo at molecular level. We have shown that ProCA3 has an excellent safety profile and pharmacokinetics for MRI in animals. With our additional effect in protein expression, modification, and scale up production of these developed protein contrast agents, ProCA3 is expected to be a promising MRI contrast for the diagnostics for disease, such as metastatic tumor and blood vessel abnormalities, and tumor biomarkers.

Background: Hip fractures are a major health problem in Canada, and two main contributors to hip fracture are weak bone strength and fall. Weak muscles also negatively affect bone strength and increase the likelihood of falling. Advanced imaging techniques, such as magnetic resonance imaging (MRI), offer in vivo measurement of bone strength and muscle area at the proximal femur. However, it is not known if MRI-based measurements of bone and muscle properties are repeatable (i.e. precise). Methods: The femoral neck and shaft of 14 healthy participants were scanned three times, using a 1.5T MRI with repositioning between scans. Boundaries of the femoral neck, shaft and four muscle groups were delineated semi-automatically. Geometrical and strength properties of bone and area of muscle groups were determined based on segmented images. The short-term precision errors (root mean square coefficient of variation; CVrms%) between the repeated measures were calculated accordingly. Results: MRI-based measures of bone geometry and strength and muscle area at the proximal femur demonstrated in vivo precision errors < 7.6%. The average CVrms% for bone measures and muscle area were less than 4% and 2.5% respectively. Higher CVrms% (e.g. average: 4.8%) was obtained for bone strength properties. Conclusion: This is the first study to evaluate the in vivo performance of MRI on application to the proximal femur and surrounding muscles. Results demonstrate that MRI is a promising non-ionizing technique that offers precise measures of bone and muscle at the proximal femur.