Sodium (23Na) plays a critical role in all organisms – it is crucial in cellular homeostasis, pH regulation and action potential propagation in muscle and neuronal fibres. Healthy cells have a low intracellular 23Na and high extracellular concentration, with the sodium-potassium pump maintaining this sodium gradient. In the human brain approximately 50% of its total energy consumption is occupied by maintenance of this gradient, demonstrating the pump’s importance in health. A failure of the sodium-potassium pump leads to cellular apoptosis and ultimately necrosis, with potentially disastrous results for neurological function. Magnetic resonance imaging (MRI) of 23Na is of great interest because of the ubiquity of sodium in cellular processes. However, it is hampered by many technical challenges. Among these are a low gyromagnetic ratio, short T2∗ relaxation times, and low concentrations all of which lead to long acquisitions in order to account for the poor inherent signal. In addition, 23Na MRI requires specialized hardware, non-standard pulse sequences and reconstruction methods in order to create images. These have all contributed to render clinical applications for 23Na MRI virtually non-existent, despite research indicating sodium’s role in various neurological disorders, including multiple sclerosis, Alzheimer’s, stroke, cancer, and traumatic brain injury. This work is motivated by a desire to use 23Na MRI in clinical settings. To that end, hardware and software methods were initially developed to process sodium images. In order to quantify the imaging system the point-spread function (PSF) and the related modulation transfer function (MTF) were calculated with the aid of a 3D-printed resolution phantom with different 23Na concentrations in gelatin. Two pulse sequences, density-adapted projection reconstruction (DA-3DPR) and Fermat looped orthogonally encoded trajectories (FLORET), with similar acquisition times were tested. Reconstructions were performed with the non-uniform fast Fourier transform. Results indicated a full-width, half-maximum (FWHM) value of 1.8 for DA-3DPR and 2.3 for FLORET. In a follow-up study, simulation experiments were added to various sodium phantom concentrations in 3% agar. The simulations indicated high potential variability in the MTF calculations depending on the methodology, while the phantom experiments found a FWHMs of 2.0 (DA-3DPR), and 2.5 (FLORET). Diffusion tensor imaging (DTI) is an MRI technique with wide adoption for the assessment of a variety of neurological disorders. Combining DTI with 23Na MRI could provide novel insight into brain pathology; however, a study with a healthy population is warranted before examinations with other populations. Fifteen subjects were scanned with DTI and sodium MRI, and the latter was used to derive voxel-wise tissue sodium concentration (TSC). Regional grey and white matter (WM) TSC was analyzed and compared to fractional anisotropy (FA) and cerebrospinal fluid (CSF) proximity. Results indicated that WM voxels proximal to CSF regions (i.e. corpus callosum) could have lower than expected FA values and higher measured TSC, with an inverse correlation between TSC and distance to CSF. This is likely the result of the broad PSF of 23Na MRI, as regions distal to CSF did not exhibit this phenomenon. This potentially represents a confounding effect when interpreting sodium concentrations, especially in regions proximal to the high 23Na content in CSF. / Thesis / Doctor of Philosophy (PhD)

Dynamic contrast enhanced MR imaging (DCE-MRI) has commonly been used to investigate disruptions in microvascular capillary permeability in pathologies such as tumours, and in brain diseases such as multiple sclerosis. This imaging technique involves intravenous injection of a contrast agent, which can modulate MR signal contrast, while frequently acquiring images (i.e. every few seconds) as the agent perfuses through the tissue of interest. Microvascular permeability, and other parameters such as blood volume and flow (perfusion) can be quantified through application of a pharmacokinetic model on the data acquired from the MRI scan. The model requires input from both the biological (e.g. pharmacokinetic rate constants) as well as physical (i.e. scanner settings) parameters. As there are a great many variables and different biophysical models (e.g. high blood flow, high permeability tissues, etc.) there needs to be considerations made for situations where the permeability may be only slightly different from normal. In the brain the blood-brain barrier (BBB) is a highly selective barrier that restricts most bulk diffusion/permeability of solutes. Changes in BBB permeability is likely only subtle in diseases such as depression or bipolar disorder, especially when compared against hypervascular-hypermemeable cancers that are void of a BBB altogether. The problem is however, to decide which model of BBB permeability is best suited for differentiating subtle changes. Thus the intention of this project was to investigate multiple pharmacokinetic models for the tracking of MRI contrast agent in regions of the brain with an intact BBB. In the brain, where there is strict regulation of molecules passing through the microvasculature into the extracellular space, and where more subtle disruptions might be of interest, different assumptions may be necessary. Four models were investigated: the Tofts model, the modified Tofts model, the two-compartment exchange model, and the uptake model. Scans of eight healthy subjects were analyzed, and permeability was quantified using each model. The accuracy of each model, quantified by the R\textsuperscript{2} value, were compared. Analysis found that the Tofts model performed significantly worse than the modified Tofts and Uptake models when fitting regions of the brain with a blood-brain barrier, with a p-value of 0.006. The analysis did not reveal any significant difference between the modified Tofts, Uptake or 2CX models, although perhaps it was obscured due to the limited number of data points. Further investigation is needed to determine any differences between the three top-performing models. / Thesis / Master of Applied Science (MASc)

Somatoparaphrenia (SP) is a disorder where patients deny ownership of their limb and display delusional ideas regarding it. In a review by Vallar and Ronchi (2009), they systematically reviewed the SP literature, and made several conclusions regarding the neural correlates of SP. The current review wanted to investigate whether the brain areas Vallar and Ronchi (2009) associated with SP were still supported today. This was done by systematically reviewing the literature containing lesion data on SP, and then comparing it (with the context of body ownership research) to the findings from Vallar and Ronchi (2009). The results showed extensive damage in the fronto-temporo-parietal regions (most notably the inferior parietal regions) and the underlying white matter. Considerable damage could also be seen at the subcortical level (especially in the insula and basal ganglia), together with extensive white matter damage, mostly in and around the internal capsule. Majority of the lesions were right hemisphere based. These results showed high correspondence with the findings from Vallar and Ronchi (2009). Same could be said when considering body ownership research, because the insula and the inferior parietal region are two areas that have been associated with our sense of body ownership. Although these results had some limitations, they overall contribute to a better understanding of the mechanisms behind both SP and body ownership. Future reviews on SP could try to distinguish between the mechanisms behind the delusional aspect of SP.

Magnetic Resonance Imaging at field strengths up to 3 T, has become a default diagnostic modality for a variety of disorders and injuries, due to multiple reasons ranging from its non-invasive nature to the possibility of obtaining high resolution images of internal organs and soft tissues. Despite tremendous advances, MR imaging of certain anatomical regions and applications present specific challenges to be overcome. One such application is MR Musculo-Skeletal Imaging. This work addresses a few difficult areas within MSK imaging from the hardware perspective, with coil solutions for dynamic imaging of knee and high field imaging of hand. Starting with a brief introduction to MR physics, different types of RF coils are introduced in chapter 1, followed by sections on design of birdcage coils, phased arrays and their characterization in chapter 2. Measurements, calculations and simulations, done during the course of this work, have been added to this chapter to give a quantitative feel of the concepts explained. Chapter 3 deals with the construction of a phased array receiver for dynamic imaging of knee of a large animal model, i.e. minipig, at 1.5 T. Starting with details on the various aspects of an application that need to be considered when an MR RF array is designed, the chapter details the complex geometry of the region of interest in a minipig and reasons that necessitate a high density array. The sizes of the individual elements that constitute the array have been arrived at by studying the ratio of unloaded to loaded Q factors and choosing a size that provides the best ratio but still maintains a uniform SNR throughout the movement of the knee. To have a minimum weight and to allow mechanical movement of the knee, the Preamplifiers were located in a separate box. A movement device was constructed to achieve adjustable periodic movement of the knee of the anesthetized animal. The constructed array has been characterized for its SNR and compared with an existing product coil to show the improvement. The movement device was also characterized for its reproducibility. High resolution static images with anatomical details marked have been presented. The 1/g maps show the accelerations possible with the array. Snapshots of obtained dynamic images trace the cruciate ligaments through a cycle of movement of the animal's knee. The hardware combination of a high density phased array and a movement device designed for a minipig's knee was used as a 'reference' and extended in chapter 4 for a human knee. In principle the challenges are similar for dynamic imaging of a human knee with regards to optimization of the elements, the associated electronics and the construction of the movement device. The size of the elements were optimized considering the field penetration / sensitivity required for the internal tissues. They were distributed around the curvature of the knee keeping in mind the acceleration required for dynamic imaging and the direction of the movement. The constructed movement device allows a periodic motion of the lower half of the leg, with the knee placed within the coil, enabling visualization of the tissues inside, while the leg is in motion. Imaging has been performed using dynamic interleaved acquisition sequence where higher effective TR and flip angles are achieved due to a combination of interleaving and segmentation of the sequence. The movement device has been characterized for its reproducibility while the SNR distribution of the constructed RF array has been compared with that of a commercially available standard 8 channel array. The results show the improvement in SNR and acceleration with the constructed geometry. High resolution static images, dynamic snapshots and the 3D segmentation of the obtained images prove the usefulness of the complete package provided in the design, for performing dynamic imaging at a clinically relevant field strength. A simple study is performed in chapter 5 to understand the effects of changes in overlap for coil configurations with different loads and at different frequencies. The noise levels of individual channels and the correlation between them are plotted against subtle changes in overlap, at 64 and 123 MHz. SNR for every overlap setup is also measured and plotted. Results show that achieving critical overlap is crucial to obtain the best possible SNR in those coil setups where the load offered by the sample is low. Chapter 6 of the thesis work deals with coil design for high field imaging of hand and wrists at 7 T, with an aim to achieve ultra high resolution imaging. At this field strength due to the increase in dielectric effects and the resulting decrease in homogeneity, whole body transmit coils are impractical and this has led engineers to design local transmit coils, for specific anatomies. While transmit or transceive arrays are usually preferred, to mitigate SAR effects, the spatial resolution obtained is limited. It is shown that a solution to this, with regards to hand imaging, can be a single volume transmit coil, along with high density receive arrays optimized for different regions of the hand. The use of a phased array for reception provides an increased SNR / penetration under high resolution. A volume transmit coil could pose issues in homogeneity at 7 T, but the specific anatomy of hand and wrist, with comparatively less water content, limits dielectric effects to have homogeneous B_1+ profile over the hand. To this effect, a bandpass birdcage and a 12 channel receive array are designed and characterized. Images of very high spatial resolution (0.16 x 0.16 x 0.16 mm3) with internal tissues marked are presented. In vivo 1/g maps show that an acceleration of up to 3 is possible and the EM simulation results presented show the uniform field along with SAR hotspots in the hand. To reduce the stress created due to the 'superman' position of imaging, provisions in the form of a holder and a hand rest have been designed and presented. Factors that contributed to the stability of the presented design are also listed, which would help future designs of receive arrays at high field strengths. In conclusion, the coils and related hardware presented in this thesis address the following two aspects of MSK imaging: Dynamic imaging of knee and High resolution imaging of hand / wrist. The presented hardware addresses specific challenges and provides solutions. It is hoped that these designs are steps in the direction of improving the existing coils to get a better knowledge and understanding of MSK diseases such as Rheumatoid Arthritis and Osteoarthritis. The hardware can aid our study of ligament reconstruction and development. The high density array and transmit coil design for hand / wrist also demonstrates the benefits of the obtained SNR at 7 T while maintaining SAR within limits. This design is a contribution towards optimizing hardware at high field strength, to make it clinically acceptable and approved by regulatory bodies. / Die Magnetresonanztomographie mit Feldstärken bis zu 3 T ist zu einer Standard- Diag-nosemethode für eine Vielzahl von Erkrankungen und Verletzungen geworden. Das hat mehrere Gründe, angefangen von ihrer nicht-invasiven Natur bis hin zu ihrer Fähigkeit,hochaufgelöste Bilder von inneren Organen und Weichteilen zu erhalten. Trotz enormer Fortschritte stellt die MR-Bildgebung bestimmter anatomischer Regionen oder bei bestimmten Anwendungen und Fragestellungen eine besondere Herausforderung dar. Eine dieser Anwendungen ist die MR-Bildgebung am Muskuloskelettalen System (MSK). Die vorliegende Arbeit befasst sich mit einigen schwierigen Fragestellungen innerhalb der MSK-Bildgebung aus aus der Perspektive der Hardware-Entwicklung: mit Spulendesigns für die dynamische Bildgebung des Knies und mit MR-Bildgebung der Hand bei hohen Magentfeldern. Nach einer kurzen Einführung in die MR-Physik werden in Kapitel 1 dann verschiedene Typen von Hochfrequenz-Spulen (HF-Spulen) vorgestellt, gefolgt in Kapitel 2 mit Abhandlungen des Designs von Birdcage-Spulen, Phased Arrays und deren Charakterisierung. Außerdem enthält das Kapitel Messungen, Berechnungen und Simulationen, die im Rahmen dieser Arbeit durchgeführt wurden, um einen quantitativen Eindruck von den erläuterten Konzepten zu vermitteln. Kapitel 3 befasst sich mit dem Aufbau eines Phased-Array-Empfängers für die dynamische Bildgebung des Knies an einem großen Tiermodell (Minipig) bei 1,5 T. Es werden detailliert verschiedene Aspekte erläutert, die bei der Konstruktion eines RF-Arrays berücksichtigt werden müssen. Des Weiteren beschreibt das Kapitel die komplexe Geometrie des Zielbereichs am Knie des Minipigs und die Gründe für ein Array mitvielen Spulenelementen. ...

Magnetic Resonance Imaging (MRI) has become one of the most important medical imaging modalities over the past few decades because of its flexibility and low risk, along with other useful attributes. For traditional MRI, the static magnetic field, B_0, must be highly homogeneous. Obtaining this homogeneity can be difficult. Traditional MRI also requires linear gradient fields that are directed along the static field direction. Under these conditions a Fourier transform relationship exists between sampled data and the image to be reconstructed. In the case of an inhomogeneous static field, gradient fields that are not linear, or gradients that are not pointed along B0, there will be no Fourier transform relationship, but a linear relationship does exists and imaging is still possible. This thesis explores the possibilities of inhomo- geneous field imaging and presents the development of hardware for inhomogeneous MRI research. Two techniques for inhomogeneous imaging are derived and presented. Matrix operators are found for these two imaging methods which are analyzed using a singular value decomposition. This analysis shows that reconstructing an image from an inhomogeneous system is possible if a field map is available.

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Conventional MRI techniques are not convenient when it comes to study cerebral microvascularization due to the length of the scans needed. A technique called Magnetic Resonance Fingerprinting (MRF) is an excellent candidate to solve this problem as it requires much shorter scan durations. It relies on the ability to simulate a large amount of MR signals coming from virtual voxels of controlled parameters. This thesis addresses this simulation aspect. Coding implements were made on a simulation tool called MRVox2D to improve its realism and flexibility. In particular, the voxel geometry generation algorithm was reworked to allow simulations in line with what can be obtained from a scanner. Having a variable vessel size within a simulated voxel is now possible and the Vessel Size Index can be computed accordingly. MRF applications were made on mice data using these implementations, showing encouraging but perfectible results. / Konventionella MR-tekniker är inte praktiska när det gäller att studera cerebral mikrovaskularisering på grund av längden på de skanningar som krävs. En teknik som kallas Magnetic Resonance Fingerprinting (MRF) är en utmärkt kandidat för att lösa detta problem eftersom den kräver mycket kortare skanningsvaraktigheter. Metoden baseras på förmågan att simulera en stor mängd MR-signaler som kommer från virtuella voxels av kontrollerade parametrar. Det här examensarbetet behandlar denna simuleringsaspekt. Kodningsredskap gjordes på ett simuleringsverktyg som heter MRVox2D för att förbättra dess realism och flexibilitet. I synnerhet omarbetades algoritmen för generering av voxelgeometri för att tillåta simuleringar i linje med vad som kan erhållas från en skanner. Att ha en variabel kärlstorlek inom en simulerad voxel är nu möjligt och Vessel Size Index kan beräknas i enlighet därmed. MRF-applikationer gjordes på mössdata med användning av dessa implementationer, vilket visade uppmuntrande men ännu inte perfekta resultat.

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The accurate assessment of hemodynamics and its parameters play an important role when diagnosing cardiovascular diseases. In this context, 4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique that facilitates hemodynamic parameter assessment as well as quantitative and qualitative analysis of three-directional flow over time. However, the assessment is limited by noise, low spatio-temporal resolution and long acquisition times. Consequently, in regions characterized by transient, rapid flow dynamics, such as the aorta and heart, capturing these rapid transient flows remains particularly challenging. Recent research has shown the feasibility of machine learning models to effectively denoise and increase the spatio-temporal resolution of 4D Flow MRI. However, temporal super-resolution networks, which can generalize on unseen domains and are independent on boundary segmentations, remain unexplored.  This study aims to investigate the feasibility of a neural network for temporal super-resolution and denoising of 4D Flow MRI data. To achieve this, we propose a residual convolutional neural network (based on the 4DFlowNet from Ferdian et al.) providing an end-to-end mapping from temporal low resolution space to high resolution space. The network is trained on patient-specific cardiac models created with computational-fluid dynamic (CFD) simulations covering a full cardiac cycle. For clinical contextualization, performance is assessed on clinical patient data. The study shows the potential of the 4DFlowNet for temporal-super resolution with an average relative error of 16.6 % on an unseen cardiac domain, outperforming deterministic methods such as linear and cubic interpolation. We find that the network effectively reduces noise and recovers high-transient flow by a factor of 2 on both in-silico and in-vivo cardiac datasets. The prediction results in a temporal resolution of 20 ms, going beyond the general clinical routine of 30-40 ms. This study exemplifies the performance of a residual CNN for temporal super-resolution of 4D flow MRI data, providing an option to extend evaluations to aortic geometries and to further develop different upsampling factors and temporal resolutions. / En noggrann bedömning av hemodynamiken och dess parametrar spelar en viktig roll vid diagnos av kardiovaskulära sjukdomar. I detta sammanhang är 4D Flow Magnetic Resonance Imaging (4D Flow MRI) en icke-invasiv mätteknik som underlättar bedömning av hemodynamiska parametrar samt kvantitativ och kvalitativ analys av flöde. Bedömningen begränsas av brus, låg spatio-temporal upplösning och långa insamlingstider. I områden som karakteriseras av snabb flödesdynamik, såsom aorta och hjärta, är det därför fortfarande särskilt svårt att fånga dessa snabba transienta flöden. Ny forskning har visat att det är möjligt att använda maskininlärningsmodeller för att effektivt reducera brus och öka den spatio-temporala upplösningen i 4D Flow MRI. Nätverk för temporal superupplösning, som kan generaliseras till osedda domäner och är oberoende av segmentering, är fortfarande outforskade.  Denna studie syftar till att undersöka genomförbarheten av ett neuralt nätverk för temporal superupplösning och brusreducering av 4D Flow MRI-data. För att uppnå detta föreslår vi ett residual faltningsneuralt nätverk (baserat på 4DFlowNet från Ferdian et al.) som tillhandahåller en end-to-end-mappning från temporalt lågupplöst utrymme till högupplöst utrymme. Nätverket tränas på patientspecifika hjärtmodeller som skapats med CFD-simuleringar som spänner över en hel hjärtcykel. För klinisk kontextualisering utvärderas nätverkets prestanda på kliniska patientdata. Studien visar potentialen av 4DFlowNet för temporal superupplösning med ett genomsnittligt relativt fel på 16,6 % på en osedd hjärtdomän, vilket överträffar deterministiska metoder som linjär och kubisk interpolation. Vi konstaterar att nätverket effektivt minskar brus och återställer högtransient flöde med en faktor på 2 på både in-silico ochin-vivo hjärtdataset. Förutsägelsen resulterar i en temporal upplösning på 20 ms, vilket är mer än den allmänna kliniska rutinen på 30-40 ms. Denna studie exemplifierar prestandan hos en residual CNN för temporal superupplösning av 4D-flödes-MRI-data, vilket ger möjlighet att utvidga utvärderingarna till aortageometrier och att vidareutveckla olika uppsamplingsfaktorer och temporala upplösningar.

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