Elevated micrometer-scale iron deposits in the brain are a crucial early detection marker for numerous neurodegenerative diseases. Although iron deposits exist below conventional magnetic resonance imaging resolution, sub-voxel information on their spatial properties can be encoded into the MR signal through magnetic susceptibility differences and diffusion effects. Spin-lock pulse sequences have recently emerged as a powerful tool sensitive to diffusion-mediated dephasing, characterized by the time constant T_1ρ. By employing continuous low-frequency radiofrequency pulses, signal dynamics can be sensitized to motions in the order of sub-kilohertz, rendering it sensitive to the effect of diffusion. In this work, the potential of microstructure characterization with T_1ρ was explored through simulation and phantom experiments. A Monte Carlo simulation of a conventional spin-lock pulse showed high sensitivity to microbead radius, concentration, and susceptibility shift through R_1ρ dispersion magnitude and inflection point. Phantom experiments of a balanced and refocused spin-lock pulse demonstrated minimal changes in relaxation rate, suggesting that a considerable susceptibility gradient must be present before signal dynamics are affected. By overcoming current experimental limitations, spin-lock pulse sequences hold great promise as reliable tools for probing structures of micrometer size.

Magnetic Resonance Imaging (MRI) is increasingly applied at high magnetic field strengths of 3T and above. This trend aids in achieving superior image quality, accelerated scan times, and enhanced diagnostic capabilities. However, the increased magnetic field strengths also amplify the acoustic and electromagnetic field interactions during MRI. This presents considerable challenges for comfortable and reliable imaging.
Firstly, the acoustic noise at high magnetic field strength MRI is greatly exacerbated. The sound may reach up to 130 dB, greatly exceeding the safe prolonged noise exposure limit at 90 dB. This causes anxiety in patients, elevate claustrophobic reactions, and are even associated with increased scan refusal rates. The sound pressure levels at modern scanners generally exceed the public safety threshold. Thus, if not adequately accounted for, it bears the risk of temporary or permanent hearing damage.
Secondly, achieving a homogeneous distribution of the transmitted radiofrequency (RF) field, which is used to create the magnetization signal, becomes increasingly challenging at high magnetic fields. The degree of constructive and destructive interference of the RF field components becomes exacerbated as the RF field wavelength shortens and starts to approximate the body dimensions in tissue. This results in spatial signal variation that cannot be universally predetermined, which can hinder diagnostic assessment in clinical imaging.
In this thesis, multiple challenges of high-field MRI were tackled by developing advanced devices and MR scanning methodologies. Firstly, a solution to the acoustic noise problem was proposed based on predicting the scanner sound and superimposing its anti-noise to reduce the sound pressure. The results indicate robust noise reduction of up to 13 dB with a proof-or-principle system across various scanning methods.
To tackle the transmitted field B1+ inhomogeneity, an adaptive shimming device was proposed, based on an array of electrically-coupled pads with high permittivity. Based on electromagnetic field simulations, the device prototype was constructed. Up to 11% modulation was measured in phantoms at 15 mm depth, with an ability to tune the location of shimming hotspot.
A novel scanning methodology to quantify B1+ magnitude in the heart was developed, using Bloch-Siegert shift-based preparations. The sequence has shown highly-robust 2D and 3D mapping in healthy subjects, and achieved superior noise-resilience, when compared to more established mapping methods.
The proposed novel B1+ mapping sequence was then adapted to enable conductivity mapping in the myocardium. The method provided the first complex B1+ field-based conductivity reconstruction in healthy subjects, with robust results in agreement with previous literature.
Finally, another MRI scanning methodology was proposed for quantitative cardiac imaging robust to field inhomogeneities.T2* - a common biomarker used in MRI - was reconstructed using phase-cycled preparations. Compared to conventional sequence, higher noise resilience was achieved in healthy subjects, while enabling a wider range of sequence tailoring options.@en

Myocardial perfusion, the blood flow to the heart muscle, can be evaluated by tracing the passage of a contrast agent using cardiac magnetic resonance (CMR) imaging. This technique, well-established for diagnosing coronary artery disease, is limited by the necessity for breath-holding, subjective assessment, and low myocardial coverage. In this thesis, we aim to address these limitations of contrast-enhanced myocardial perfusion CMR. We developed a pulse sequence and post-processing pipeline to quantify myocardial perfusion using free-breathing 3D contrast-enhanced CMR. To restrict volume acquisition to the diastolic phase, characterized by minimal cardiac motion, we employed optimal slice oversampling, maximal partial Fourier acquisition, and cartesian undersampling in spatial and temporal domains. To mitigate the effects of breathing, respiratory tracking and image registration were performed. Collaborations for the reconstruction of raw data utilizing deep learning and image registration were established. Validation in healthy volunteers demonstrates that the developed pulse sequence enables isotropic 3D acquisition (3.6 x 3.6 x 3.6 mm^3) of an arterial input function (AIF) and myocardial signal during each cardiac cycle, up to heart rates of 76 bpm. Obtained AIF images exhibit sufficient resolution for extracting the left ventricular blood pool signal and registered myocardial images are of good quality. We investigated and validated a method to convert signal intensity to T1, which is required for MBF quantification. While T1 estimates from the AIF images approximate reference values up to 500 ms well, underestimation was observed from the myocardial images and for high T1 values.

Magnetic Resonance Imaging (MRI) is an important imaging modality, since it can create high-resolution cross-sectional images of the human body. In MRI scanners, the nuclear spin magnetization is excited using radio-frequency pulses. Images are created based on the time-evolution of this magnetization, which is characterized by relaxation times (T₁,T₂,T_1ρ,…). These relaxation times change from tissue to tissue, and between healthy and diseased tissue.

Rotating frame (T_1ρ) relaxation measurements are a promising technique for assessing slow molecular interactions in tissue. This has applications in articular cartilage imaging, and cardiac imaging without contrast agent injection. T_1ρ measurements require continuous application of an electromagnetic excitation field. Variations of both the main magnetic field and the excitation field strength cause this excitation to be off-resonant. This in turn leads to contrast loss in the final images.

Adiabatic pulses, whose orientation changes slowly in time, are resistant to these off-resonance effects. Their effectiveness is dependent on their parameters, such as the peak sharpness β or the frequency modulation amplitude A. Conventional optimization techniques for these parameters neglect off-resonance effects.

In this project Redfield theory was used to create a pulse optimization algorithm that can take this off-resonance behaviour into account.

Magnetic resonance imaging (MRI) is a clinical imaging technique that allows for non-invasive visualization inside the human body with excellent soft tissue contrast with a sub-millimeter resolution. Qualitative MRI is used to visually highlight normal or pathological components by exploiting the physical properties of different tissues. However, these acquisitions provide minimal consistency between scans, patients, and scanners. To address this issue, quantitative MRI (qMRI) provides absolute measures that give meaningful physical information about tissues, enabling objective comparisons. Relaxometry, a branch of qMRI that characterizes tissues through their magnetic relaxation properties, has been employed to quantitatively assess various diseases with different biomarkers in the past. However, certain radiofrequency (RF) pulses used to induce relaxation times weighting in the MRI signal are sensitive to field inhomogeneities, which makes consistent quantification of relaxation times difficult. In order to improve sensitivity and detect more diseases, better contrast mechanisms and biomarkers are crucial. One promising technique is Relaxation Along a Fictitious Field (RAFF), which may serve as a biomarker for a wide range of diseases due to its sensitivity to slow molecular motion in tissue. Currently, it has the downside of being sensitive to off-resonance and B₁⁺ artifacts, which hampers clinical application. This project aims to develop novel contrasts for quantitative MRI by investigating the performance of adapted RF pulses. Ultimately, the goal is to reduce the susceptibility to off-resonance and B₁⁺ artifacts for the RF pulses.

Cardiac perfusion magnetic resonance imagining (MRI) is often used for ischemic diagnostics. However, the currently most popular technique uses an intravenous contrast agent: gadoliniumchelate. As this injection can cause problems in patients with renal problems, which are more prevalent in cardiac patients, a non-contrast cardiac perfusion technique would be ideal. Arterial spin labelling (ASL) is such a non-contrast technique. However, ASL requires using separate labelling pulses, complicating timing and sequence design. Concurrent labelling and imaging would solve this, which is why in this project simultaneous multi-slice (SMS) ASL was investigated. SMS is an imaging method during which multiple slices are excited at once and after receiving their signals the images are separated. If SMS were to be applied to two slices that contain the same arteries, the upstream slice would be functioning as a labelling and imaging site at the same time, as the blood in the upstream slice inevitably gets saturated during imaging. This is a way around the aforementioned downsides of ASL. Since blood flow in the arteries is highly pulsatile, SMS-cine was used, a dynamic SMS method which is more robust to motion. To isolate the saturated blood from background tissue and to compensate for bias from magnetization transfer between boound pools, the subtraction between upstream blood saturation and downstream blood saturation was taken. The hypothesis of this report is that by continuously labelling and imaging at the same time with SMS-cine, a signal can be produced directly related to the dynamic cardiac perfusion of the arteries. The viability of the proposed technique is investigated and optimized using numerical models and phantom experiments. From the phantom experiments and model predictions, it follows that for SMSASL a large flip angle and large slice thickness are optimal. The relative flow enhancement seen in the phantom experiments, using tubes with flowing water, responded to the varying of these parameters as predicted by the simulations. Yet, the relative flow enhancement was much higher than predicted by the model. This is probably caused by the fact that the tubes and water have a different T1 than blood and tissue. The model predicts relative flow enhancements of more than 90 % caused by pulsatile flow, regardless of the dicretization grid in z used, which indicates that it would be fruitful to further explore the potential of SMS-ASL in vivo. It is recommended to use an SPGR sequence and both a large flip angle and large slice thickness for this. Unbalancing the flip angle and slice thickness could also be explored using an expanded version of the numerical model and later phantom and in vivo experiments. Finally, a large potential improvement could be made to the numerical model by applying a strict conservation of total magnetization when moving spins to simulate flow, which is currently not guaranteed by the interpolation embedded in flow simulation.