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.