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Radio-frequency (RF) safety plays an important role in Magnetic Resonance Imaging (MRI) with the goal of assuring patient safety and preventing excessive RF heating. Historically, RF safety in MRI has been monitored using pre-calculated specific absorption rate (SAR) limits which indicate the amount of energy that can be delivered safely to the subject. Electromagnetic (EM) simulations have usually been performed to assess the electric field and RF energy levels that are experienced by the subject. In order to validate these EM simulations, the distribution of radiofrequency (B1) field can be measured experimentally, and compared with simulation results. Also, the measurement of temperature in phantom and animal models has been used to assess RF heating directly and validate the EM simulations. Well-characterized phantom models are needed to assess RF heating experimentally. Meat phantoms can be used for RF heating tests, but these are difficult to store and challenging for their shape to be well described. Agar-gel phantoms can also be used for RF heating tests, in which one can control their dielectric properties with use of carefully controlled ingredients, such as NaCl and polyethylene powder to achieve specific conductivity and permittivity values. Once a phantom is made, the dielectric properties can be verified experimentally using an open-ended coaxial cable. A number of EM simulation methods have been proposed, which help one understand EM field phenomena in high-field MRI. But there are still many questions remaining which need to be further studied, including better characterization of thermal behaviours. In Chapter 3, three simulation methods are compared against experimental thermal elevation measures. A framework of validating EM simulations using Proton Resonance Frequency Shift (PRF) based MR thermometry in the context of parallel transmit (pTx) MRI is described in Chapter 4. Also described in this chapter is a 3D gradient-echo sequence used to monitor temperature-induced phase shifts, as well as the required image reconstruction techniques and field-stabilisation methods. The need for personalised SAR models has arisen quickly, especially in ultra-highfield pTx studies. Use of a safety margin of 1.5 (150%) to account for morphometric differences across the population has been reported previously. To reduce the need for overestimation, the development of a personalized SAR models using non-linear registration is described in Chapter 5 and assessed for robustness using three 'standard' models. Finally, the practical advantages of using the personalised model in pTx MRI are discussed in Chapter 6. With the aid of high computing capacity the personalised model approach could help MRI users reduce safety margins, so that the scanners can operate closer to the true SAR limits representing the subject in the scanner.