Title: Towards Patient-Specific and Reliable SAR Management for Parallel-Transmit Technology on Ultra-High Field MRI
Funder: Engineering and Physical Sciences Research Council

Abstract: Neural circuitry inside a human brain is probably the most complicated large scale circuit that any electronic engineer could think of: it contains around100 billion neurons, instantly linked through trillions of pathways to generate thought, memory, action or emotion. When faults rise within the neural circuitry, different brain disorders may arise. There are 10 million people in the UK living with a neurological condition, and the associated economic burden is estimated to be 116 billion pounds per year. With the recent significant investments in Brain Mapping projects in both Europe and the US, Neuroscientists need to develop new imaging technologies with superior signal-to-noise ratio (SNR), such as Ultrahigh field Magnetic Resonance Imaging, to show how complex neural circuits interact and eventually yield methods of preventing and treating neurological disorders. However various image artifacts presented at 7T MR images raise uncertainty of MRI measurements, because of increased inhomogeneity of the magnetic excitation field. The latest technology to solve this problem is to utilise a novel RF technology: Parallel Transmission (pTX), through multiple RF excitation coils with unique spatial profiles to achieve the homogeneous magnetization. To adopt this engineering solution for medical imaging application, there is a preeminent need to address one technical challenge: to develop a reliable RF safety management, measured by Specific Absorption Rate (SAR), to ensure this technique will meet the RF exposure legal constraint. Since the advent of pTX for 7T MRI, the difficulty in accurately characterising the local SAR, especially for the pTX pulse optimised for a specific subject, greatly hampers its clinical application. The current practice for SAR estimation in use worldwide by adopting electromagnetic (EM) simulation requires an expensive safety margin (at least 40% higher) to accommodate the uncertainties. The other SAR calculation approach recently pioneered by our project partner (Philips Healthcare), B1-map based ultrafast SAR calculation, still suffers from poor accuracy due to several unrealistic default assumptions, and has not been validated against quantitative experimental measurements at Ultrahigh field MRI yet. Within this project, we will develop a trustworthy and ultrafast SAR calculation approach to address this Engineering challenge by combining the electromagnetic numerical solution with B1 mapping for the first time, to enable a paradigm shift from using numerical simulation with generic models to proactively managing SAR for specific subjects under examination. In particular we will tackle the poor accuracy problem associated with the latest MRI B1-map based ultrafast SAR calculation by using complementary EM knowledge to supplement the missing information. It will be the first attempt to adopt such a hybrid approach, which could draw the essence of each technique, to tackle the MRI SAR issue in this global research forefront area. The project is seen as timely because it will address two challenges raised in the 2012 EPSRC/MRC Medical Imaging Technology Working Group Report: "Safer, lower cost, and higher throughput systems and Improving the value of current medical imaging technologies". The research project will also benefit from close collaboration with leading national and international partners in MRI RF technology from both academia (Nottingham University and Queensland University) and industry (Both Philips Healthcare and Pulseteq Ltd) to ensure its immediate impact on Healthcare Industry in the UK from the outset. To accelerate the impact of our research, the SAR management software developed here will provide free licences to all academic and clinical MR researchers. The applicant will also engage actively with the Health Protection Agency's Advisory Group, British Institute of Radiology and Safety Committee of the ISMRM for their reviews on our research output.


Research activity codes: 1.3 CHEMICAL AND PHYSICAL SCIENCES;4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: NEUROLOGICAL