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A new computational tool for the analysis of Floor Borne Vibrations on the performance and image quality of MRI scanners

Funder: UK Research and InnovationProject code: 2600930
Funded under: EPSRC

A new computational tool for the analysis of Floor Borne Vibrations on the performance and image quality of MRI scanners

Description

THE CONTEXT The functioning of an MRI scanner relies on high strength and extremely uniform magnetic fields generated through superconducting magnets (i.e. main coils) and non-uniform magnetic fields generated by time-varying current signatures specified in AC gradient coils. A third key component in an MRI scanner is the cryostat, which is comprised of a series of radiation shields and keeps the main magnet coils immersed in liquid Helium within a Helium vessel. On the contrary, the gradient coils sit outside the cryostat at room temperature. Unfortunately, externally generated vibrations, also known as Floor Borne Vibrations (FBV), introduce undesirable accelerations on the magnets (primarily in the vertical direction, but also some in lateral direction). These vibrations can lead to relative movement between the radiation shields and the magnets, thus generating unwanted eddy currents in the shields which, in turn, produce secondary magnetic fields, the latter affecting the quality of the primary uniform magnetic field and, ultimately, resulting in non-desirable imaging artefacts. THE CHALLENGE To alleviate the negative impact of FBV, magnets are built with some amount of vibration isolation either underneath the cryostat, in the form of either a soft rubber matting or a spring-damper assembly, or by trial and error changes to the mechanical behaviour of the magnet and cryostat interface. However, the optimal design and the precise location of these vibration isolation devices within a realistic 3D MRI configuration is an extremely complex task which requires expert human intervention. The challenge at hand consists of predicting the performance of the MRI scanner over a wide range of input acceleration frequencies and determining the engineering changes required to reduce its sensitivity to FBV, via (a) the optimal selection of material parameters (i.e. shield conductivity, carbon fibre suspension stiffness) and (b) the shape optimisation of the MRI scanner components (i.e. flat or round ends in radiation shield components). This requires the a-priori (and very accurate) knowledge of the effect of FBV on: (a) the magnetic field distribution (i.e. to the Parts Per Billion level) and (b) the output image quality. This can only be achieved via cutting-edge high-fidelity in-silico modelling tools, robustly benchmarked against available experimental data, and embedded within the design cycle at Siemens Healthineers via the use of Reduced Order Modelling (ROM) techniques which can permit the rapid variation of material parameters and/or geometrical features. THE AIM The development of a new robust, accurate and fast data-driven 3D in-silico ROM computational framework for the modelling of FBV on MRI performance and imaging quality. THE OBJECTIVES The objectives of this challenging EPSRC CASE Award project proposal are four: 1. The accurate computation of eddy currents and magnetic fields (i.e. to the Parts Per Billion level) within a realistic 3D MRI configuration when subjected to external FBV. The use of high order Finite Elements will be here exploited, investigating the order "p" of interpolation needed to produce the level of accuracy required. 2. The benchmarking of the software tool against experimental data collected from state-of-the-art shaker tables at Erlangen and Oxford. Experimental data will help ensure robustness and reliability of the software. 3. The study of the impact of FBV on image quality through the combination of the developed software tool with in-house imaging analysis tools at Siemens Healthineers. 4.The development of a ROM technique for fast multiple-query when considering the rapid variation of material parameters (i.e. stiffness, conductivity) and/or geometrical features (i.e. shield geometry). In-house experience at Siemens Healthineers will be here exploited in order to facilitate the identification of the most sensitive parameters to FBV.

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