MTL Annual Research Report 2012

Computational Electromagnetics Tools for High-Field Magnetic Resonance Imaging

Two recent advances in Magnetic Resonance Imaging (MRI) technology have resulted in a need for sophisticated computational electromagnetics (CEM) tools. The first is the availability of higher fields scans that can improve signal-to-noise ratio. The second is the availability of transmit-coil arrays, which can be used to minimize human-body heating by electric fields. Higher fields imply higher-frequency RF pulses, with wavelengths comparable to the human body dimensions, which complicates electromagnetic analysis. They also imply increased tissue heating, which limits the RF power used for imaging purposes. In the computational prototyping group, we are developing CEM techniques to address these new needs of the MRI community, working in close collaboration with the RLE MRI group and the Harvard Massachusetts General Hospital MRI group, with some specific targets.

First, we are developing fast methods for tuning and matching the transmitters to the human-body loaded MRI coils. We combined scattering-matrix formalism, a frequency-domain finite-elements method, and commercial RF optimization software to reduce this process from days to hours. Also we plan to apply integral-equation methods to reduce it to minutes. Second, we are developing integral methods to allow for efficiently optimizing the geometrical configuration of the transmit coils. This hybrid approach will combine pre-computed Green’s functions for a realistic human body model with method of moments to be able to rapidly assess different coil configurations for a typical body. To aid this assessment, we plan to leverage our work on parameterized model-order reduction, automatically generating models depending on relevant parametric quantities. We are also working on fast methods for computing the approximate solutions to the electromagnetic fields inside the human body, assuming a simplified 3-tissue model that can be obtained for each patient by a quick MRI scan. Finally, we are developing an automated procedure for designing robust decoupling networks for arbitrary MRI transmission coil arrays, based on automatic nonlinear least squares techniques to compute the input impedance matrix, in opposition to currently applied manual methods, limited to small number of channels. These decoupling networks reduce the input power required for the same local increase of body heat vs. excitation fidelity.