A vast array of medical technology relies on sophisticated control of electromagnetic and acoustic fields in human tissue, such as imaging modalities (e.g. magnetic resonance and ultrasound), treatment modalities (e.g. deep brain stimulation and localized hyperthermia), and wireless implantable devices (e.g. neurostimulators and pacemakers). The combined market for these technologies is growing rapidly, and that growth is driven primarily by market-expanding design innovations that either dramatically reduce cost or add substantial functionality. Field distribution in highly inhomogeneous human tissue plays a central role in the performance of many of these technologies. Yet it is stunning that given the huge market, the pace of technological innovation, and the human cost of flaws, such field distribution in highly inhomogeneous human tissue is still being analyzed using tools developed for calculating signal and wave propagation in metal boxes and printed circuit boards. Relying on such tools, which can be both slow and inaccurate, inhibits design exploration and rules out point-of-care patient-specific optimization.
Now there is however an alternative, as demonstrated in a recent joint project between Skoltech, MIT and Harvard/Massachusetts General Hospital on optimizing field patterns to minimize tissue heating during magnetic resonance imaging. Specifically the team developed a specialized volume-integral equation method combined with a matrix compression scheme, leading to a magnetic resonance field analysis tool that is both more accurate and orders of magnitude faster than those widely-used re-purposed general tools mentioned above. The kind of speed this method is offering will be paradigm-shifting for both magnetic resonance designers and for imaging specialists, since it will not only enable far more aggressive design exploration, but also it will enable patient-specific field optimization and in-situ safety verification.
Skoltech professor Athanasios Polimeridis and his colleagues Jorge Villena, postdoc at MIT, Yigitcan Eryaman, postdoc at University of Minnesota, Elfar Adalsteinson, professor of Harvard-MIT division of health sciences and technology, Lawrence Wald, associate professor of radiology at Harvard, Jacob White, and Luca Daniel, professors of electrical engineering and computer science at MIT, have published their results in IEEE Transactions on Biomedical Engineering. The main algorithms of this work have been implemented into MARIE (MAgnetic Resonance Integral Equation) suite: a MATLAB-based open source software package, available for download at https://github.com/thanospol/MARIE. (Fig.1)
Fig. 1 Magnetic Resonance Green Function (MRGF)-based steps: (a) body model discretization and volume integral equation set-up; (b) define the coil domain for the MRGFs; (c) compute the MRGFs – a set of points and precomputed matrices; (d-e) On-line electromagnetic solver: combine the desired surface integral equation models with the MRGFs.
Professor Polimeridis has recently received the Skoltech Translational Research and Innovation Program for transitioning this tool from university prototype to commercial product, with the eventual goal of general fields-in-tissue analysis, although the initial focus will be primarily on the MR market.
* The Skolkovo Institute of Science and Technology (Skoltech) is a private graduate research university in Skolkovo, Russia, a suburb of Moscow. Established in 2011 in collaboration with MIT, Skoltech educates global leaders in innovation, advances scientific knowledge, and fosters new technologies to address critical issues facing Russia and the world. Applying international research and educational models, the university integrates the best Russian scientific traditions with twenty-first century entrepreneurship and innovation.
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