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Accelerating implant RF safety assessment using a low‐rank inverse update method
Author(s) -
Stijnman Peter R. S.,
Tokaya Janot P.,
Gemert Jeroen,
Luijten Peter R.,
Pluim Josien P. W.,
Brink Wyger M.,
Remis Rob F.,
Berg Cornelis A. T.,
Raaijmakers Alexander J. E.
Publication year - 2020
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.28023
Subject(s) - computation , radio frequency , implant , cochlear implant , inverse , computer science , matrix (chemical analysis) , rank (graph theory) , algorithm , biomedical engineering , materials science , mathematics , telecommunications , geometry , medicine , surgery , audiology , composite material , combinatorics
Purpose Patients who have medical metallic implants, e.g. orthopaedic implants and pacemakers, often cannot undergo an MRI exam. One of the largest risks is tissue heating due to the radio frequency (RF) fields. The RF safety assessment of implants is computationally demanding. This is due to the large dimensions of the transmit coil compared to the very detailed geometry of an implant. Methods In this work, we explore a faster computational method for the RF safety assessment of implants that exploits the small geometry. The method requires the RF field without an implant as a basis and calculates the perturbation that the implant induces. The inputs for this method are the incident fields and a library matrix that contains the RF field response of every edge an implant can occupy. Through a low‐rank inverse update, using the Sherman–Woodbury–Morrison matrix identity, the EM response of arbitrary implants can be computed within seconds. We compare the solution from full‐wave simulations with the results from the presented method, for two implant geometries. Results From the comparison, we found that the resulting electric and magnetic fields are numerically equivalent (maximum error of 1.35%). However, the computation was between 171 to 2478 times faster than the corresponding GPU accelerated full‐wave simulation. Conclusions The presented method enables for rapid and efficient evaluation of the RF fields near implants and might enable situation‐specific scanning conditions.