ArticleMagnetic resonance imaging2026
Fast electromagnetic and RF circuit co-simulation for passive resonator field calculation and optimization in MRI.
Article in Magnetic resonance imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Reducing RF-Induced Heating of DBS in 3 T MRI Using Dual-Role Receive Arrays as Wireless Resonators: A Simulation Study.IEEE access : practical innovations, open solutions · 2026Article
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Abstract
purposePassive resonators have been widely used in MRI to manipulate RF field distributions. However, optimizing these structures using full-wave electromagnetic (EM) simulations is computationally prohibitive, particularly for massive-element passive resonator arrays with many degrees of freedom.
methodsWhile EM and RF circuit co-simulation methods have previously been applied to RF coil design, this work presents a co-simulation framework specifically tailored for the analysis and optimization of passive resonators. The framework performs a single full-wave EM simulation in which the resonator's lumped components are replaced by ports, followed by circuit-level computations to evaluate arbitrary capacitor/inductor configurations. This allows integration with a genetic algorithm to rapidly optimize the resonator parameters to enhance B
resultsThe proposed method was validated across three scenarios of increasing complexity: (1) a single-loop passive resonator on a spherical phantom, (2) a two-loop array on a cylindrical phantom, and (3) a two-loop array on a human head model. In all cases, the co-simulation results showed excellent agreement with full-wave EM simulations, with relative errors below 1%. The genetic-algorithm-driven optimization, involving tens of thousands of capacitor combinations, completed in under 5 minutes-whereas equivalent full-wave EM sweeps would require an impractically long computation time.
conclusionTo the best of our knowledge, this work represents the first systematic extension of the co-simulation methodology to passive resonator design, enabling fast, accurate, and scalable optimization. The approach significantly reduces computational burden while preserving full-wave accuracy, making it a powerful tool for passive RF structure development in MRI.
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