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Purpose: There is increasing use of open‐bore vertical MR systems that consist of two planar RF coils. A recent study showed that the RF‐induced heating of a neuromodulation device was much lower in the open‐bore system at the brain and the chest imaging landmarks. This study focused on the hip and knee implants and compared the specific absorption rate (SAR) distribution in human models in a 1.2T open‐bore coil with that of a 1.5T conventional birdcage coil. Methods: Computational modeling results were compared against the measurement values using a saline phantom. The differences in RF exposure were examined between a 1.2T open‐bore coil and a 1.5T conventional birdcage coil using SAR in an anatomical human model. Results: Modeling setups were validated. The body placed closed to the coil elements led to high SAR values in the birdcage system compared with the open‐bore system. Conclusion: Our computational modeling showed that the 1.2T planar system demonstrated a lower intensity of SAR distribution adjacent to hip and knee implants compared with the 1.5T conventional birdcage system. [ABSTRACT FROM AUTHOR]

Computational electromagnetic modeling is a powerful technique to evaluate the effects of electrical stimulation of the human brain. The results of these simulations can vary depending on the specific segmentation of the head and brain generated from the patient images. Using an existing boundary element fast multipole method (BEM-FMM) electromagnetic solver, this work evaluates the electric field differences modeled using two neuroimaging segmentation methods. A transcranial magnetic stimulation (TMS) coil targeting both the primary motor cortex and the dorsolateral prefrontal cortex (DLPFC) was simulated. Average field differences along a 100 mm line from the coil were small (2% for motor cortex, 3% for DLPFC) and the average field differences in the regions directly surrounding the target stimulation point were 5% for the motor cortex and 2% for DLPFC. More studies evaluating different coils and other segmentation options may further improve the computational modeling for robust TMS treatment.Clinical relevance- Patient-specific computational modeling will provide more information to clinicians for improved localization and targeting of neuromodulation therapies.