Toward in vivo quantification of induced RF currents on long thin conductors

Griffin, Gregory H.; Ramanan, Venkat; Barry, Jennifer; Wright, Graham A.

doi:10.1002/mrm.27195

Cited by 9 publications

(18 citation statements)

References 15 publications

(31 reference statements)

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“…In Figure an example of a TM is shown, together with a schematic depiction of the way it is determined in simulations as described previously . The method for TM determination relies on knowledge of the induced current, that can be measured with MRI, and the incident electric field, that is determined by simulations.…”

Section: Introductionmentioning

confidence: 99%

MRI‐based transfer function determination through the transfer matrix by jointly fitting the incident and scattered field

Tokaya

Raaijmakers

Luijten

et al. 2019

Magnetic Resonance in Med

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PurposeA purely experimental method for MRI‐based transfer function (TF) determination is presented. A TF characterizes the potential for radiofrequency heating of a linear implant by relating the incident tangential electric field to a scattered electric field at its tip. We utilize the previously introduced transfer matrix (TM) to determine transfer functions solely from the MR measurable quantities, that is, the ||B1+ and transceive phase distributions. This technique can extend the current practice of phantom‐based TF assessment with dedicated experimental setup toward MR‐based methods that have the potential to assess the TF in more realistic situations.Theory and MethodsAn analytical description of the B1+ magnitude and transceive phase distribution around a wire‐like implant was derived based on the TM. In this model, the background field is described using a superposition of spherical and cylindrical harmonics while the transfer matrix is parameterized using a previously introduced attenuated wave model. This analytical description can be used to estimate the transfer matrix and transfer function based on the measured B1+ distribution.ResultsThe TF was successfully determined for 2 mock‐up implants: a 20‐cm bare copper wire and a 20‐cm insulated copper wire with 10 mm of insulation stripped at both endings in respectively 4 and 3 different trajectories. The measured TFs show a strong correlation with a reference determined from simulations and between the separate experiments with correlation coefficients above 0.96 between all TFs. Compared to the simulated TF, the maximum deviation in the estimated tip field is 9.4% and 12.2% for the bare and insulated wire, respectively.ConclusionsA method has been developed to measure the TF of medical implants using MRI experiments. Jointly fitting the incident and scattered B1+ distributions with an analytical description based on the transfer matrix enables accurate determination of the TF of 2 test implants. The presented method no longer needs input from simulated data and can therefore, in principle, be used to measure TF's in test animals or corpses.

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Section: Introductionmentioning

confidence: 99%

MRI‐based transfer function determination through the transfer matrix by jointly fitting the incident and scattered field

Tokaya

Raaijmakers

Luijten

et al. 2019

Magnetic Resonance in Med

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“…Both the home‐built and vendor‐provided pTx system were successfully used to apply the orthogonal projection for pTx mitigation and imaging (Figures 3 and 10). Such setups hold the promise to validate MR based methods proposed for in vivo assessments of implant safety, eg, via

B_{1}^{+}

or image based current detection methods 17,19,23,62,63 or MR thermometry 20 . Other applications include the measurement of the transfer function 15 or validation experiments of the MR based transfer matrix 22 .…”

Section: Discussionmentioning

confidence: 99%

Parallel transmission medical implant safety testbed: Real‐time mitigation of RF induced tip heating using time‐domain E‐field sensors

Winter

Silemek

Petzold

et al. 2020

Magnetic Resonance in Med

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Purpose To implement a modular, flexible, open‐source hardware configuration for parallel transmission (pTx) experiments on medical implant safety and to demonstrate real‐time mitigation strategies for radio frequency (RF) induced implant heating based on sensor measurements. Methods The hardware comprises a home‐built 8‐channel pTx system (scalable to 32‐channels), wideband power amplifiers and a positioning system with submillimeter precision. The orthogonal projection (OP) method is used to mitigate RF induced tip heating and to maintain sufficient B1+ for imaging. Experiments are performed at 297MHz and inside a clinical 3T MRI using 8‐channel pTx RF coils, a guidewire substitute inside a phantom with attached thermistor and time‐domain E‐field probes. Results Repeatability and precision are ~3% for E‐field measurements including guidewire repositioning, ~3% for temperature slopes and an ~6% root‐mean‐square deviation between B1+ measurements and simulations. Real‐time pTx mitigation with the OP mode reduces the E‐fields everywhere within the investigated area with a maximum reduction factor of 26 compared to the circularly polarized mode. Tip heating was measured with ~100 μK resolution and ~14 Hz sampling frequency and showed substantial reduction for the OP vs CP mode. Conclusion The pTx medical implant safety testbed presents a much‐needed flexible and modular hardware configuration for the in‐vitro assessment of implant safety, covering all field strengths from 0.5‐7 T. Sensor based real‐time mitigation strategies utilizing pTx and the OP method allow to substantially reduce RF induced implant heating while maintaining sufficient image quality without the need for a priori knowledge based on simulations or in‐vitro testing.

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“…15,23 Next to an alternative way of understanding induced current patterns on medical implants knowing these eigenvectors could prove beneficial for RF safety assessment of implants by current mapping. [24][25][26] Once the eigenvectors of the TM are known, the current patterns will be accurately resolvable in a weighted sum of a limited number of eigenvectors. Hence the entire distribution can be determined from a few sample points and therefore knowing the current in a couple of slices will be sufficient.…”

Section: Discussionmentioning

confidence: 99%

Explaining RF induced current patterns on implantable medical devices during MRI using the transfer matrix

et al. 2020

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In this work a simulation study is performed to gain insights in the patterns of induced radiofrequency (RF) currents for various implant-like structures at 1.5 T. The previously introduced transfer matrix (TM) is used to determine why certain current patterns have a tendency to naturally occur. This can benefit current safety assessment techniques and may enable the identification of critical exposure conditions. Theory and Methods: The induced current on an elongated implant can be determined by multiplication of the incident electric field along the implant with its TM. The eigenmode spectrum of the TMs for various lengths and various types of implants are determined. The eigenvector with the highest eigenvalue describes the incident electric field pattern that induces the highest current which in turn will lead to highest heating. Subsequently, a statistical probability analysis is performed using a wide range of potential incident electric field distributions in a representative human subject model during a 1.5 T MR exam which are determined by means of electromagnetic FDTD simulations. These incident electric field distributions and the resulting induced current patterns are projected onto eigenvectors of the TM to determine which eigenmodes of the implant dominate the current patterns. Results: The eigenvectors of the TM of bare and insulated wires resemble sinusoidal harmonics of a string fixed at both ends similar to the natural-current distribution on thin antennas(1). The currents on implants shorter than 20 cm are generally dominated by the first harmonic (similar to half a sine wave). This is firstly because for these implant lengths (relative to the RF wavelength), the first eigenvalue is more than three times bigger than the second showing the ability of an implant to accommodate one eigenmode better than another. Secondly, the incident electric fields have a high likelihood (≳95,7%) to project predominantly on this first eigenmode. Conclusion: The eigenmode spectrum of the TM of an implant provides insight into the expected shape of induced current distributions and worst-case exposure conditions. For short implants, the first eigenvector is dominant. In addition, realistic incident electric field distributions project more heavily on this eigenvector. Both effects together cause significant currents to always resemble the dominant eigenmode of the TM for short implants at 1.

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Toward in vivo quantification of induced RF currents on long thin conductors

Abstract: Through comparison of measured heating and image-based prediction, feasibility of using a custom UTE sequence to quantify RF heating risk in vivo was demonstrated.

Cited by 9 publications

References 15 publications

MRI‐based transfer function determination through the transfer matrix by jointly fitting the incident and scattered field

MRI‐based transfer function determination through the transfer matrix by jointly fitting the incident and scattered field

Parallel transmission medical implant safety testbed: Real‐time mitigation of RF induced tip heating using time‐domain E‐field sensors

Explaining RF induced current patterns on implantable medical devices during MRI using the transfer matrix

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