Comparing RF heating simulations and experimental resultsĀ in pTx coils: an evaluation of three simulation methods
Hongbae Jeong1, Peter Jezzard1, and Aaron Hess2

1FMRIB Centre, University of Oxford, Oxford, United Kingdom, 2Department of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom

Synopsis

In this study, we conducted thermal simulations using EM simulation software and compared these to proton resonance frequency (PRF) thermometry using an ultra-high-field MR phantom. RF heating was measured in the magnet environment using a PRF-based 3D GRE on a 8-channel pTx coil. Three types of simulation method were assessed and compared with experimental data. Amongst the three simulation methods the realistic capacitance simulation was closest to the experimental measurement. In conclusion, PRF RF heating measurements with real fiber optic temperature changes can be used to assess and validate different types of RF simulation.

Purpose

The purpose of this study was to determine which RF coil simulation technique, if any, matched experimental RF heating measurements.

Introduction

To achieve robust patient safety, electromagnetic simulation is usually conducted in advance to assess energy absorption in the object. In this study, we conducted thermal simulations using EM simulation software and compared these to proton resonance frequency (PRF) thermometry using an ultra-high-field MR phantom1. Three types of simulation method were assessed: (1) simple current sources were used in the RF coil model rather than explicit capacitors; (2) the true capacitance values for the RF coil were used for simulation; and (3) capacitance values were used that were optimized for the Duke model (IT’IS foundation, Switzerland)2,3.

Methods

(Experimental) The average dielectric properties of grey matter and white matter at 297.2 MHz were used to design a PRF-compatible MR phantom with diameter 280 mm that fitted tightly into a pTx head coil (Affinity Imaging, Juelich, Germany). Sodium chloride and polyethylene (Sigma-Aldrich, St Louis, USA) were used to control conductivity and relative permittivity (measured values εr: 55.66, σ: 0.52 S/m)4 and mixed with agarose and benzoic acid5,6 (Fig. 1). RF heating was also measured in the magnet environment using a PRF-based 3D GRE sequence (α: -0.086 ppm/°C), with modified RF pules that simultaneously deposit 30.9 W continuous power at 10 kHz off resonance on a single pTx coil, while the readout excitation used all coils (4.7 x 4.7 x 10 mm3, TR = 25 ms, TEs = 1.55 ms to 20.36 ms in steps of 2.09 ms, TA: 5min 20sec). Two fiber optic probes (Edmund, UK) were used, one for monitoring the true temperature change at the edge of the coil (close to the element under investigation) and the other (located at the center of phantom) acting as a reference for phase drift correction. Reflected power was measured using directional-couplers, so that the simulation input power could be adjusted to match the experiment conditions (26.68W and 14.65W for channel 8 and 2, respectively).

(Simulation) For Method 1, all capacitors were replaced by current sources, giving 88 current sources in total. 11 are used as ports to generate individual fields in Channel 8 and Channel 2, respectively. For Method 2, eight capacitors were equally distributed around each element with one forming the current source on top of the element and two additional decoupling capacitors placed between each element. The same capacitor values as for the real coil were chosen. For Method 3, the capacitor values were optimized with the Duke model at 297.2 MHz to generate the conditions for a tuned coil under this phantom’s loading. The thermal properties of the agar phantom were assigned from the literature value7.

Results

A single channel RF heating experiment gave a maximum temperature rise of 2.63 °C over a 5 min 20 sec heating period for Channel 8 (Fig. 3) measured by the fiber optic probe. With PRF thermometry a maximum rise in temperature of 1.09 °C was observed at the edge of the phantom. For the Method 1 simulation, the predicted RF heating profile showed an ‘ideal’ pattern without evidence of coupling from adjacent coil elements, while Methods 2 and 3 that simulated capacitors, as well as the PRF data, showed interference in neighboring elements (Fig. 3). The real-time fiber optic temperature measurement was compared with the PRF measurement and the 3 simulation methods (Fig. 4). Method 2 showed the closest estimation of the measured heating profile in both channels 8 and 2, and its accuracy was within 15%. The three simulation methods showed different amounts of predicted heating, which are shown in comparison with the experimental PRF measurement in Fig. 5.

Conclusions

We found differences between empirical and simulated results for RF heating. Amongst the three simulation methods the realistic capacitance simulation was closest to the experimental measurement. The precise distribution of capacitors used in the coil design may generate different field behaviors and coil characteristics. Care is needed to interpret the PRF results, since temperature uncertainties of PRF MR thermometry were observed8. The discrepancy between the experimental and simulated heating patterns suggests that a more accurate model of the coil is required to have confidence in using the simulated RF heating pattern as a safety validation step. Further studies are needed with improved PRF thermometry and reduced artifacts. In conclusion, PRF RF heating measurements with real fiber optic temperature changes can be used to assess and validate different types of RF simulation.

Acknowledgements

Oxford-Radcliffe scholarship (University College Oxford) and Clarendon fund

References

1.Hindman J. Proton Resonance Shift of Water in the Gas and Liquid States. J Chem Phys. 1966.

2.Christ A, Kainz W, Hahn EG, et al. The Virtual Family—development of surface-based anatomical models of two adults and two children for dosimetric simulations. Phys Med Biol. 2010;55:23-38.

3.Beqiri A, Hand JW, Hajnal J V, Malik SJ. Comparison between Simulated Decoupling Regimes for Specific Absorption Rate Prediction in Parallel Transmit MRI. Magn Reson Med. 2015.

4.Zajícek R, Vrba J, Novotný K. Evaluation of a Reflection Method on an Open-Ended Coaxial Line and its Use in Dielectric Measurements. Acta Polytech. 2006;46(5):50-54.

5.Graedel NN, Polimeni JR, Guerin B, Gagoski B, Wald LL. An Anatomically Realistic Temperature Phantom for Radiofrequency Heating Measurements. Magn Reson Med. 2015;73:442-450.

6.Duan Q, Duyn JH, Gudino N, et al. Characterization of a dielectric phantom for high-field magnetic resonance imaging applications. Med Phys J Appl Phys. 2014;41(97):10-305.

7.Oh S, Ryu Y-C, Carluccio G, Sica CT, Collins CM. Measurement of SAR-Induced Temperature Increase in a Phantom and In Vivo with Comparison to Numerical Simulation. Magn Reson Med. 2014.

8.Olsrud J, Wirestam R, Brockstedt S, et al. MRI thermometry in phantoms by use of the proton resonance frequency shift method: application to interstitial laser thermotherapy. Phys Med Biol Phys Med Biol. 1998;43(4398):2597-2613.

Figures

Figure 1. Agar gel phantom used for PRF thermometry

Figure 2. RF heating profile (Power scaling factor: Ch8=26.8W, Ch2= 14.5W)

Figure 3. Measured and experiment temperature elevation at edge point

Figure 4. Temperature changes (°C) at monitoring points in the edge

Figure 5. Temperature elevation in profile view



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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