Simultaneous magnetic resonance phase and magnitude temperature maps in muscle

Cline, H. E.; Hynynen, Kullervo; Schneider, Erika; Hardy, Christopher J.; Maier, Stefan E.; Watkins, Ronald D.; Jólesz, Ferenc A.

doi:10.1002/mrm.1910350307

Cited by 101 publications

(60 citation statements)

References 12 publications

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“…In order to increase temperature accuracy, the combination of different methods into a single acquisition has been investigated, eg, T 1 and M 0 (78 -80) or T 1 and PRF (27). However, due to the tissue-type-dependence of the T 1 method, the combination of T 1 and PRF can also become tissue-type-dependent.…”

Section: Combined Methodsmentioning

confidence: 99%

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MR thermometry

Rieke

Pauly

2008

Magnetic Resonance Imaging

987

952

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Minimally invasive thermal therapy as local treatment of benign and malignant diseases has received increasing interest in recent years. Safety and efficacy of the treatment require accurate temperature measurement throughout the thermal procedure. Noninvasive temperature monitoring is feasible with magnetic resonance (MR) imaging based on temperature-sensitive MR parameters such as the proton resonance frequency (PRF), the diffusion coefficient (D), T 1 and T 2 relaxation times, magnetization transfer, the proton density, as well as temperature-sensitive contrast agents. In this article the principles of temperature measurements with these methods are reviewed and their usefulness for monitoring in vivo procedures is discussed. Whereas most measurements give a temperature change relative to a baseline condition, temperature-sensitive contrast agents and spectroscopic imaging can provide absolute temperature measurements. The excellent linearity and temperature dependence of the PRF and its near independence of tissue type have made PRF-based phase mapping methods the preferred choice for many in vivo applications. Accelerated MRI imaging techniques for real-time monitoring with the PRF method are discussed. Special attention is paid to acquisition and reconstruction methods for reducing temperature measurement artifacts introduced by tissue motion, which is often unavoidable during in vivo applications.

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Section: Combined Methodsmentioning

confidence: 99%

“…The small nonlinear temperature dependence on the equilibrium magnetization is often neglected (26) or, alternatively, Eq. [7] is modified to (27):…”

Section: T 1 Relaxation Time Of Water Protonsmentioning

confidence: 99%

MR thermometry

Rieke

Pauly

2008

Magnetic Resonance Imaging

987

952

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“…To demonstrate the basic capability of the technique, temperature maps are made of the simplest system to model: the dielectric sphere. Temperature imaging with proton resonance shift imaging has been used to monitor thermal surgery (17)(18)(19)(20). The method involves acquiring phase images before and after RF heating, and constructing a thermal map that provides the power deposition.…”

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confidence: 99%

Radiofrequency power deposition utilizing thermal imaging

Cline

Mallozzi

et al. 2004

Magnetic Resonance in Med

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Wavelength effects influence radiofrequency (RF) power deposition distributions and limit magnetic resonance (MR) medical applications at very high magnetic fields. The power depositions in spherical saline gel phantoms were deduced from proton resonance shift thermal maps at both 1.5 T and 3.0 T over a range of conductivities. Phase differences before and after RF heating were measured for both a quadrature head coil and a circular surface coil. A long echo time (TE) pulse sequence with a 3D phase unwrap algorithm provided increased thermal sensitivity. The measured thermal maps agreed with a model of eddy-current heating by circularly polarized oscillating RF fields in a conducting dielectric sphere. At 3.0 T, thermal maps were acquired with a <0.32°C temperature rise at 4 W. Proton resonance shift thermal maps provided a measure of hot spots in very-high-field MR imaging (MRI), in which both the phase sensitivity and signalto-noise ratio (SNR) were increased. The method provides a means of studying the heat distribution generated by RF coils excited by clinical pulse sequences. MRI thermal mapping provides a means of estimating the radiofrequency (RF) power deposition (1). As the resonance frequency increases, effects from the finite electromagnetic wavelength increasingly influence the power distribution. Measuring the nonuniform power deposition in very-high-field magnetic resonance (MR) systems is an important step in establishing a safe operating environment for fast imaging sequences (2,3). RF fields in the head during a high-field MR exam exhibit wave phenomena (4 -11) similar to those of RF fields interacting with a dielectric sphere-a problem that has been discussed in a number of textbooks (4 -7). The distribution of heat absorbed in a conducting dielectric sphere, and the RF field pattern both depend on the diameter relative to the radiation wavelength. An oscillating magnetic field induces eddy currents that act to reduce the field inside the sphere, as well as displacement currents from the dielectric properties that enhance the field in the center (7). Early low-field MRI systems had a long wavelength compared to the head size. It was argued that eddy-current screening would limit the application of high-field systems (8); however, the first 1.5-T imaging system built in our laboratory had a uniform RF field profile that balanced conductivity screening and dielectric field focusing. At higher field strengths, finite wavelength effects become the dominant phenomenon, and the RF field is observed to peak in the center of the head (9 -11). Tissue conductivity leads to Joule heating, which imposes an imaging limitation described by the specific absorption rate (SAR) that increases with RF frequency. The RF power absorbed in tissue raises the temperature depending on both the tissue conductivity and the mean square electric field induced by the circularly polarized magnetic field. For safety reasons, it is important to establish methods to accurately predict heating during an MR examination. Numerical...

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“…Theoretically, the lowest temperature standard deviation will be achieved when TE is close to T 2 *. 52,57,58 This would favor centric sampling schemes that have the longest TE (20.4 and 22.1 ms for ESC and NESC2-VD2, respectively, vs 15.0 ms for the sequentially sampled schemes). This is the case for the ESC scheme that has the lowest standard deviation (0.03…”

Section: Discussionmentioning

confidence: 99%

Sampling strategies for subsampled segmented EPI PRF thermometry in MR guided high intensity focused ultrasound

et al. 2014

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Purpose: To investigate k-space subsampling strategies to achieve fast, large field-of-view (FOV) temperature monitoring using segmented echo planar imaging (EPI) proton resonance frequency shift thermometry for MR guided high intensity focused ultrasound (MRgHIFU) applications. Methods: Five different k-space sampling approaches were investigated, varying sample spacing (equally vs nonequally spaced within the echo train), sampling density (variable sampling density in zero, one, and two dimensions), and utilizing sequential or centric sampling. Three of the schemes utilized sequential sampling with the sampling density varied in zero, one, and two dimensions, to investigate sampling the k-space center more frequently. Two of the schemes utilized centric sampling to acquire the k-space center with a longer echo time for improved phase measurements, and vary the sampling density in zero and two dimensions, respectively. Phantom experiments and a theoretical point spread function analysis were performed to investigate their performance. Variable density sampling in zero and two dimensions was also implemented in a non-EPI GRE pulse sequence for comparison. All subsampled data were reconstructed with a previously described temporally constrained reconstruction (TCR) algorithm. Results: The accuracy of each sampling strategy in measuring the temperature rise in the HIFU focal spot was measured in terms of the root-mean-square-error (RMSE) compared to fully sampled "truth." For the schemes utilizing sequential sampling, the accuracy was found to improve with the dimensionality of the variable density sampling, giving values of 0.65• C, 0.49 • C, and 0.35• C for density variation in zero, one, and two dimensions, respectively. The schemes utilizing centric sampling were found to underestimate the temperature rise, with RMSE values of 1.05• C and 1.31• C, for variable density sampling in zero and two dimensions, respectively. Similar subsampling schemes with variable density sampling implemented in zero and two dimensions in a non-EPI GRE pulse sequence both resulted in accurate temperature measurements (RMSE of 0.70• C and 0.63 • C, respectively). With sequential sampling in the described EPI implementation, temperature monitoring over a 192 × 144 × 135 mm 3 FOV with a temporal resolution of 3.6 s was achieved, while keeping the RMSE compared to fully sampled "truth" below 0.35• C. Conclusions: When segmented EPI readouts are used in conjunction with k-space subsampling for MR thermometry applications, sampling schemes with sequential sampling, with or without variable density sampling, obtain accurate phase and temperature measurements when using a TCR reconstruction algorithm. Improved temperature measurement accuracy can be achieved with variable density sampling. Centric sampling leads to phase bias, resulting in temperature underestimations.

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Simultaneous magnetic resonance phase and magnitude temperature maps in muscle

Cited by 101 publications

References 12 publications

MR thermometry

MR thermometry

Radiofrequency power deposition utilizing thermal imaging

Sampling strategies for subsampled segmented EPI PRF thermometry in MR guided high intensity focused ultrasound

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