Spatially-segmented undersampled MRI temperature reconstruction for transcranial MR-guided focused ultrasound

Recent technological advancements in thermometry

Thermometry is the key factor for achieving successful thermal therapy. Although invasive thermometry with a probe has been used for more than four decades, this method can only detect the local temperature within the probing volume. Noninvasive temperature imaging using a tomographic technique is ideal for monitoring hot-spot formation in the human body. Among various techniques, such as X-ray computed tomography, microwave tomography, echo sonography, and magnetic resonance (MR) imaging, the proton resonance frequency shift method of MR thermometry is the only method currently available for clinical practice because its temperature sensitivity is consistent in most aqueous tissues and can be easily observed using common clinical scanners. New techniques are being proposed to improve the robustness of this method against tissue motion. MR techniques for fat thermometry were also developed based on relaxation times. One of the latest non-MR techniques to attract attention is photoacoustic imaging.

Reducing temperature errors in transcranial MR-guided focused ultrasound using a reduced-field-of-view sequence

PURPOSE

To reduce temperature errors due to water motion in transcranial MR-guided focused ultrasound (tcMRgFUS) ablation.

THEORY AND METHODS

In tcMRgFUS, water is circulated in the transducer bowl around the patient's head for acoustic coupling and heat removal. The water moves during sonications that are monitored by MR thermometry, which causes it to alias into the brain and create temperature errors. To reduce these errors, a two-dimensional excitation pulse was implemented in a gradient-recalled echo thermometry sequence. The pulse suppresses water signal by selectively exciting the brain only, which reduces the imaging FOV. Improvements in temperature precision compared to the conventional full-FOV scan were evaluated in healthy subject scans outside the tcMRgFUS system, gel phantom scans in the system with heating, and in 2×-accelerated head phantom scans in the system without heating.

RESULTS

In vivo temperature precision (standard deviation of temperature errors) outside the tcMRgFUS system was improved 43% on average, due to the longer TR and TE of the reduced-FOV sequence. In the phantom heating experiments, the hot spot was less distorted in the reduced-FOV scans, and background temperature precision was improved 59% on average. In the accelerated head phantom temperature reconstructions, temperature precision was improved 89% using the reduced-FOV sequence.

CONCLUSIONS

Reduced-FOV temperature imaging alleviates temperature errors due to water bath motion in tcMRgFUS, and enables accelerated temperature mapping with greater precision.

Simultaneous multislice MRI thermometry with a single coil using incoherent blipped-controlled aliasing

PURPOSE

To increase volume coverage in real-time MR thermometry for transcranial MR-guided focused ultrasound (tcMRgFUS) ablation, without multiple receive coils.

THEORY AND METHODS

Multiband excitation and incoherent blipped-controlled aliasing were implemented in a 2DFT pulse sequence used clinically for tcMRgFUS, and an extended k-space hybrid reconstruction was developed that recovers slice-separated temperature maps assuming that heating is focal, given slice-separated pretreatment images. Simulations were performed to characterize slice leakage, the number of slices that can be simultaneously imaged with low-temperature error, and robustness across random slice-phase k-space permutations. In vivo experiments were performed using a single receive coil without heating to measure temperature precision, and gel phantom FUS experiments were performed to test the method with heating and with a water bath.

RESULTS

Simulations showed that with large hot spots and identical magnitude images on each slice, up to three slices can be simultaneously imaged with less than 1 ∘ C temperature root-mean-square error. They also showed that hot spots do not alias coherently between slices, and that an average 86% of random slice-phase k-space permutations yielded less than 1 ∘ C temperature error. Temperature precision was not degraded compared to single-slice imaging in the in vivo SMS scans, and the gel phantom SMS temperature maps closely tracked single-slice temperature in the hot spot, with no coherent aliasing to other slices.

CONCLUSIONS

Incoherent controlled aliasing SMS enables accurate reconstruction of focal heating maps from two or three slices simultaneously, using a single receive coil and a sparsity-promoting temperature reconstruction.

Low-rank plus sparse compressed sensing for accelerated proton resonance frequency shift MR temperature imaging

PURPOSE

To improve multichannel compressed sensing (CS) reconstruction for MR proton resonance frequency (PRF) shift thermography, with application to MRI-induced RF heating evaluation and MR guided high intensity focused ultrasound (MRgFUS) temperature monitoring.

METHODS

A new compressed sensing reconstruction is proposed that enforces joint low rank and sparsity of complex difference domain PRF data between post heating and baseline images. Validations were performed on 4 retrospectively undersampled dynamic data sets in PRF applications, by comparing the proposed method to a previously described L₁ and total variation- (TV-) based CS approach that also operates on complex difference domain data, and to a conventional low rank plus sparse (L+S) separation-based CS reconstruction applied to the original domain data.

RESULTS

In all 4 retrospective validations, the proposed reconstruction method outperformed the conventional L+S and L₁ +TV CS reconstruction methods with a 3.6× acceleration ratio in terms of temperature accuracy with respect to fully sampled data. For RF heating evaluation, the proposed method achieved RMS error of 12%, compared to 19% for the L+S method and 17% for the L₁ +TV method. For in vivo MRgFUS thalamotomy, the peak temperature reconstruction errors were 19%, 31%, and 35%, respectively.

CONCLUSION

The complex difference-based low rank and sparse model enhances compressibility for dynamic PRF temperature imaging applications. The proposed multichannel CS reconstruction method enables high acceleration factors for PRF applications including RF heating evaluation and MRgFUS sonication.