Method for target tracking in focused ultrasound surgery of liver using magnetic resonance filtered venography

MR techniques for guiding high-intensity focused ultrasound (HIFU) treatments

To make full use of the ability of magnetic resonance (MR) to guide high-intensity focused ultrasound (HIFU) treatment, effort has been made to improve techniques for thermometry, motion tracking, and sound beam visualization. For monitoring rapid temperature elevation with proton resonance frequency (PRF) shift, data acquisition and processing can be accelerated with parallel imaging and/or sparse sampling in conjunction with appropriate signal processing methods. Thermometry should be robust against tissue motion, motion-induced magnetic field variation, and susceptibility change. Thus, multibaseline, referenceless, or hybrid techniques have become important. In cases with adipose or bony tissues, for which PRF shift cannot be used, thermometry with relaxation times or signal intensity may be utilized. Motion tracking is crucial not only for thermometry but also for targeting the focus of an ultrasound in moving organs such as the liver, kidney, or heart. Various techniques for motion tracking, such as those based on an anatomical image atlas with optical-flow displacement detection, a navigator echo to seize the diaphragm position, and/or rapid imaging to track vessel positions, have been proposed. Techniques for avoiding the ribcage and near-field heating have also been examined. MR acoustic radiation force imaging (MR-ARFI) is an alternative to thermometry that can identify the location and shape of the focal spot and sound beam path. This technique could be useful for treating heterogeneous tissue regions or performing transcranial therapy. All of these developments, which will be discussed further in this review, expand the applicability of HIFU treatments to a variety of clinical targets while maintaining safety and precision.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;47:316-331.

Respiration based steering for high intensity focused ultrasound liver ablation

PURPOSE

Respiratory motion makes hepatic ablation using high intensity focused ultrasound (HIFO) challenging. Previous HIFU liver treatment had required apnea induced during general anesthesia. We describe and test a system that allows treatment of the liver in the presence of breathing motion.

METHODS

Mapping a signal from an external respiratory bellow to treatment locations within the liver allows the ultrasound transducer to be steered in real time to the target location. Using a moving phantom, three metrics were used to compare static, steered, and unsteered sonications: the area of sonications once a temperature rise of 15°C was achieved, the energy deposition required to reach that temperature, and the average rate of temperature rise during the first 10 s of sonication. Steered HIFU in vivo ablations of the porcine liver were also performed and compared to breath-hold ablations.

RESULTS

For the last phantom metric, all groups were found to be statistically significantly different (P ≤ 0.003). However, in the other two metrics, the static and unsteered sonications were not statistically different (P > 0.9999). Steered in vivo HIFU ablations were not statistically significantly different from ablations during breath-holding.

CONCLUSIONS

A system for performing HIFU steering during ablation of the liver with breathing motion is presented and shown to achieve results equivalent to ablation performed with breath-holding.

Multipathway sequences for MR thermometry

MR-based thermometry is a valuable adjunct to thermal ablation therapies as it helps to determine when lethal doses are reached at the target and whether surrounding tissues are safe from damage. When the targeted lesion is mobile, MR data can further be used for motion-tracking purposes. The present work introduces pulse sequence modifications that enable significant improvements in terms of both temperature-to-noise-ratio properties and target-tracking abilities. Instead of sampling a single magnetization pathway as in typical MR thermometry sequences, the pulse-sequence design introduced here involves sampling at least one additional pathway. Image reconstruction changes associated with the proposed sampling scheme are also described. The method was implemented on two commonly used MR thermometry sequences: the gradient-echo and the interleaved echo-planar imaging sequences. Data from the extra pathway enabled temperature-to-noise-ratio improvements by up to 35%, without increasing scan time. Potentially of greater significance is that the sampled pathways featured very different contrast for blood vessels, facilitating their detection and use as internal landmarks for tracking purposes. Through improved temperature-to-noise-ratio and lesion-tracking abilities, the proposed pulse-sequence design may facilitate the use of MR-monitored thermal ablations as an effective treatment option even in mobile organs such as the liver and kidneys.

Reweighted ℓ1 referenceless PRF shift thermometry

Temperature estimation in proton resonance frequency (PRF) shift MR thermometry requires a reference, or pretreatment, phase image that is subtracted from image phase during thermal treatment to yield a phase difference image proportional to temperature change. Referenceless thermometry methods derive a reference phase image from the treatment image itself by assuming that in the absence of a hot spot, the image phase can be accurately represented in a smooth (usually low order polynomial) basis. By masking the hot spot out of a least squares (ℓ(2)) regression, the reference phase image's coefficients on the polynomial basis are estimated and a reference image is derived by evaluating the polynomial inside the hot spot area. Referenceless methods are therefore insensitive to motion and bulk main field shifts, however, currently these methods require user interaction or sophisticated tracking to ensure that the hot spot is masked out of the polynomial regression. This article introduces an approach to reference PRF shift thermometry that uses reweighted ℓ(1) regression, a form of robust regression, to obtain background phase coefficients without hot spot tracking and masking. The method is compared to conventional referenceless thermometry, and demonstrated experimentally in monitoring HIFU heating in a phantom and canine prostate, as well as in a healthy human liver.

Hybrid referenceless and multibaseline subtraction MR thermometry for monitoring thermal therapies in moving organs

PURPOSE

Magnetic resonance thermometry using the proton resonance frequency (PRF) shift is a promising technique for guiding thermal ablation. For temperature monitoring in moving organs, such as the liver and the heart, problems with motion must be addressed. Multi-baseline subtraction techniques have been proposed, which use a library of baseline images covering the respiratory and cardiac cycle. However, main field shifts due to lung and diaphragm motion can cause large inaccuracies in multi-baseline subtraction. Referenceless thermometry methods based on polynomial phase regression are immune to motion and susceptibility shifts. While referenceless methods can accurately estimate temperature within the organ, in general, the background phase at organ/tissue interfaces requires large polynomial orders to fit, leading to increased danger that the heated region itself will be fitted by the polynomial and thermal dose will be underestimated. In this paper, a hybrid method for PRF thermometry in moving organs is presented that combines the strengths of referenceless and multi-baseline thermometry.

METHODS

The hybrid image model assumes that three sources contribute to image phase during thermal treatment: Background anatomical phase, spatially smooth phase deviations, and focal, heat-induced phase shifts. The new model and temperature estimation algorithm were tested in the heart and liver of normal volunteers, in a moving phantom HIFU heating experiment, and in numerical simulations of thermal ablation. The results were compared to multi-baseline and referenceless methods alone.

RESULTS

The hybrid method allows for in vivo temperature estimation in the liver and the heart with lower temperature uncertainty compared to multi-baseline and referenceless methods. The moving phantom HIFU experiment showed that the method accurately estimates temperature during motion in the presence of smooth main field shifts. Numerical simulations illustrated the method's sensitivity to algorithm parameters and hot spot features.

CONCLUSIONS

This new hybrid method for MR thermometry in moving organs combines the strengths of both multi-baseline subtraction and referenceless thermometry and overcomes their fundamental weaknesses.