Referenceless Thermometry Research Articles

A Computational Study on Temperature Variations in MRgFUS Treatments Using PRF Thermometry Techniques and Optical Probes.

Structural and metabolic imaging are fundamental for diagnosis, treatment and follow-up in oncology. Beyond the well-established diagnostic imaging applications, ultrasounds are currently emerging in the clinical practice as a noninvasive technology for therapy. Indeed, the sound waves can be used to increase the temperature inside the target solid tumors, leading to apoptosis or necrosis of neoplastic tissues. The Magnetic resonance-guided focused ultrasound surgery (MRgFUS) technology represents a valid application of this ultrasound property, mainly used in oncology and neurology. In this paper; patient safety during MRgFUS treatments was investigated by a series of experiments in a tissue-mimicking phantom and performing ex vivo skin samples, to promptly identify unwanted temperature rises. The acquired MR images, used to evaluate the temperature in the treated areas, were analyzed to compare classical proton resonance frequency (PRF) shift techniques and referenceless thermometry methods to accurately assess the temperature variations. We exploited radial basis function (RBF) neural networks for referenceless thermometry and compared the results against interferometric optical fiber measurements. The experimental measurements were obtained using a set of interferometric optical fibers aimed at quantifying temperature variations directly in the sonication areas. The temperature increases during the treatment were not accurately detected by MRI-based referenceless thermometry methods, and more sensitive measurement systems, such as optical fibers, would be required. In-depth studies about these aspects are needed to monitor temperature and improve safety during MRgFUS treatments.

Reference-less MR thermometry on pre-clinical thiel human cadaver for liver surgery with MRgFUS

Purpose: Reference-less MR thermometry can be a promising technique for temperature mapping during liver treatment with Magnetic Resonance-guided Focused Ultrasound (MRgFUS), as it is more robust to breathing motion than Proton Resonance Frequency MR thermometry. However, there is a lack of a pre-clinical model for repeatable testing of reference-less thermometry. The purpose of this work was to verify the explanted Thiel embalmed human liver and whole Thiel embalmed human cadaver for application of a custom made reference-less thermometry algorithm during MRgFUS sonication.Material and methods: Phase maps were generated during sonication as an input to the algorithm. A square Region-of-Interest (ROI) was designed around the heated area. The ROI was interpolated using a two-dimensional polynomial to the surrounding phase map to calculate the background phase.Results: Using the phase information from the images, the temperature rise was measured. Validation of the methodology showed accordance of temperatures with actual temperatures.Conclusions: The explanted liver and the whole cadaver constitute a promising and feasible model to study reference-less techniques for thermometry during MRgFUS, before clinical trials.

Motion Correction in Proton Resonance Frequency-based Thermometry in the Liver.

The unique ability of magnetic resonance imaging to measure temperature noninvasively, in vivo, makes it an attractive tool for monitoring interventional procedures, such as radiofrequency or microwave ablation in real-time. The most frequently used approach for magnetic resonance-based temperature measurement is proton resonance frequency (PRF) thermometry. Although it has many advantages, including tissue-independence and real-time capability, the main drawback is its motion sensitivity. This is likely the reason PRF thermometry in moving organs, such as the liver, is not commonly used in the clinical arena. In recent years, however, several developments suggest that motion-corrected thermometry in the liver is achievable. The present article summarizes the diverse attempts to correct thermometry in the liver. Therefore, the physical principle of PRF is introduced, with additional references for necrosis zone estimation and how to deal with fat phase modulation, and main magnetic field drifts. The primary categories of motion correction are presented, including general methods for motion compensation and library-based approaches, and referenceless thermometry and hybrid methods. Practical validation of the described methods in larger patient groups will be necessary to establish accurate motion-corrected thermometry in the clinical arena, with the goal of complete liver tumor ablation.

Applications of imaging processing to MRgFUS treatment for fibroids: a review

Magnetic resonance guided focused ultrasound (MRgFUS) is an innovative technology that can treat many oncological diseases. Among these, uterine fibroids are well suited to be treated by focused ultrasound, because the treatment, unlike traditional surgical resection, is non-invasive and thus preserves the desired reproductive capacity of patients. There are some methodological issues in MRgFUS treatment that should be addressed. First, there is operator dependence; this is related to the use of manual approaches for the segmentation of regions of interest (ROIs) for treatment, both in the initial stages of treatment planning and in the post-treatment evaluation of the ablated area. From this scenario, we understand the need to integrate MRgFUS technology with methods for the automatic detection of the regions affected by the treatment. Temperature monitoring techniques, based on proton resonance shift (PRF), although not always able to provide correct measurements, are the most used in the treatments guided by magnetic resonance. The dependence on a reference image makes the thermal maps obtained through PRF subject to artefacts and, consequently, to temperature measurement errors. It is therefore crucial to develop new techniques, perhaps based on referenceless thermometry approaches, in order to avoid overheating in unwanted areas that could lead to patients suffering burns. Closely linked to the two above mentioned problems , there is the motion compensation that would improve the current method (this requires re-planning MRgFUS treatment in cases of patient movement) as well as temperature monitoring since it would overcome limitations related to a fixed baseline image, uncorrelated to the real patient position. This paper addresses these important issues, providing for each of them a high-level discussion able to give a brief overview. Specific technical details are provided about one of the approaches in the literature, in order to make the discussed problem more complete and easier to understand.

A fast referenceless PRFS-based MR thermometry by phase finite difference

Proton resonance frequency shift-based MR thermometry is a promising temperature monitoring approach for thermotherapy but its accuracy is vulnerable to inter-scan motion. Model-based referenceless thermometry has been proposed to address this problem but phase unwrapping is usually needed before the model fitting process. In this paper, a referenceless MR thermometry method using phase finite difference that avoids the time consuming phase unwrapping procedure is proposed. Unlike the previously proposed phase gradient technique, the use of finite difference in the new method reduces the fitting error resulting from the ringing artifacts associated with phase discontinuity in the calculation of the phase gradient image. The new method takes into account the values at the perimeter of the region of interest because of their direct relevance to the extrapolated baseline phase of the region of interest (where temperature increase takes place). In simulation study, in vivo and ex vivo experiments, the new method has a root-mean-square temperature error of 0.35 °C, 1.02 °C and 1.73 °C compared to 0.83 °C, 2.81 °C, and 3.76 °C from the phase gradient method, respectively. The method also demonstrated a slightly higher, albeit small, temperature accuracy than the original referenceless MR thermometry method. The proposed method is computationally efficient (∼0.1 s per image), making it very suitable for the real time temperature monitoring.

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

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. 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. 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. 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.

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 multi-baseline subtraction thermometry for monitoring thermal therapies in the heart

However, main field shifts due to lung and diaphragm motion can still cause large inaccuracies in multi-baseline subtraction. In contrast, referenceless thermometry methods [3-5] based on polynomial phase regression are immune to motion and susceptibility shifts. While referenceless methods can be accurate in localized regions of the heart, in general the background phase in the myocardial wall requires large polynomial orders to fit, leading to increased danger that the hot spot itself will be fit by the polynomial and thermal dose will be underestimated.

Real‐time MR thermometry for monitoring HIFU ablations of the liver

A high-resolution and high-speed pulse sequence is presented for monitoring high-intensity focused ultrasound ablations in the liver in the presence of motion. The sequence utilizes polynomial-order phase saturation bands to perform outer volume suppression, followed by spatial-spectral excitation and three readout segmented echo-planar imaging interleaves. Images are processed with referenceless thermometry to create temperature-rise images every frame. The sequence and reconstruction were implemented in RTHawk and used to image stationary and moving sonications in a polyacrylamide gel phantom (62.4 acoustic W, 50 sec, 550 kHz). Temperature-rise images were compared between moving and stationary experiments. Heating spots and corresponding temperature-rise plots matched very well. The stationary sonication had a temperature standard deviation of 0.15 degrees C compared to values of 0.28 degrees C and 0.43 degrees C measured for two manually moved sonications at different velocities. Moving the phantom (while not heating) with respect to the transducer did not cause false temperature rises, despite susceptibility changes. The system was tested on nonheated livers of five normal volunteers. The mean temperature rise was -0.05 degrees C, with a standard deviation of 1.48 degrees C. This standard deviation is acceptable for monitoring high-intensity focused ultrasound ablations, suggesting real-time imaging of moving high-intensity focused ultrasound sonications can be clinically possible.

Evaluation of referenceless thermometry in MRI‐guided focused ultrasound surgery of uterine fibroids

To clinically assess a previously described method (Rieke et.al., Magn Reson Med 2004) to produce more motion-robust MRI-based temperature images using data acquired during MRI-guided focused ultrasound surgery (MRgFUS) of uterine fibroids. The method ("referenceless thermometry") uses surface fitting in nonheated regions of individual phase images to extrapolate and then remove background phase variations that are unrelated to temperature changes. We tested this method using images from 100 sonications selected from 33 patient MRgFUS treatments. Temperature measurements and thermal dose contours estimated with the referenceless method were compared with those produced with the standard phase-difference technique. Fitting accuracy and noise level were also measured. In 92/100 sonications, the difference between the two measurements was less than 3 degrees C. The average difference in the measurements was 1.5 +/- 1.4 degrees C. Small motion artifacts were observed in the phase-difference imaging when the difference was greater than 3 degrees C. The method failed in two cases. The mean absolute error in the surface fit in baseline images corresponded to a temperature error of 0.8 +/- 1.4 degrees C. The noise level was approximately 40% lower than the phase-difference method. Thermal dose contours calculated from the two methods agreed well on average. Based on the small error when compared with the standard technique, this method appears to be adequate for temperature monitoring of MRgFUS in uterine fibroids and may prove useful for monitoring temperature changes in moving organs.

Referenceless MR Thermometry for Monitoring Thermal Ablation in the Prostate

Referenceless proton resonance frequency (PRF) shift thermometry provides a means to measure temperature changes during minimally invasive thermotherapy that is inherently robust to motion and tissue displacement. However, if the referenceless method is used to determine temperature changes during prostate ablation, phase gaps between water and fat in image regions used to determine the background phase can confound the phase estimation. We demonstrate an extension to referenceless thermometry which eliminates this problem by allowing background phase estimation in the presence of phase discontinuities between aqueous and fatty tissue. In this method, images are acquired with a multiecho sequence and binary water and fat maps are generated from a Dixon reconstruction. For the background phase estimation, water and fat regions are treated separately and the phase offset between the two tissue types is determined. The method is demonstrated feasibile in phantoms and during in vivo thermal ablation of canine prostate.