Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Grissom WA

PROVIDER: S-EPMC6903412 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Publications

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

Grissom William A WA Allen Steven S

Magnetic resonance in medicine 20190904 3

<h4>Purpose</h4>To reduce temperature errors due to water motion in transcranial MR-guided focused ultrasound (tcMRgFUS) ablation.<h4>Theory and methods</h4>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 ...[more]

PMID: 31483525

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Project description:Background and purposeTranscranial MR imaging-guided focused ultrasound is a promising novel technique to treat multiple disorders and diseases. Planning for transcranial MR imaging-guided focused ultrasound requires both a CT scan for skull density estimation and treatment-planning simulation and an MR imaging for target identification. It is desirable to simplify the clinical workflow of transcranial MR imaging-guided focused ultrasound treatment planning. The purpose of this study was to examine the feasibility of deep learning techniques to convert MR imaging ultrashort TE images directly to synthetic CT of the skull images for use in transcranial MR imaging-guided focused ultrasound treatment planning.Materials and methodsThe U-Net neural network was trained and tested on data obtained from 41 subjects (mean age, 66.4 ± 11.0 years; 15 women). The derived neural network model was evaluated using a k-fold cross-validation method. Derived acoustic properties were verified by comparing the whole skull-density ratio from deep learning synthesized CT of the skull with the reference CT of the skull. In addition, acoustic and temperature simulations were performed using the deep learning CT to predict the target temperature rise during transcranial MR imaging-guided focused ultrasound.ResultsThe derived deep learning model generates synthetic CT of the skull images that are highly comparable with the true CT of the skull images. Their intensities in Hounsfield units have a spatial correlation coefficient of 0.80 ± 0.08, a mean absolute error of 104.57 ± 21.33 HU, and a subject-wise correlation coefficient of 0.91. Furthermore, deep learning CT of the skull is reliable in the skull-density ratio estimation (r = 0.96). A simulation study showed that both the peak target temperatures and temperature distribution from deep learning CT are comparable with those of the reference CT.ConclusionsThe deep learning method can be used to simplify workflow associated with transcranial MR imaging-guided focused ultrasound.

Project description:PurposeTo analyze clinical data indicating a reduction in the induced energy-temperature efficiency relationship during transcranial focused ultrasound (FUS) Essential Tremor (ET) thalamotomy treatments at higher acoustic powers, establish its relationship with the spatial distribution of the focal temperature elevation, and explore its cause.MethodsA retrospective observational study of patients (n = 19) treated between July 2015 and August 2016 for (ET) by FUS thalamotomy was performed. These data were analyzed to compare the relationships between the applied power, the applied energy, the resultant peak temperature achieved in the brain, and the dispersion of the focal volume. Full ethics approval was received and all patients provided signed informed consent forms before the initiation of the study. Computer simulations, animal experiments, and clinical system tests were performed to determine the effects of skull heating, changes in brain properties and transducer acoustic output, respectively. All animal procedures were approved by the Animal Care and Use Committee and conformed to the guidelines set out by the Canadian Council on Animal Care. MATLAB was used to perform statistical analysis.ResultsThe reduction in the energy efficiency relationship during treatment correlates with the increase in size of the focal volume at higher sonication powers. A linear relationship exists showing that a decrease in treatment efficiency correlates positively with an increase in the focal size over the course of treatment (P < 0.01), supporting the hypothesis of transient skull and tissue heating causing acoustic aberrations leading to a decrease in efficiency. Changes in thermal conductivity, perfusion, absorption rates in the brain, as well as ultrasound transducer acoustic output levels were found to have minimal effects on the observed reduction in efficiency.ConclusionsThe reduction in energy-temperature efficiency during high-power FUS treatments correlated with observed increases in the size of the focal volume and is likely caused by transient changes in the tissue and skull during heating.

Project description:This work explored an elementwise approach to model transcranial MRI-guided focused ultrasound (TcMRgFUS) thermal ablation, a noninvasive approach to neurosurgery. Each element of the phased array transducer was simulated individually and could be simultaneously loaded into computer memory, allowing for rapid (~2.5 s) calculation of the pressure field for different phase offsets used for beam steering and aberration correction. We simulated the pressure distribution for 431 sonications in 32 patients, applied the phase and magnitude values used during treatment, and estimated the resulting temperature rise. We systematically varied the relationship between CT (computerized tomography)-derived skull density and the acoustic attenuation and sound speed to obtain the best agreement between the predictions and MR temperature imaging (MRTI). The optimization was validated with simulations of 396 sonications from 40 additional treatments. After optimization, the predicted and measured heating agreed well (R2: 0.74 patients 1-32; 0.71 patients 33-72). The dimensions and obliquity of the heating in the simulated temperature maps were correlated with the MRTI (R2: 0.62, 0.74, respectively), but the measured heating was more spatially diffuse. The energy needed to achieve ablation varied by an order of magnitude (3.3-36.1 kJ). While this elementwise approach required more computation time up front (the combined simulation matrices were approximately 4.6 times higher than a single large simulation), it could be performed in parallel on a computing cluster. It allows for rapid calculation of the three-dimensional heating at the focus for different phase and magnitude values on the array. We also show how this approach can be used to optimize the relationship between CT-derived skull density and acoustic properties. While the relationships found here need further validation in a larger patient population, these results demonstrate the promise of this approach to model TcMRgFUS.

Dataset Information

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

Purpose

Theory and methods

Results

Conclusions

Publications

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

Similar Datasets

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