Intraoperative lesion characterization after focused ultrasound thalamotomy

Francesco Sammartino Department of Neurosurgery, The Ohio State University, Columbus, Ohio; and

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Fang-Cheng Yeh Department of Neurosurgery, University of Pittsburgh, Pennsylvania

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Vibhor Krishna Department of Neurosurgery, The Ohio State University, Columbus, Ohio; and

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OBJECTIVE

Outcomes after focused ultrasound ablation (FUSA) for essential tremor remain heterogeneous, despite therapeutic promise. Clinical outcomes are directly related to the volume and location of the therapeutic lesions, consistent with CNS ablative therapies. Recent data demonstrate that postoperative diffusion MRI, specifically the quantification of intracellular diffusion by restricted diffusion imaging (RDI), can accurately characterize focused ultrasound lesions. However, it is unclear whether RDI can reliably detect focused ultrasound lesions intraoperatively (i.e., within a few minutes of lesioning) and whether the intraoperative lesions predict delayed clinical outcomes.

METHODS

An intraoperative imaging protocol was implemented that included RDI and T2-weighted imaging in addition to intraoperative MR thermography. Lesion characteristics were defined with each sequence and then compared. An imaging-outcomes analysis was performed to determine lesion characteristics associated with delayed clinical outcomes.

RESULTS

Intraoperative RDI accurately identified the volume and location of focused ultrasound lesions. Intraoperative T2-weighted imaging underestimated the lesion volume but accurately identified the location. Intraoperative RDI revealed that lesions of the ventral border of the ventral intermediate nucleus were significantly associated with postoperative tremor improvement. In contrast, the lesions extending into the inferolateral white matter were associated with postoperative ataxia.

CONCLUSIONS

These data support the acquisition of intraoperative RDI to characterize focused ultrasound lesions. Future research should test the histological correlates of intraoperative RDI and test whether it can be developed as feedback to optimize the current technique of FUSA.

ABBREVIATIONS

AUC = area under the ROC curve; CEM = cumulative equivalent minute; FUSA = focused ultrasound ablation; GQI = generalized q-sampling imaging; RDI = restricted diffusion imaging; ROC = receiver operating characteristic; ROI = region of interest; VIM = ventral intermediate nucleus.

OBJECTIVE

Outcomes after focused ultrasound ablation (FUSA) for essential tremor remain heterogeneous, despite therapeutic promise. Clinical outcomes are directly related to the volume and location of the therapeutic lesions, consistent with CNS ablative therapies. Recent data demonstrate that postoperative diffusion MRI, specifically the quantification of intracellular diffusion by restricted diffusion imaging (RDI), can accurately characterize focused ultrasound lesions. However, it is unclear whether RDI can reliably detect focused ultrasound lesions intraoperatively (i.e., within a few minutes of lesioning) and whether the intraoperative lesions predict delayed clinical outcomes.

METHODS

An intraoperative imaging protocol was implemented that included RDI and T2-weighted imaging in addition to intraoperative MR thermography. Lesion characteristics were defined with each sequence and then compared. An imaging-outcomes analysis was performed to determine lesion characteristics associated with delayed clinical outcomes.

RESULTS

Intraoperative RDI accurately identified the volume and location of focused ultrasound lesions. Intraoperative T2-weighted imaging underestimated the lesion volume but accurately identified the location. Intraoperative RDI revealed that lesions of the ventral border of the ventral intermediate nucleus were significantly associated with postoperative tremor improvement. In contrast, the lesions extending into the inferolateral white matter were associated with postoperative ataxia.

CONCLUSIONS

These data support the acquisition of intraoperative RDI to characterize focused ultrasound lesions. Future research should test the histological correlates of intraoperative RDI and test whether it can be developed as feedback to optimize the current technique of FUSA.

In Brief

An accurate lesion characterization is crucial to optimize focused ultrasound (FUS) treatment parameters and ultimately improve clinical outcomes. This study found that intraoperative restricted diffusion imaging (RDI) accurately identified the volume and location of FUS lesions. Lesions adjacent to the ventral border of the VIM were significantly associated with tremor improvement; in contrast, lesion extension into the inferolateral white matter was associated with ataxia. These data support the acquisition of intraoperative RDI to characterize FUS lesions.

Ventral intermediate nucleus focused ultrasound ablation (VIM FUSA) is an emerging treatment for essential tremor.1 VIM FUSA was significantly more effective than sham treatment in a blinded, randomized controlled trial.2 Since experience has accumulated with the VIM FUSA technique worldwide, it is now being optimized to reduce the risk of adverse events and improve patient outcomes.3 Specifically, advances in tractography-based VIM targeting represent one such opportunity to reduce the risk of neurological deficits from the off-target ablation of the corticospinal tract and medial lemniscus.4,5 Parallel efforts are also underway to define the optimal parameters for subthreshold testing to systematically explore the stereotactic target before delivering permanent ablation.6 Yet more work is required with this technique to reduce the risks and improve clinical outcomes; one-third of patients remain at risk for developing ataxia and imbalance after VIM FUSA.7 Whether this risk of ataxia is specific to the lesion characteristics (such as size and location) or related to secondary tissue damage or perilesional edema is unknown.8 Accurate characterization of VIM FUSA lesions is therefore crucial to optimize treatment parameters against the in vivo tissue response and ultimately improve the long-term clinical outcomes.

The biological effects of focused ultrasound thermal energy are well defined in the preclinical models: a thermal dose of 240 cumulative equivalent minutes (CEMs) created coagulative necrosis in the brain tissue.9,10 Therefore, an intraoperative thermal dose, specifically the 240-CEM dose envelope, was implemented in the clinical FUSA system (ExAblate 4000, Insightec Inc.) to guide intraoperative decision-making during VIM FUSA. Despite its merits, thermal dose estimation has limitations. For example, 2D thermography imaging using a single-slice acquisition and a thermal spot shift in the frequency-encoding direction limit an accurate 3D estimation of the VIM FUSA lesions.1012 Therefore, other imaging methods such as T2-weighted imaging and diffusion MRI were also tested to characterize FUSA lesions. T2-weighted imaging is the most popular method because it can be easily acquired, and it differentiates the lesion from postoperative edema.1318 Lesion characterization using T2-weighted imaging, however, is specific to the timing of the acquisition; for example, the FUSA lesions almost double in size within the first few weeks, and eventually they become indistinguishable from the surrounding tissue in a few months after VIM FUSA.19 These limitations led several groups to test diffusion MRI to characterize VIM FUSA lesions after surgery.8,20,21 Diffusion MRI accurately distinguished coagulative necrosis from edema in an imaging histology study.21 We were able to detect VIM FUSA lesions not only at 24 hours, but also at 1 year after surgery using a slightly different analytical approach of restricted diffusion imaging (RDI).20 RDI-based lesion characterization revealed that the size and location of postoperative lesions were significant predictors of outcomes.

Although these initial insights from postoperative imaging are promising, their clinical application is limited because the imaging was acquired several hours to days after the surgery. To optimize the FUSA surgical technique, the treatment parameters will need to be optimized against immediate feedback of tissue response obtained from RDI.22 However, it is unknown whether intraoperative RDI, measured by an imaging acquisition within a few minutes of lesioning, can accurately detect the FUSA lesion volume and location. To test this paradigm, we implemented an ad hoc imaging protocol to detect intraoperative RDI change. We then performed a descriptive study to characterize VIM FUSA lesions, comparing RDI-based lesions to intraoperative T2-weighted and thermographic imaging, the current standard of care. We also acquired postoperative RDI and T2-weighted imaging to detect any timing-specific changes 1 week after VIM FUSA. We hypothesized that RDI would accurately detect VIM FUSA lesion volume and location on intraoperative imaging, and RDI-based lesion characterization was not specific to the timing of imaging acquisition. Furthermore, we hypothesized that RDI-based lesion characterization would distinguish lesion characteristics associated with postoperative ataxia from those associated with tremor relief.

Methods

We included consecutive patients with a clinical diagnosis of essential tremor as determined by a multidisciplinary assessment. All patients provided written informed consent as a part of this IRB-approved study at The Ohio State University Wexner Medical Center.

Surgical Treatment

The details of the surgical procedure for VIM FUSA were described in an earlier report.1 Briefly, the VIM was identified using tractography.23 The pyramidal tract and medial lemniscus were first identified, and the location of the VIM region of interest (ROI), measuring 4 × 4 × 6 mm, was determined medial and anterior to these tracts, respectively. The VIM ROI was then overlaid on a preoperative T1-weighted scan. After stereotactic frame placement, the ultrasound transducer was positioned over the patient’s head. The space between the head and the transducer was filled with degassed water for coupling and local cooling. Initial scans included structural acquisitions in all three planes through the thalamus. These images were then coregistered with preoperative T1-weighted imaging with the VIM ROI.

Several ablative sonications were performed after subthreshold testing. We performed frequent clinical testing to detect any side effects and determine tremor relief. Treatment was deemed complete based on tremor assessment, adequate VIM coverage with ablative thermal dose, or appearance of any side effects.

Tremor Assessment

Clinical assessment included tremor rating with motor tasks (i.e., action, posture, and intention) and writing assessment (spiral, straight line, and handwriting) using parts A and B of the Clinical Rating Scale for Tremor. The total score on this scale was 24, and a higher score indicates worse tremor. A tremor improvement percentage was calculated by subtracting the tremor scores after VIM FUSA from the baseline tremor score. The percentage tremor improvement contralateral to the treated hemisphere was scaled and centered before inputting into the statistical model.

Ataxia Assessment

Presence or absence of ataxia was determined by a neurological examination of the limbs, trunk, and gait at the last follow-up visit. Specifically, ataxia was considered present if the patient developed postoperative dysmetria, incoordination, or gait imbalance.

Baseline Imaging Acquisition

Diffusion MRI was acquired 6–8 weeks before surgery on a 3-T MRI scanner (Achieva, Philips Medical Systems) using a 32-channel head coil. Whole-brain diffusion imaging data were acquired using a single-shot spin-echo echo planar imaging sequence, consisting of the following parameters: axial acquisition, TR 8100 msec, TE 68 msec, flip angle 90°, monopolar diffusion gradient, 60 directions, diffusion gradient timing DELTA/delta 32.8/21.6 msec, b-values 0 and 1000 sec/mm2, fat suppression using spectral presaturation with inversion recovery, 240 × 240–mm field of view, 2-mm isotropic in-plane resolution, 60 transverse interleaved slices, zero gap, 2-mm slice thickness, and SENSE factor 2.

We also acquired a 3D fast gradient echo T1-weighted sequence with the following parameters: TR 8.2 msec, TE 3.7 msec, flip angle 8°, field of view 240 mm2, 240 × 240 acquisition matrix, voxel size 1 mm isotropic (n = 160, transverse), and SENSE factor 1.5. A 3D whole-brain axial T2-weighted image with a 1-mm resolution was acquired (TE 80 msec, TR 6650 msec, 0.83 × 0.83 × 1.2 mm, flip angle 90°).

Intraoperative Imaging Acquisition

Intraoperative thermography was acquired using proton shift imaging as implemented in the VIM FUSA standard of care. Diffusion MR images were acquired immediately before and after (within a few minutes) VIM FUSA on a 3-T MRI machine (Discovery 750, GE Medical Systems) using a 32-channel head coil. The ultrasound transducer and head frame were removed to reduce imaging artifacts. Partial volume diffusion imaging data were acquired using a single-shot spin-echo echo planar imaging sequence, consisting of the following parameters: sagittal partial acquisition centered on the treated thalamus, in-plane resolution 1.5 mm, slice thickness 1.5 mm, TR 4370 msec, 150 × 150 matrix, TE 114 msec, b-values 0 and 1000 sec/mm2, flip angle 90°, and 60 diffusion gradient (monopolar) directions. We also acquired an opposite phase-encoding volume at each run to correct for phase distortion artifacts. In addition, a T2-weighted turbo field echo scan was acquired after VIM FUSA using the following parameters: TE 90.7 msec, TR 9633 msec, 1-mm in-plane resolution, 2-mm slice thickness, no slice gap, 256 × 256 matrix, axial acquisition, 70 slices.

Postoperative Imaging Acquisition

Diffusion MRI and T1- and T2-weighted imaging were acquired 1 week after VIM FUSA using the scanner and protocol given above for baseline imaging acquisition.

Diffusion Imaging Preprocessing

All DICOM images were converted into the NIfTI format using dcm2nii software.24 Each diffusion scan was first corrected for any distortions due to eddy currents and head motion using Eddy software (FSL).24 The corrected images were processed at later stages with trilinear interpolation. In this step, the first diffusion MRI acquisition was set as the target image, into which the remaining 60 volumes were registered. We applied “topup” correction to the intraoperative images to account for the susceptibility-induced off-resonance field artifact.

Estimation of Diffusion Metrics

For each subject, the motion-corrected diffusion data were reconstructed in diffusion MRI space with DSI Studio software (May 10, 2021 build) using the generalized q-sampling imaging (GQI) algorithm with a diffusion sampling length of 1.2 mm. We extracted RDI maps for each subject and time point (intra- and postoperative). ANTs software with a combination of rigid and affine transforms was used to align the intra- and postoperative diffusion MRI and T2-weighted images for each subject to the baseline T1-weighted images.25 To perform group analysis, each subject’s RDI maps and segmentation label maps were nonlinearly registered to the MNI ICBM 2009c template space using ANTs software. All lesion segmentations were aligned to the left hemisphere.

Lesion Segmentation

We used 3DSlicer (Slicer.org) software to segment the thermal dose exports from the treatment console. The console displays the VIM region that received an accumulated (at the completion of VIM FUSA) thermal dose ≥ 240 CEMs.26 The 240-CEM dose envelope was segmented for each patient as a distinct label map and scaled appropriately based on the pixel scale provided by the treatment console to perform volumetric analysis. Each thalamic lesion was manually segmented on the intra- and postoperative T2-weighted imaging using ITK-snap software (www.itksnap.org). A label was then created to include the necrotic center and the rim immediately surrounding the lesion using a previously validated approach.27

To compute lesion volume from the diffusion MRI, we computed subject-specific percentage RDI change maps in a volume of 10 × 10 × 10 voxels individually centered at each lesion, similar to a previously published methodology.20 Each map was individually thresholded to define the VIM FUSA lesion. An RDI change threshold of 30.7% increase from baseline, representing a sensitivity of 90% and specificity of 94%, was used to detect FUSA lesions.20

The lesion volumes were then calculated from the label maps obtained from thermography, T2-weighted imaging, and RDI separately for the intra- and postoperative imaging. To determine the lesion location, lesion overlap with the VIM ROI (or target coverage) was calculated. For this purpose, the VIM ROI was intersected with the imaging-specific lesion label maps to calculate a target coverage, expressed as percentage of VIM volume overlap with the lesion, with 100% indicating complete coverage and 0% indicating no coverage. This was calculated for each patient at each time point (intra- and postoperatively).

Statistical Analysis

All analyses were performed using packages in R language (version 3.4.3, R Foundation for Statistical Computing). The Shapiro-Wilk test was used to test data normality. Group metrics were described using mean and standard deviation for normally distributed data and median and interquartile range for nonnormal distributions.

Lesion Volume Comparison

The group mean lesion volume from thermography was compared to intra- and postoperative T2-weighted imaging and RDI using two-tailed t-tests. To test the reliability of lesion volume estimation from intraoperative imaging, we statistically analyzed the relationship between the lesion volumes from the intra- and postoperative imaging using Pearson’s correlation coefficient. A leave-one-out cross-validation analysis was performed to predict postoperative lesion volume and create receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) was then calculated (pROC library28). An AUC > 0.7 was considered clinically meaningful.29

Lesion Location Comparison

The group mean target coverage from thermography was compared between intra- and postoperative T2-weighted imaging and RDI using two-tailed t-tests. To test the reliability of target coverage estimation from intraoperative imaging, the target coverage between intra- and postoperative imaging was statistically compared using Pearson’s correlation coefficient. A leave-one-out cross-validation analysis was performed to predict target coverage on postoperative imaging and create an ROC; an AUC > 0.7 was considered clinically meaningful.29

Lesion Locations Associated With Tremor Improvement and Ataxia

We performed a voxel-wise comparison of RDI maps and segmentation results using general linear models (FSL) with F-tests to detect significant differences across time points, followed by t-tests to understand the direction of the significant changes, controlling for covariates. The tests were run through randomize software (FSL) with threshold-free cluster enhancement, using 5000 permutations. To determine the lesion location associated with optimal tremor improvement, each lesion was weighted by its corresponding tremor improvement. The group-level lesion maps were then thresholded to identify statistically significant voxels associated with tremor improvement greater than the mean tremor improvement for the group. To define lesion locations associated with ataxia, the patient-specific lesions were similarly weighted and thresholded to define the voxels shared between at least 50% of the patients who developed postoperative ataxia. The voxels significantly associated with tremor improvement and ataxia were then classified using the HCP842 white matter atlas.30

Bonferroni correction was applied to account for multiple comparisons arising from the analysis of two variables (lesion volume, target coverage) at two imaging time points (intra- and postoperative) with three imaging sequences (thermography, T2-weighted imaging, and RDI). A p value ≤ 0.004 was considered statistically significant. The data that support the findings of this study can be made available from the corresponding author upon reasonable request.

Results

Among the 19 patients included in this analysis, 7 were women. Most patients (15 of 19) received left-sided VIM FUSA. The mean (± SD) age of the cohort was 75 ± 8 years. The mean follow-up duration was 6.7 ± 2.8 months. An average of 7 ± 2 sonications were performed during VIM FUSA. Four patients developed ataxia postoperatively. The mean tremor reduction at the last follow-up was 84.8% ± 18.6%.

Lesion Volume Comparisons

As shown in Fig. 1, the lesion volume was specific to the imaging modality. Intraoperative T2-weighted imaging significantly underestimated lesion volume (0.11 ± 0.04 cm3) in comparison to thermography (0.24 ± 0.09 cm3, p = 6.56e−06). In contrast, RDI estimated the lesion volume to be larger, although not statistically significantly different, than thermography (0.39 ± 0.21 cm3, p = 0.009). Lesion volume determined by imaging was specific to the timing of acquisition (postoperative T2-weighted lesion volume 0.18 ± 0.08 cm3, p = 0.003). Lesion volume as determined by RDI did not change between intra- and postoperative imaging (0.37 ± 0.23 cm3, p = 0.66).

FIG. 1.
FIG. 1.

Bar graph comparing lesion volumes between intra- and postoperative imaging. *p < 0.05, **p < 0.01, ***p < 0.001. T2w = T2-weighted. Figure is available in color online only.

The lesion volumes estimated by the intra- and postoperative RDI were correlated (Pearson’s correlation coefficient = 0.49, p = 0.027). Intraoperative RDI was highly reliable in predicting postoperative lesion volume (AUC = 0.97). Such correlation did not exist for T2-weighted imaging (Pearson’s correlation coefficient = 0.12, p = 0.61). Lesion volume estimation on intra- and postoperative imaging in a representative patient is shown in Fig. 2.

FIG. 2.
FIG. 2.

Lesion characterization with intra- and postoperative imaging in a representative patient: intraoperative thermography (A), intraoperative RDI (B), postoperative RDI (C), intraoperative T2-weighted sequence (D), and postoperative T2-weighted sequence (E). Figure is available in color online only.

Lesion Location Comparisons

The target coverage was found to be specific to the imaging modality (Fig. 3). Intraoperative thermography significantly underestimated target coverage (42.4% ± 15.2%) in comparison to T2-weighted imaging (66.8% ± 24.8%, p = 8.45e−10) and RDI (54.3% ± 33.1%, p = 1.30e−06). Interestingly, target coverage did not change in postoperative imaging: postoperative target coverage was 68.3% ± 24.3% for T2-weighted imaging and 53.5% ± 34% for RDI (p = 0.94).

FIG. 3.
FIG. 3.

Bar graph comparing target coverage between intra- and postoperative imaging. *p < 0.05, **p < 0.01, ***p < 0.001. TVIM = tractography-defined VIM. Figure is available in color online only.

There was a significant correlation between target coverage estimated by intra- and postoperative RDI (Pearson’s correlation coefficient = 0.66, p = 0.0015). Intraoperative RDI was reliable in predicting postoperative target coverage (AUC = 0.71). There was no significant correlation between target coverage estimates for intra- and postoperative T2-weighted imaging (Pearson’s correlation coefficient = 0.43, p = 0.06, AUC = 0.64).

Lesion Locations Associated With Tremor Improvement and Ataxia

Intraoperative RDI differentiated between lesion locations associated with postoperative tremor relief and ataxia. While the lesions near the ventral VIM border were significantly associated with tremor reduction, the lesion extension beyond the VIM boundaries, specifically into the inferolateral white matter, was associated with ataxia (Fig. 4). The lesion volumes were not significantly different between the two groups (ataxia vs no ataxia, p = 0.11; tremor improvement higher than vs lower than the mean, p = 0.45). Lesion location associated with tremor relief significantly overlapped with the dentatorubrothalamic tract (52%), parietopontine tract (32%), and the medial lemniscus (18%). For ataxia, the lesion overlap with the following tracts was significant: corticospinal tract (47%), parietopontine tract (36%), medial lemniscus (13%), and frontopontine tract (4%).

FIG. 4.
FIG. 4.

Lesion locations significantly associated with postoperative tremor relief (green) and ataxia (red) revealed by intraoperative RDI. Figure is available in color online only.

Discussion

We developed and implemented an intraoperative imaging protocol, using RDI and T2-weighted sequences to compare with intraoperative MR thermography. Intraoperative RDI accurately identified the volume and location of focused ultrasound lesions. Intraoperative T2-weighted imaging underestimated the lesion volume but accurately identified the lesion location. Intraoperative RDI identified lesion locations associated with delayed postoperative clinical outcomes.

Current VIM FUSA Technique

Intraoperative Clinical Assessment and Its Limitations

VIM FUSA is an emerging treatment for medication-refractory essential tremor, which is both efficacious and cost-effective.31 It is promising and attractive to patients because tremors can now be immediately abolished without requiring surgical incisions or anesthesia. The therapeutic promise of VIM FUSA lies in the use of subthreshold testing to physiologically map the stereotactic target before permanent ablation.1 This technique delivers low-energy ultrasound beams to the proposed stereotactic target, and clinicians perform frequent clinical testing to detect any side effects or reduction in tremors. If tremor relief is detected without any side effects, the ultrasound energy is then increased in a stepwise manner to deliver the therapeutic ablation and make the clinical effects permanent. This technique mirrors the intraoperative clinical testing during deep brain stimulation surgery, in which repeated electrical stimulations at varying thresholds allow a physiological exploration of the stereotactic target and its adjacent anatomy. Intraoperative testing during deep brain stimulation is highly reliable in predicting postoperative outcomes.32 Unlike electrical stimulation, however, intraoperative testing during VIM FUSA is not as reliable. We reported that intraoperative tremor testing consistently overestimated long-term tremor relief, and patients experienced a 20% worsening in their tremors within the first 3 months after VIM FUSA.4 While exploring the mechanisms underlying this inaccuracy, we discovered that the intraoperative clinical effects of VIM FUSA are not only derived from tissue ablation alone but also represent a combined effect of graded ultrasound exposure, which simultaneously generates VIM tissue ablation, partial ablation, and thermal neuromodulation.6 We showed that during VIM FUSA, the center of the thermal spot received an ablative thermal dose (i.e., ≥ 240 CEMs). Toward the spot periphery, the dose decrease was sharp; still, the tissue rim surrounding ablation was exposed to a thermal dose sufficient to cause partial ablation (25–240 CEMs). Interestingly, another concentric rim of tissue was simultaneously exposed to a thermal dose sufficient to inactivate the VIM tissue but not cause any tissue destruction (i.e., < 25 CEMs, or thermal neuromodulation).33 This inaccuracy in intraoperative clinical testing causes variability in the current technique of VIM FUSA.3 For example, in a multicenter study, the reported number of sonications varied from 7 to 22, and the technique was surgeon- and experience-dependent. Given this discrepancy, it becomes paramount to develop robust and reliable intraoperative feedback to standardize the VIM FUSA technique. Intraoperative VIM FUSA lesion imaging therefore remains critical for clinical decision-making during VIM FUSA.

Intraoperative Lesion Imaging and Its Limitations

In addition to clinical testing, the current VIM FUSA technique also relies on MR thermography to provide live feedback of the tissue ablation. Thermography is based on proton shift imaging, and it measures temperature change with excellent thermal accuracy, but the anatomical location of the thermal spot is inaccurate because of two main reasons.3436 First, the intraoperative thermography acquisition is 2D, and it also suffers from shifts in the frequency-encoding direction. Ultimately, thermography is an indirect technique to measure the temperature change, and therefore does not provide direct imaging of tissue response after FUSA. In a quest to determine direct tissue response, several groups performed postsurgical imaging studies. The imaging protocols included T1-, T2-, and susceptibility-weighted imaging to define the lesion volume and location and associate the lesion characteristics with clinical outcomes.8,1315,17,19,20,37 T1- and T2-weighted sequences were found to be relatively inaccurate in measuring the lesion volume and, like our results, were highly timing-dependent. A few studies have also tested the feasibility of acquiring intraoperative imaging during VIM FUSA.17,22 These studies confirmed its feasibility but did not test how intraoperative imaging compared to delayed imaging and whether it could predict delayed clinical outcomes. To overcome some of these limitations, we became interested in the opportunities offered by RDI to characterize VIM FUSA lesions.20 RDI estimation is based on GQI for model-free analysis of intracellular water diffusivity by eliminating the free water effect associated with tissue edema after VIM FUSA.38 RDI proved useful in identifying tissue necrosis and differentiating it from the immediate tissue edema in biological tissues,39 making it ideal for clinical translation to VIM FUSA. We showed that RDI differentiated postoperative VIM FUSA lesions and reliably predicted clinical outcomes at 1 year (sensitivity = 77.3%, specificity = 66.1%).20 These data prompted us to determine whether intraoperative RDI could detect VIM FUSA lesion volume and location. Based on this intraoperative testing, we showed that RDI can detect intraoperative lesions and provide clinically relevant information. Future research should test whether RDI can be developed into a live or real-time feedback of in vivo tissue response for optimizing VIM FUSA technique.

Intraoperative RDI: Implications for the VIM FUSA Technique

We discovered that RDI lesions were more extensive than those revealed by intraoperative thermography and remain stable even at 1 week after VIM FUSA. There can be two explanations for this finding: 1) RDI overestimated the lesion volume, or 2) thermography underestimated the lesion volume. The latter is the more likely explanation because intraoperative thermography is 2D and limited to a single slice acquisition (approximate 3-mm thickness) and lacks the ability to fully reveal the lesion extension. In addition, although a 240-CEM thermal dose consistently ablates brain tissue, the tissue’s sensitivity to thermal ablation is specific to factors such as blood flow (lower blood flow causes less heat dissipation), which can cause lesions to extend beyond the 240-CEM envelope. In the context of VIM FUSA specifically, the white matter surrounding the VIM potentially requires a lower thermal dose to the lesion than the VIM itself because of a lower blood supply in the white matter. The tissue specificity of ablation threshold can create a discrepancy between estimated and actual lesion volumes (i.e., actual lesion volume can be higher than the estimated lesion volume by thermography). Others have reported that a lower thermal dose threshold, specifically 200 CEMs or higher, was significantly associated with postoperative lesions.9,4042 Therefore, neurosurgeons should be aware that the FUSA lesions can extend beyond the 240-CEM dose envelope displayed on the treatment console and should be cautious while ablating in the proximity of VIM borders, specifically the inferior and lateral borders. One strategy to avoid lesion extension beyond the VIM boundaries is to use tractography to visualize the target.4,26,4348 A recent meta-analysis reported that the risk of ataxia was significantly reduced with the use of tractography-based targeting.5 We implemented tractography for VIM targeting and still observed postoperative ataxia in 4 patients. The risk of ataxia underscores the need to simultaneously visualize tissue ablation relative to the VIM target during VIM FUSA. We show the preliminary feasibility of using RDI to detect intraoperative lesions and identify clinically relevant lesion locations. Future work is required to test whether RDI can be developed to guide intraoperative decision-making. We envision that RDI can be potentially implemented in the FUSA workflow during the later stages of the procedure when therapeutic sonications (51°C or higher) are delivered. Each therapeutic sonication is followed by a cooling phase, which lasts approximately 2–6 minutes. Because the RDI sequence implemented in this research takes about 2–3 minutes, it can be acquired during the cooling phase to characterize the tissue response and accurately calculate the lesion volume and location. In the next phase, we plan to acquire RDI and optimize it in the presence of an ultrasound transducer and the head frame. The utility of this approach in guiding intraoperative decision-making will then be determined. In the interim, our findings support a cautious approach to ablate near the inferolateral VIM border. To reduce lesion extension beyond the inferior VIM border, neurosurgeons could choose the ablation target above the anterior commissure–posterior commissure plane because FUSA thermal spots are elongated in the superoinferior axis and can extend into the subthalamic white matter. Filtered masks can be another option to avoid an inadvertent mediolateral spread causing a corticospinal tract ablation. Finally, short-duration sonications can be used to reduce heat dissipation into a larger tissue volume. Future research should test whether these strategies can reduce the risk of postoperative ataxia.

Conclusions

We found that intraoperative RDI accurately identified the volume and location of VIM FUSA lesions. Intraoperative T2-weighted imaging underestimated the lesion volume but accurately identified the location. Intraoperative RDI revealed that lesions adjacent to the ventral VIM border were significantly associated with tremor improvement. In contrast, lesions extending into the inferolateral white matter were associated with the development of postoperative ataxia. These data support the use of intraoperative RDI to characterize focused ultrasound lesions. Future research should determine the histological correlates of intraoperative RDI change and test whether it can be developed into an intraoperative feedback to optimize the VIM FUSA treatment technique.

Disclosures

The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Author Contributions

Conception and design: Krishna. Acquisition of data: all authors. Analysis and interpretation of data: all authors. Drafting the article: Krishna, Sammartino. Critically revising the article: all authors. Reviewed submitted version of manuscript: Krishna. Approved the final version of the manuscript on behalf of all authors: Krishna. Statistical analysis: Krishna, Sammartino. Administrative/technical/material support: Krishna. Study supervision: Krishna.

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    • Export Citation
  • 9

    Hynynen K, Vykhodtseva NI, Chung AH, Sorrentino V, Colucci V, Jolesz FA. Thermal effects of focused ultrasound on the brain: determination with MR imaging. Radiology. 1997;204(1):247253.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Vykhodtseva N, Sorrentino V, Jolesz FA, Bronson RT, Hynynen K. MRI detection of the thermal effects of focused ultrasound on the brain. Ultrasound Med Biol. 2000;26(5):871880.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Kuroda K, Chung AH, Hynynen K, Jolesz FA. Calibration of water proton chemical shift with temperature for noninvasive temperature imaging during focused ultrasound surgery. J Magn Reson Imaging. 1998;8(1):175181.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Bond AE, Elias WJ. Predicting lesion size during focused ultrasound thalamotomy: a review of 63 lesions over 3 clinical trials. Neurosurg Focus. 2018;44(2):E5.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Elias WJ, Huss D, Voss T, Loomba J, Khaled M, Zadicario E, et al. A pilot study of focused ultrasound thalamotomy for essential tremor. N Engl J Med. 2013;369(7):640648.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Lipsman N, Schwartz ML, Huang Y, Lee L, Sankar T, Chapman M, et al. MR-guided focused ultrasound thalamotomy for essential tremor: a proof-of-concept study. Lancet Neurol. 2013;12(5):462468.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Chang WS, Jung HH, Kweon EJ, Zadicario E, Rachmilevitch I, Chang JW. Unilateral magnetic resonance guided focused ultrasound thalamotomy for essential tremor: practices and clinicoradiological outcomes. J Neurol Neurosurg Psychiatry. 2015;86(3):257264.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Pineda-Pardo JA, Urso D, Martínez-Fernández R, Rodríguez-Rojas R, Del-Alamo M, Millar Vernetti P, et al. Transcranial magnetic resonance-guided focused ultrasound thalamotomy in essential tremor: a comprehensive lesion characterization. Neurosurgery. 2020;87(2):256265.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Gagliardo C, Cannella R, Quarrella C, D’Amelio M, Napoli A, Bartolotta TV, et al. Intraoperative imaging findings in transcranial MR imaging-guided focused ultrasound treatment at 1.5T may accurately detect typical lesional findings correlated with sonication parameters. Eur Radiol. 2020;30(9):50595070.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Jung HH, Chang WS, Rachmilevitch I, Tlusty T, Zadicario E, Chang JW. Different magnetic resonance imaging patterns after transcranial magnetic resonance-guided focused ultrasound of the ventral intermediate nucleus of the thalamus and anterior limb of the internal capsule in patients with essential tremor or obsessive-compulsive disorder. J Neurosurg. 2015;122(1):162168.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Keil VC, Borger V, Purrer V, Groetz SF, Scheef L, Boecker H, et al. MRI follow-up after magnetic resonance-guided focused ultrasound for non-invasive thalamotomy: the neuroradiologist’s perspective. Neuroradiology. 2020;62(9):11111122.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Sammartino F, Yeh FC, Krishna V. Longitudinal analysis of structural changes following unilateral focused ultrasound thalamotomy. Neuroimage Clin. 2019;22:101754.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Walker MR, Zhong J, Waspe AC, Looi T, Piorkowska K, Hawkins C, et al. Acute MR-guided high-intensity focused ultrasound lesion assessment using diffusion-weighted imaging and histological analysis. Front Neurol. 2019;10:1069.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Levi Chazen J, Stradford T, Kaplitt MG. Cranial MR-guided focused ultrasound for essential tremor: technical considerations and image guidance. Clin Neuroradiol. 2019;29(2):351357.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23

    Sammartino F, Krishna V, King NKK, Lozano AM, Schwartz ML, Huang Y, Hodaie M. Tractography-based ventral intermediate nucleus targeting: Novel methodology and intraoperative validation. Mov Disord. 2016;31(8):12171225.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24

    Li X, Morgan PS, Ashburner J, Smith J, Rorden C. The first step for neuroimaging data analysis: DICOM to NIfTI conversion. J Neurosci Methods. 2016;264:4756.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    Avants BB, Tustison N, Song G. Advanced normalization tools (ANTS). Insight J. 2009;2(365):135.

  • 26

    Exablate Neuro. Insightec.com. Accessed October 18, 2021. https://www.insightec.com/exablate-neuro/

  • 27

    Elias WJ, Khaled M, Hilliard JD, Aubry JF, Frysinger RC, Sheehan JP, et al. A magnetic resonance imaging, histological, and dose modeling comparison of focused ultrasound, radiofrequency, and Gamma Knife radiosurgery lesions in swine thalamus. J Neurosurg. 2013;119(2):307317.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, Müller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12(1):77.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143(1):2936.

  • 30

    Yeh FC, Panesar S, Fernandes D, Meola A, Yoshino M, Fernandez-Miranda JC, et al. Population-averaged atlas of the macroscale human structural connectome and its network topology. Neuroimage. 2018;178:5768.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    Ravikumar VK, Parker JJ, Hornbeck TS, Santini VE, Pauly KB, Wintermark M, et al. Cost-effectiveness of focused ultrasound, radiosurgery, and DBS for essential tremor. Mov Disord. 2017;32(8):11651173.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32

    Sammartino F, Rege R, Krishna V. Reliability of intraoperative testing during deep brain stimulation surgery. Neuromodulation. 2020;23(4):525529.

  • 33

    Foley JL, Little JW, Vaezy S. Image-guided high-intensity focused ultrasound for conduction block of peripheral nerves. Ann Biomed Eng. 2007;35(1):109119.

  • 34

    Yuan J, Mei CS, Panych LP, McDannold NJ, Madore B. Towards fast and accurate temperature mapping with proton resonance frequency-based MR thermometry. Quant Imaging Med Surg. 2012;2(1):2132.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35

    Clarke RL, ter Haar GR. Temperature rise recorded during lesion formation by high-intensity focused ultrasound. Ultrasound Med Biol. 1997;23(2):299306.

  • 36

    Vimeux FC, De Zwart JA, Palussiére J, Fawaz R, Delalande C, Canioni P, et al. Real-time control of focused ultrasound heating based on rapid MR thermometry. Invest Radiol. 1999;34(3):190193.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37

    Chang JW, Park CK, Lipsman N, Schwartz ML, Ghanouni P, Henderson JM, et al. A prospective trial of magnetic resonance-guided focused ultrasound thalamotomy for essential tremor: results at the 2-year follow-up. Ann Neurol. 2018;83(1):107114.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Yeh FC, Wedeen VJ, Tseng WY. Generalized q-sampling imaging. IEEE Trans Med Imaging. 2010;29(9):16261635.

  • 39

    Yeh FC, Liu L, Hitchens TK, Wu YL. Mapping immune cell infiltration using restricted diffusion MRI. Magn Reson Med. 2017;77(2):603612.

  • 40

    Huang Y, Lipsman N, Schwartz ML, Krishna V, Sammartino F, Lozano AM, Hynynen K. Predicting lesion size by accumulated thermal dose in MR-guided focused ultrasound for essential tremor. Med Phys. 2018;45(10):47044710.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41

    Lyons BE, Obana WG, Borcich JK, Kleinman R, Singh D, Britt RH. Chronic histological effects of ultrasonic hyperthermia on normal feline brain tissue. Radiat Res. 1986;106(2):234251.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Dewey WC. Arrhenius relationships from the molecule and cell to the clinic. Int J Hyperthermia. 2009;25(1):320.

  • 43

    Weidman EK, Kaplitt MG, Strybing K, Chazen JL. Repeat magnetic resonance imaging-guided focused ultrasound thalamotomy for recurrent essential tremor: case report and review of MRI findings. J Neurosurg. 2020;132(1):211216.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44

    Tsolaki E, Downes A, Speier W, Elias WJ, Pouratian N. The potential value of probabilistic tractography-based for MR-guided focused ultrasound thalamotomy for essential tremor. Neuroimage Clin. 2017;17:10191027.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45

    Tian Q, Wintermark M, Jeffrey Elias W, Ghanouni P, Halpern CH, Henderson JM, et al. Diffusion MRI tractography for improved transcranial MRI-guided focused ultrasound thalamotomy targeting for essential tremor. Neuroimage Clin. 2018;19:572580.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46

    Schreglmann SR, Bauer R, Hägele-Link S, Bhatia KP, Natchev P, Wegener N, et al. Unilateral cerebellothalamic tract ablation in essential tremor by MRI-guided focused ultrasound. Neurology. 2017;88(14):13291333.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47

    Chazen JL, Sarva H, Stieg PE, Min RJ, Ballon DJ, Pryor KO, et al. Clinical improvement associated with targeted interruption of the cerebellothalamic tract following MR-guided focused ultrasound for essential tremor. J Neurosurg. 2018;129(2):315323.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48

    Miller TR, Zhuo J, Eisenberg HM, Fishman PS, Melhem ER, Gullapalli R, Gandhi D. Targeting of the dentato-rubro-thalamic tract for MR-guided focused ultrasound treatment of essential tremor. Neuroradiol J. 2019;32(6):401407.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Collapse
  • Expand

Images from Minchev et al. (pp 479–488).

  • FIG. 1.

    Bar graph comparing lesion volumes between intra- and postoperative imaging. *p < 0.05, **p < 0.01, ***p < 0.001. T2w = T2-weighted. Figure is available in color online only.

  • FIG. 2.

    Lesion characterization with intra- and postoperative imaging in a representative patient: intraoperative thermography (A), intraoperative RDI (B), postoperative RDI (C), intraoperative T2-weighted sequence (D), and postoperative T2-weighted sequence (E). Figure is available in color online only.

  • FIG. 3.

    Bar graph comparing target coverage between intra- and postoperative imaging. *p < 0.05, **p < 0.01, ***p < 0.001. TVIM = tractography-defined VIM. Figure is available in color online only.

  • FIG. 4.

    Lesion locations significantly associated with postoperative tremor relief (green) and ataxia (red) revealed by intraoperative RDI. Figure is available in color online only.

  • 1

    Krishna V, Sammartino F, Rezai A. A review of the current therapies, challenges, and future directions of transcranial focused ultrasound technology: advances in diagnosis and treatment. JAMA Neurol. 2018;75(2):246254.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    Elias WJ, Lipsman N, Ondo WG, Ghanouni P, Kim YG, Lee W, et al. A randomized trial of focused ultrasound thalamotomy for essential tremor. N Engl J Med. 2016;375(8):730739.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3

    Krishna V, Sammartino F, Cosgrove R, Ghanouni P, Schwartz M, Gwinn R, et al. Predictors of outcomes after focused ultrasound thalamotomy. Neurosurgery. 2020;87(2):229237.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    Krishna V, Sammartino F, Agrawal P, Changizi BK, Bourekas E, Knopp MV, Rezai A. Prospective tractography-based targeting for improved safety of focused ultrasound thalamotomy. Neurosurgery. 2019;84(1):160168.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    Agrawal M, Garg K, Samala R, Rajan R, Naik V, Singh M. Outcome and complications of MR guided focused ultrasound for essential tremor: a systematic review and meta-analysis. Front Neurol. 2021;12:654711.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Sammartino F, Snell J, Eames M, Krishna V. Thermal neuromodulation with focused ultrasound: implications for the technique of subthreshold testing. Neurosurgery. 2021;89(4):610616.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Fishman PS, Elias WJ, Ghanouni P, Gwinn R, Lipsman N, Schwartz M, et al. Neurological adverse event profile of magnetic resonance imaging-guided focused ultrasound thalamotomy for essential tremor. Mov Disord. 2018;33(5):843847.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Boutet A, Ranjan M, Zhong J, Germann J, Xu D, Schwartz ML, et al. Focused ultrasound thalamotomy location determines clinical benefits in patients with essential tremor. Brain. 2018;141(12):34053414.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    Hynynen K, Vykhodtseva NI, Chung AH, Sorrentino V, Colucci V, Jolesz FA. Thermal effects of focused ultrasound on the brain: determination with MR imaging. Radiology. 1997;204(1):247253.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Vykhodtseva N, Sorrentino V, Jolesz FA, Bronson RT, Hynynen K. MRI detection of the thermal effects of focused ultrasound on the brain. Ultrasound Med Biol. 2000;26(5):871880.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Kuroda K, Chung AH, Hynynen K, Jolesz FA. Calibration of water proton chemical shift with temperature for noninvasive temperature imaging during focused ultrasound surgery. J Magn Reson Imaging. 1998;8(1):175181.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Bond AE, Elias WJ. Predicting lesion size during focused ultrasound thalamotomy: a review of 63 lesions over 3 clinical trials. Neurosurg Focus. 2018;44(2):E5.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Elias WJ, Huss D, Voss T, Loomba J, Khaled M, Zadicario E, et al. A pilot study of focused ultrasound thalamotomy for essential tremor. N Engl J Med. 2013;369(7):640648.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Lipsman N, Schwartz ML, Huang Y, Lee L, Sankar T, Chapman M, et al. MR-guided focused ultrasound thalamotomy for essential tremor: a proof-of-concept study. Lancet Neurol. 2013;12(5):462468.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Chang WS, Jung HH, Kweon EJ, Zadicario E, Rachmilevitch I, Chang JW. Unilateral magnetic resonance guided focused ultrasound thalamotomy for essential tremor: practices and clinicoradiological outcomes. J Neurol Neurosurg Psychiatry. 2015;86(3):257264.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Pineda-Pardo JA, Urso D, Martínez-Fernández R, Rodríguez-Rojas R, Del-Alamo M, Millar Vernetti P, et al. Transcranial magnetic resonance-guided focused ultrasound thalamotomy in essential tremor: a comprehensive lesion characterization. Neurosurgery. 2020;87(2):256265.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Gagliardo C, Cannella R, Quarrella C, D’Amelio M, Napoli A, Bartolotta TV, et al. Intraoperative imaging findings in transcranial MR imaging-guided focused ultrasound treatment at 1.5T may accurately detect typical lesional findings correlated with sonication parameters. Eur Radiol. 2020;30(9):50595070.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Jung HH, Chang WS, Rachmilevitch I, Tlusty T, Zadicario E, Chang JW. Different magnetic resonance imaging patterns after transcranial magnetic resonance-guided focused ultrasound of the ventral intermediate nucleus of the thalamus and anterior limb of the internal capsule in patients with essential tremor or obsessive-compulsive disorder. J Neurosurg. 2015;122(1):162168.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Keil VC, Borger V, Purrer V, Groetz SF, Scheef L, Boecker H, et al. MRI follow-up after magnetic resonance-guided focused ultrasound for non-invasive thalamotomy: the neuroradiologist’s perspective. Neuroradiology. 2020;62(9):11111122.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Sammartino F, Yeh FC, Krishna V. Longitudinal analysis of structural changes following unilateral focused ultrasound thalamotomy. Neuroimage Clin. 2019;22:101754.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Walker MR, Zhong J, Waspe AC, Looi T, Piorkowska K, Hawkins C, et al. Acute MR-guided high-intensity focused ultrasound lesion assessment using diffusion-weighted imaging and histological analysis. Front Neurol. 2019;10:1069.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Levi Chazen J, Stradford T, Kaplitt MG. Cranial MR-guided focused ultrasound for essential tremor: technical considerations and image guidance. Clin Neuroradiol. 2019;29(2):351357.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23

    Sammartino F, Krishna V, King NKK, Lozano AM, Schwartz ML, Huang Y, Hodaie M. Tractography-based ventral intermediate nucleus targeting: Novel methodology and intraoperative validation. Mov Disord. 2016;31(8):12171225.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24

    Li X, Morgan PS, Ashburner J, Smith J, Rorden C. The first step for neuroimaging data analysis: DICOM to NIfTI conversion. J Neurosci Methods. 2016;264:4756.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    Avants BB, Tustison N, Song G. Advanced normalization tools (ANTS). Insight J. 2009;2(365):135.

  • 26

    Exablate Neuro. Insightec.com. Accessed October 18, 2021. https://www.insightec.com/exablate-neuro/

  • 27

    Elias WJ, Khaled M, Hilliard JD, Aubry JF, Frysinger RC, Sheehan JP, et al. A magnetic resonance imaging, histological, and dose modeling comparison of focused ultrasound, radiofrequency, and Gamma Knife radiosurgery lesions in swine thalamus. J Neurosurg. 2013;119(2):307317.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, Müller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12(1):77.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143(1):2936.

  • 30

    Yeh FC, Panesar S, Fernandes D, Meola A, Yoshino M, Fernandez-Miranda JC, et al. Population-averaged atlas of the macroscale human structural connectome and its network topology. Neuroimage. 2018;178:5768.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    Ravikumar VK, Parker JJ, Hornbeck TS, Santini VE, Pauly KB, Wintermark M, et al. Cost-effectiveness of focused ultrasound, radiosurgery, and DBS for essential tremor. Mov Disord. 2017;32(8):11651173.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32

    Sammartino F, Rege R, Krishna V. Reliability of intraoperative testing during deep brain stimulation surgery. Neuromodulation. 2020;23(4):525529.

  • 33

    Foley JL, Little JW, Vaezy S. Image-guided high-intensity focused ultrasound for conduction block of peripheral nerves. Ann Biomed Eng. 2007;35(1):109119.

  • 34

    Yuan J, Mei CS, Panych LP, McDannold NJ, Madore B. Towards fast and accurate temperature mapping with proton resonance frequency-based MR thermometry. Quant Imaging Med Surg. 2012;2(1):2132.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35

    Clarke RL, ter Haar GR. Temperature rise recorded during lesion formation by high-intensity focused ultrasound. Ultrasound Med Biol. 1997;23(2):299306.

  • 36

    Vimeux FC, De Zwart JA, Palussiére J, Fawaz R, Delalande C, Canioni P, et al. Real-time control of focused ultrasound heating based on rapid MR thermometry. Invest Radiol. 1999;34(3):190193.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37

    Chang JW, Park CK, Lipsman N, Schwartz ML, Ghanouni P, Henderson JM, et al. A prospective trial of magnetic resonance-guided focused ultrasound thalamotomy for essential tremor: results at the 2-year follow-up. Ann Neurol. 2018;83(1):107114.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Yeh FC, Wedeen VJ, Tseng WY. Generalized q-sampling imaging. IEEE Trans Med Imaging. 2010;29(9):16261635.

  • 39

    Yeh FC, Liu L, Hitchens TK, Wu YL. Mapping immune cell infiltration using restricted diffusion MRI. Magn Reson Med. 2017;77(2):603612.

  • 40

    Huang Y, Lipsman N, Schwartz ML, Krishna V, Sammartino F, Lozano AM, Hynynen K. Predicting lesion size by accumulated thermal dose in MR-guided focused ultrasound for essential tremor. Med Phys. 2018;45(10):47044710.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41

    Lyons BE, Obana WG, Borcich JK, Kleinman R, Singh D, Britt RH. Chronic histological effects of ultrasonic hyperthermia on normal feline brain tissue. Radiat Res. 1986;106(2):234251.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Dewey WC. Arrhenius relationships from the molecule and cell to the clinic. Int J Hyperthermia. 2009;25(1):320.

  • 43

    Weidman EK, Kaplitt MG, Strybing K, Chazen JL. Repeat magnetic resonance imaging-guided focused ultrasound thalamotomy for recurrent essential tremor: case report and review of MRI findings. J Neurosurg. 2020;132(1):211216.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44

    Tsolaki E, Downes A, Speier W, Elias WJ, Pouratian N. The potential value of probabilistic tractography-based for MR-guided focused ultrasound thalamotomy for essential tremor. Neuroimage Clin. 2017;17:10191027.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45

    Tian Q, Wintermark M, Jeffrey Elias W, Ghanouni P, Halpern CH, Henderson JM, et al. Diffusion MRI tractography for improved transcranial MRI-guided focused ultrasound thalamotomy targeting for essential tremor. Neuroimage Clin. 2018;19:572580.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46

    Schreglmann SR, Bauer R, Hägele-Link S, Bhatia KP, Natchev P, Wegener N, et al. Unilateral cerebellothalamic tract ablation in essential tremor by MRI-guided focused ultrasound. Neurology. 2017;88(14):13291333.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47

    Chazen JL, Sarva H, Stieg PE, Min RJ, Ballon DJ, Pryor KO, et al. Clinical improvement associated with targeted interruption of the cerebellothalamic tract following MR-guided focused ultrasound for essential tremor. J Neurosurg. 2018;129(2):315323.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48

    Miller TR, Zhuo J, Eisenberg HM, Fishman PS, Melhem ER, Gullapalli R, Gandhi D. Targeting of the dentato-rubro-thalamic tract for MR-guided focused ultrasound treatment of essential tremor. Neuroradiol J. 2019;32(6):401407.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

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