Targeting for stereotactic radiosurgical thalamotomy based on tremor treatment response

Guozhen LuoDepartments of Radiation Oncology,

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Brent D. CameronDepartments of Radiation Oncology,

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Li WangBiostatistics, and

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Hong YuNeurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee;

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Joseph S. NeimatDepartment of Neurological Surgery, University of Louisville, Kentucky; and

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Peter HederaDepartment of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee

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Fenna PhibbsDepartment of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee

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Elise B. BradleyDepartment of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee

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Anthony J. CmelakDepartments of Radiation Oncology,

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Austin N. KirschnerDepartments of Radiation Oncology,

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OBJECTIVE

Stereotactic radiosurgery (SRS) treats severe, medically refractory essential tremor and tremor-dominant Parkinson disease. However, the optimal target for SRS treatment within the thalamic ventral intermediate nucleus (VIM) is not clearly defined. This work evaluates the precision of the physician-selected VIM target, and determines the optimal SRS target within the VIM by correlation between early responders and nonresponders.

METHODS

Early responders and nonresponders were assessed retrospectively by Elements Basal Ganglia Atlas autocontouring of the VIM on the pre–SRS-treatment 1-mm slice thickness T1-weighted MRI and correlating the center of the post–SRS-treatment lesion. Using pre- and posttreatment diffusion tensor imaging, the fiber tracking package in the Elements software generated tremor-related tracts from autosegmented motor cortex, thalamus, red nucleus, and dentate nucleus. Autocontouring of the VIM was successful for all patients.

RESULTS

Among 23 patients, physician-directed SRS targets had a medial–lateral target range from +2.5 mm to −2.0 mm from the VIM center. Relative to the VIM center, the SRS isocenter target was 0.7–0.9 mm lateral for 6 early responders and 0.9–1.1 mm medial for 4 nonresponders (p = 0.019), and without differences in the other dimensions: 0.2 mm posterior and 0.6 mm superior. Dose–volume histogram analyses for the VIM had no significant differences between responders and nonresponders between 20 Gy and 140 Gy, mean or maximum dose, and dose to small volumes. Tractography data was obtained for 4 patients.

CONCLUSIONS

For tremor control in early responders, the Elements Basal Ganglia Atlas autocontour for the VIM provides the optimal SRS target location that is 0.7–0.9 mm lateral to the VIM center.

ABBREVIATIONS

AC = anterior commissure; DBS = deep brain stimulation; DRTT = dentato-rubro-thalamic tract; DTI = diffusion tensor imaging; DVH = dose–volume histogram; ET = essential tremor; FA = fractional anisotropy; FTM = Fahn-Tolosa-Marin; GKS = Gamma Knife surgery; IQR = interquartile range; LINAC = linear accelerator; PC = posterior commissure; QUEST = Quality of Life in Essential Tremor Questionnaire; SRS = stereotactic radiosurgery; VIM = ventral intermediate nucleus of the thalamus.

OBJECTIVE

Stereotactic radiosurgery (SRS) treats severe, medically refractory essential tremor and tremor-dominant Parkinson disease. However, the optimal target for SRS treatment within the thalamic ventral intermediate nucleus (VIM) is not clearly defined. This work evaluates the precision of the physician-selected VIM target, and determines the optimal SRS target within the VIM by correlation between early responders and nonresponders.

METHODS

Early responders and nonresponders were assessed retrospectively by Elements Basal Ganglia Atlas autocontouring of the VIM on the pre–SRS-treatment 1-mm slice thickness T1-weighted MRI and correlating the center of the post–SRS-treatment lesion. Using pre- and posttreatment diffusion tensor imaging, the fiber tracking package in the Elements software generated tremor-related tracts from autosegmented motor cortex, thalamus, red nucleus, and dentate nucleus. Autocontouring of the VIM was successful for all patients.

RESULTS

Among 23 patients, physician-directed SRS targets had a medial–lateral target range from +2.5 mm to −2.0 mm from the VIM center. Relative to the VIM center, the SRS isocenter target was 0.7–0.9 mm lateral for 6 early responders and 0.9–1.1 mm medial for 4 nonresponders (p = 0.019), and without differences in the other dimensions: 0.2 mm posterior and 0.6 mm superior. Dose–volume histogram analyses for the VIM had no significant differences between responders and nonresponders between 20 Gy and 140 Gy, mean or maximum dose, and dose to small volumes. Tractography data was obtained for 4 patients.

CONCLUSIONS

For tremor control in early responders, the Elements Basal Ganglia Atlas autocontour for the VIM provides the optimal SRS target location that is 0.7–0.9 mm lateral to the VIM center.

In Brief

Researchers studied patients with severe essential tremor and parkinsonian tremor who were treated by linear accelerator–based stereotactic radiosurgery to stop the malfunctioning site in the brain. By comparing early responders to nonresponders, a detailed neuroanatomy atlas using patient-specific MRI series revealed the critical importance of extremely precise targeting within the brain. This work can guide neurosurgery and radiotherapy practices to improve targeting and enhance the success of stereotactic radiosurgical thalamotomy for the treatment of severe tremor.

Essential tremor (ET) afflicts 5% of people and can worsen over decades to become debilitating. Severe, medication-refractory ET is often treated by deep brain stimulation (DBS), which allows real-time tremor assessment to help determine the optimal position for the electrode. Nevertheless, uncertainty remains about the optimal location, parameters, and mechanism for DBS treatment.1–3 For patients who prefer a noninvasive treatment or who are ineligible for DBS, stereotactic radiosurgery (SRS) is an alternative, standard-of-care ablative treatment.

SRS involves focusing a very high dose of high-energy ionizing radiation on the part of the brain involved in tremor generation to permanently ablate the tissue. The SRS target is the ventral intermediate nucleus (VIM), which is a region of the thalamus that is difficult to visualize on a clinical brain MR image. Gamma Knife surgery (GKS) is a standard approach to perform SRS, which typically uses a hard frame affixed to the skull and requires several hours for the treatment, depending on the 60Co source strength.4–6 In recent years, linear accelerators (LINACs) have become more readily available and have SRS capability through specialized equipment, on-board imaging, and immobilization techniques that can provide submillimeter accuracy.7–10

Frameless LINAC-based SRS thalamotomy has been performed at our facility since 2012, generating one of the largest single-institution experiences. We previously showed in end-to-end analysis in patients that the 3D alignment accuracy was 1.1 mm and provided submillimeter accuracy within each axis.7 An interim analysis of our clinical results shows success comparable to GKS, with approximately 80% of patients showing objective clinical improvement.11 Multiple published GKS case series show that 10%–25% of patients have an inadequate response.12–15 A likely reason for this lack of efficacy is target inaccuracy. The thalamic VIM target is based on anatomical measurements and these vary within a range of several millimeters among the published case series, typically determined by the neurosurgeon’s and radiation oncologist’s experience based on Schaltenbrand atlas coordinates.16 We hypothesize that the precise target isocenter position within the VIM correlates with response to treatment. We further hypothesize that an optimal target selection based on individual anatomical detail will correlate with good treatment response and provide a more consistent targeting system that will improve the reliability of clinical outcomes.

Responses to SRS typically occur during the first 12 months after treatment and are stable for years.5,13 In this project, we sought to determine the ideal target location within the VIM by using an automated neuroanatomy contouring system. We retrospectively studied early clinical responders showing significant improvement at 3 months and compared them to nonresponders whose tremor did not improve during 12 months after SRS. We determined the relationship between the autocontoured VIM structure and the target isocenter location, including the posttreatment brain lesion seen on MRI. We also investigated the potential implementation of diffusion tensor imaging (DTI) MRI to assist in finding the optimal target location, as well as study the impact of SRS on the white matter tracts that are involved in the generation of tremor.

Methods

SRS was performed using the Novalis Tx (Varian) LINAC. The treatment target was identified by a single neurosurgeon (J.S.N. or H.Y.) and verified by a single radiation oncologist (A.J.C. or A.N.K.). The target location was selected by an atlas-based coordinate system derived from the Schaltenbrand atlas,16 further refined from an in-house database of patients receiving deep brain stimulator implantations with good response, and manually adjusted by the neurosurgeon and radiation oncologist. The in-house database was created by deep brain stimulator implantation imaging fused to MR images with a system-selected, best matching anatomy. The location of the active electrode was used as the treatment target. The target location is expressed in the axial system aligning the anterior commissure and posterior commissure in a single plane. The target is typically 6 mm anterior to the posterior commissure, 11 mm lateral from the third ventricle wall, and 4 mm superior. The coordinate system (X, Y, Z) is defined with the patient’s head in a neutral head holder (“A style” for men and “B style” for women [Silverman, Civco]), wearing a custom-fit thermoplastic head SRS mask (#F706B; Innovative Oncology Solutions).

All patients were treated with 145- to 160-Gy maximum point dose using noninvasive thermoplastic SRS mask–based immobilization; 0.75-mm thickness CT simulation (resolution 512 × 512) on a Philips Brilliance Big-Bore scanner (Philips); 3D high-resolution T1-weighted brain MRI (voxel size 0.5 mm × 0.5 mm × 1 mm); iPlan treatment planning software (Brainlab AG); the Novalis Tx LINAC with 4-mm circular cone applicator; and ExacTrac stereoscopic kV imaging performed at every table angle with treatment alignment tolerances of 0.5-mm translational and 0.5° rotational.7 The ExacTrac isocenter is calibrated to be within 0.3 mm to radiation isocenter of the LINAC based on the Winston-Lutz test.7

Patients underwent assessments by quality of life questionnaires (Quality of Life in Essential Tremor Questionnaire [QUEST] or the 39-Item Parkinson Disease Questionnaire [i.e., the PDQ-39]) and objective tremor-rating assessment by the Fahn-Tolosa-Marin (FTM) scale at baseline (pretreatment) and 3 months after SRS.11,17–20 Compared to pretreatment baseline, early clinical responders were defined as patients who had improved at 3 months after SRS by at least 10 scale points in the following 4 items on the QUEST questionnaire: dominant hand tremor severity, writing ability, using a computer, and drinking liquids; and/or had improved ≥ 3 scale points in tremor rating severity in writing and pouring liquids on the FTM assessment. Nonresponders had no change in the QUEST and FTM assessments (0–2 scale points) at 3 months after SRS and did not improve by 12 months. Judging from these standards, 6 patients (cases 1, 2, 3, 5, 25, and 27) were early responders and 4 patients (cases 12, 13, 16, and 20) were nonresponders (Supplementary Table 1).

Elements software (Brainlab) was used to analyze all imaging, including CT and pre- and posttreatment MRI. The MRI scans were also processed with the Elements distortion correction cranial algorithm based on the MR–CT registration, and new MRI data sets with correction were generated. The VIM was autocontoured using the Elements Basal Ganglia Atlas (version 3.5.0.41 beta) on all uncorrected and corrected pretreatment MRI scans.

Pretreatment DTI sequences were available for the patients in cases 24–27, who underwent scanning with the Philips MRI scanner with 32 directions and a resolution of 2 mm × 2 mm × 2 mm. Relevant tracts were created by the fiber tracking package in the Elements software with deterministic algorithm. Research has shown that increased activity involving the dentato-rubro-thalamic tract (DRTT) plays an important role in tremor.21–23 The related regions of interest, including the unilateral motor cortex, thalamus, red nucleus, and contralateral dentate nucleus were autosegmented with the Elements Basal Ganglia Atlas software package, and then fiber tracking was performed with the following settings: minimum fractional anisotropy (FA) 0.2, minimum length 40 mm, and maximum angulation 90°.

Contours, image scans, and image registrations were exported from the Elements software to the Eclipse treatment planning system (Varian) to analyze dose–volume histogram (DVH) values. For the patients with high-resolution T1-weighted, Gd contrast–enhanced posttreatment MRI scans, the enhanced spherical region seen on the MRI scans was manually contoured as the posttreatment lesion and used as a validated surrogate of the treatment delivery location.7 The geometrical centers of the VIM autocontoured structure and the post-SRS lesion were determined in Eclipse.

Statistical analyses were performed using GraphPad Prism software. Values are reported as the mean ± SD, except where noted. Comparisons among data were by the nonparametric Mann-Whitney U-test using 2-sided tails with a p value significance cutoff of less than 5%.

Patients with medically refractory severe ET or tremor-dominant Parkinson disease were treated with SRS in clinical trial NCT01734122 at a single institution and data were analyzed in this retrospective study with permission of the Vanderbilt institutional review board, in accordance with the World Medical Association Declaration of Helsinki 2000. All subjects gave their consent to the study in accordance with the informed consent regulations of the institution.

Results

The Elements software was capable of analyzing the pretreatment MRI series from 23 patients with either ET or parkinsonian tremor in this study. The mean age was 77 years (range 58–90 years), median age 75.8 (11.4 IQR) years, male sex in 70% of patients, ET in 78%. Within the cohort, patient demographics showed no significant differences between 6 early-responding patients and 4 nonresponders, with median age 76.4 (12.8 IQR) years versus 81.8 (9.3 IQR) years (p = 0.32), male sex in 83% versus 75% (p = 0.81), and ET in 67% versus 75% (p = 0.78).

The patient-specific autocontour for the VIM was successfully generated on the pretreatment high-resolution T1-weighted native MRI series, as well as on the distortion-corrected MRI series. Among 23 patients studied, the VIM volume was 0.125 ± 0.020 cm3 (range 0.090–0.170 cm3), which did not differ significantly from the VIM volume of 0.129 ± 0.021 cm3 (range 0.091–0.179 cm3) on the distortion-corrected MR images (p = 0.55).

At 3 months after SRS, 15 patients had qualified MRI scans showing a lesion whose mean volume was 0.075 ± 0.049 cm3 (range 0.010–0.170 cm3) on native MR images, which did not differ significantly from the mean lesion volume of 0.080 ± 0.055 cm3 (range 0.008–0.18 cm3) on the distortion-corrected MR images (p = 0.65). Next, an analysis was performed for the overlapping volumes between the posttreatment SRS lesion and pretreatment VIM by registering pre- and posttreatment MRI scans. The SRS lesion intersects with 25.9% ± 13.9% of the VIM volume on the uncorrected MRI scans, which was not significantly different from the distortion-corrected MR images showing that the SRS lesion occupies 27.1% ± 16.4% of the VIM volume (p > 0.55). Fig. 1 shows the pretreatment VIM volume, the DRTT fiber tracked from DTI and the posttreatment lesion fused together for the patient in case 25, who was one of the early responders.

FIG. 1.
FIG. 1.

Autocontoured VIM and DRTT fiber. As a representative example, the autosegmented VIM (cyan line) and DRTT fiber (orange line) contoured using the pretreatment MRI scan are shown for early clinical responder patient in case 25. The pretreatment and 3-month posttreatment MRI scans are fused and the contours are displayed on the posttreatment T1-weighted MRI in axial (A), sagittal (B), and coronal (C) planes. The posttreatment lesion (light pink line) was manually contoured. Figure is available in color online only.

Reproducibility in the physician-derived SRS target isocenter was analyzed. Relative to the geometrical center of the VIM autocontour, the average treatment isocenter coordinates were 0.3 ± 0.2 mm lateral, 0.6 ± 0.3 mm anterior, and 0.1 ± 0.3 mm inferior (mean ± SEM). However, there was a large range of these relative coordinates, extending up to 2.5 mm laterally, 2.0 mm medially, 2.8 mm anteriorly, 2.4 mm posteriorly, 2.0 mm superiorly, and 2.5 mm inferiorly. The 3D distance for the relative position between the VIM center and the treatment isocenter was 2.0 mm on average, with a range of 3.3–0.6 mm. No statistically significant differences in relative coordinates were found between physicians. Analyses using the data from the distortion-corrected MRI series showed similar findings compared to the uncorrected MRI series (data not shown).

We hypothesized that early responders versus nonresponders may have differences related to the VIM. Data from 6 clinically early-responding patients and 4 nonresponding patients were compared. First, no significant differences were identified in autocontoured VIM volume, post–SRS-treatment lesion volume, and percentage of overlap between the two volumes. Next, the radiation dose coverage of the autocontoured VIM structure was studied. DVHs at 20-Gy dose increments between 20 Gy and 140 Gy were analyzed, as well as the dose to 0.1, 0.05, and 0.035 cm3; maximum point dose; and mean dose to the VIM structure. The dose to 0.1 cm3 of the autocontoured VIM is significantly higher in the responders (3002 cGy) than nonresponders (1986 cGy), for the native MRI data set (p = 0.04). The data are listed in Table 1.

TABLE 1.

Autocontoured VIM data for treatment responders and nonresponders

ParameterNative MRIp ValueDistortion-Corrected MRIp Value
Responders, n = 6Nonresponders, n = 4Responders, n = 6Nonresponders, n = 4
VIM vol in cm3 (range)0.133 ± 0.016 (0.114–0.150)0.131 ± 0.039 (0.097–0.170)>0.990.138 ± 0.016 (0.122–0.160)0.135 ± 0.037 (0.104–0.179)0.87
Post-Tx lesion vol in cm3 (range)0.081 ± 0.054 (0.010–0.170)0.065 ± 0.037 (0.020–0.109)0.760.084 ± 0.053 (0.008–0.17)0.067 ± 0.041 (0.022–0.114)0.76
% VIM overlap w/ post-Tx lesion26.8 ± 14.924.1 ± 12.20.9127.0 ± 16.623.7 ± 10.60.61
Max dose ± SD (cGy)15669 ± 29815884 ± 1240.2615669 ± 29815884 ± 1240.26
Dose to 0.1 cm3 of VIM ± SD (cGy)3002 ± 3351986 ± 7530.043129 ± 4842253 ± 5680.07
Dose to 0.05 cm3 of VIM ± SD (cGy)5542 ± 10345402 ± 8610.615661 ± 10134330 ± 16410.48
Dose to 0.035 cm3 of VIM ± SD (cGy)6958 ± 14557175 ± 9380.917202 ± 12476831 ± 13770.91

Max = maximum; Tx = treatment.

Values are expressed as the mean ± SD (range). Boldface type indicates statistical significance. There were no significant differences between early responders and nonresponders, using the native MRI or distortion-corrected MRI, for the autocontoured VIM volume, posttreatment lesion volume, or percentage of VIM overlap with the posttreatment lesion. For dose parameters, there were no differences between categories for the maximum radiation dose as well as dose to 0.05 cm3 and 0.035 cm3 of the VIM, but the dose to 0.1 cm3 of VIM was significantly different for the native MRI for early responders and nonresponders.

Examining the coverage of the autocontoured VIM at 20-Gy dose intervals, no statistically significant differences were found for VIM coverage at any DVH level between responders and nonresponders (Fig. 2A). The distortion-corrected MRI series were similarly analyzed using the autocontoured VIM, and showed no significant differences in the VIM DVH between responders and nonresponders (Fig. 2B). However, there was a trend for superior coverage in the responders versus nonresponders at the 20-Gy isodose level, both in the native MRI (p = 0.08 and p = 0.11) and the distortion-corrected MRI (p = 0.06 and p = 0.11), by 2-way ANOVA and Mann-Whitney U-test, respectively.

FIG. 2.
FIG. 2.

VIM DVH shows no differences between early responders and nonresponders. Using the native MRI (A) or the distortion-corrected MRI (B), the DVH for the VIM autocontour between early clinical responders (n = 6) and nonresponders (n = 4) shows no statistically significant differences (p > 0.05) at 20-Gy intervals between 20 Gy and 140 Gy, individually analyzed by Mann-Whitney U-test.

Next, the physician-selected SRS target isocenter was compared to the geometrical center of the VIM autocontour for the early-responding patients versus the nonresponding patients. Relative to the center of the VIM, the treatment isocenter was 0.9 ± 0.2 mm lateral in the early-responding patients compared to 0.9 ± 0.5 mm medial (mean ± SEM) (p = 0.019) (Fig. 3A). There were no statistically significant differences in the other dimensions: 0.2 ± 0.5 mm posterior and 0.6 ± 0.4 mm superior, compared to 0.4 ± 0.4 mm posterior and 0.2 ± 0.8 mm superior for responders and nonresponders, respectively (mean ± SEM). Analysis of the distortion-corrected MRI showed similar findings, with treatment isocenter being 0.7 ± 0.2 mm lateral to the VIM center in the responders compared to 1.1 ± 0.5 mm medial in the nonresponders (p = 0.019), and no significant differences for the other dimensions (mean ± SEM) (Fig. 3B).

FIG. 3.
FIG. 3.

The geometrical center for the autocontoured VIM can identify the best SRS target isocenter for early clinical responders. The physician-selected SRS target isocenter position relative to the VIM center was 0.9–0.7 mm lateral for early-responding patients compared to 0.9–1.1 mm medial for nonresponding patients, using the native MRI (A) or distortion-corrected MRI (B), respectively. The geometrical center of the posttreatment lesion relative to the VIM center was 0.5–0.6 mm lateral for early-responding patients compared to 1.1 mm medial for nonresponding patients, using the native MRI (C) or the distortion-corrected MRI (D), respectively. For all panels, there were no statistical differences between responders and nonresponders for the superior-inferior and anterior-posterior directions. The axes are defined in the neutral head holder position used for CT simulation. X-direction: positive is more lateral, negative is more medial. Y-direction: positive is more posterior, negative is more anterior. Z-direction: positive is more superior, negative is more inferior. The p values were calculated by Mann-Whitney U-test.

A confirmatory analysis was performed by comparing the geometrical center of the posttreatment lesions for the responders and nonresponders as manually contoured on the 3-month posttreatment MRI scan relative the autosegmented VIM geometrical center on the pretreatment MRI. Relative to the VIM center, the posttreatment lesion center was 0.5 ± 0.1 mm lateral in responders compared to 1.1 ± 0.5 mm medial in nonresponders (mean ± SEM) (p = 0.014) (Fig. 3C). The anteroposterior and superoinferior directions did not show significant differences for the posttreatment lesion center relative to the VIM center between responders and nonresponders. The distortion-corrected MRI showed similar findings, with the posttreatment lesion center 0.6 ± 0.1 mm lateral in responders compared to 1.1 ± 0.5 mm medial in nonresponders (mean ± SEM) (p = 0.010) (Fig. 3D).

To explore additional methods of determining the optimal treatment isocenter, DTI MRI series were acquired before and after SRS in the patients in cases 24–27. The DRTT structure was generated from the autocontoured regions of interest. The characteristics of the tracked fibers, including average FA, mean fiber length, and volume of the tracked fibers are listed in Table 2 for pretreatment and at least 2 posttreatment MRI scans. For the patients in cases 24 and 26, fiber tracking was unsuccessful at 3 months posttreatment, whereas for the patients in cases 25 and 27, fiber tracking was unsuccessful starting at 6 months posttreatment, showing the response patterns over several months after SRS.

TABLE 2.

DRTT fiber characteristics for SRS-treated patients

CharacteristicCase 24Case 25Case 26Case 27
Pre-Tx
 Average FA0.490.430.470.37
 Mean fiber length (mm)125151110138
 Vol (cm3)2.621.691.860.5
Post-Tx group 1 (3 mos)
 Average FANA0.47NA0.38
 Mean fiber length (mm)NA132NA121
 Vol (cm3)NA2.55NA0.78
Post-Tx group 2 (6–8 mos)
 Average FANANANANA
 Mean fiber length (mm)NANANANA
 Vol (cm3)NANANANA

NA = not applicable.

Tracts could not be generated (i.e., NA) for all 4 patients at 6–8 months after SRS, suggesting that the lesion successfully interrupted the DRTT.

Discussion

Successful delivery of SRS thalamotomy requires a 2-fold approach: the appropriate location of the isocenter target and the accurate delivery of radiation to the planned target position. For the delivery accuracy, we demonstrated that our delivered isocenter is within 1.1 mm of the intended target by overlapping the posttreatment lesion to the planned isocenter.7 Given that response from radiation therapy is a delayed reaction, predetermination of the treatment target is more crucial for SRS thalamotomy than for DBS or radiofrequency ablation procedures, in which the target can be adjusted according to a patient’s response during the procedure. In our current treatment protocol, the location of the target is initially derived from historical atlases, refined by a database of patients with deep brain stimulator implants, and then adjusted at the physician’s discretion. Although our current practice can benefit most patients, we aim to improve the treatment outcome by locating the optimal target directly from MR images with comparison of the early clinical responders and nonresponders.

Numerous studies have shown that the VIM is the target for successful deep brain stimulator implantation and radiofrequency ablation. Autocontouring of brain substructures was successfully performed by the Elements software on all the qualified imaging series. The VIM was appropriate in location, size, and shape, according to accepted neuroanatomical information.24,25

After mapping the isocenter to the autocontoured VIM, we found that our treated patients had a large range of isocenter positions relative to the VIM center—up to 2.8 mm in a single direction. The differences in all 6 directions (lateral–medial, anterior–posterior, and superior–inferior) were compared for groups of early responders and nonresponders. The only direction that appears to be associated with patient response is the medial–lateral position. Specifically, relative to the autocontoured VIM center, the responders had an isocenter position that was 0.9 ± 0.2 mm lateral and a posttreatment lesion center that was 0.5 ± 0.1 mm lateral (mean ± SEM). In contrast, nonresponders had a relative isocenter position that was 0.9 ± 0.5 mm medial to the VIM center and a posttreatment lesion that was 1.1 ± 0.5 mm medial (mean ± SEM). This statistically significant finding suggests that the optimal isocenter position for clinical response is 0.5–0.9 mm lateral to the autocontoured VIM geometrical center. Very similar results were obtained for both native and distortion-corrected MR images. It is likely that our MRI scanners were appropriately optimized to minimize geometrical distortion, especially near the center of the head where the echo planar spin echo MR scan is minimally distorted.

We investigated whether there were any correlations between early responders and nonresponders for DVH values, including volumes at 20-Gy intervals up to 140 Gy, mean dose, maximum dose, and dose to small volumes of the VIM. The only statistically significant difference was identified in the dose to 0.1 cm3 of autocontoured VIM structure, being slightly higher (at 30 Gy) in the responders compared to 20 Gy in the nonresponders. No correlations were found in any other of these parameters, although there was a trend toward significance at the 20-Gy isodose level. This finding may be due to the fact that the high-dose region resulting from a 4-mm cone is relatively small compared with the volume of the VIM structure. Therefore, as long as the isocenter is not too far from the center of VIM, the DVH at the high-dose level to VIM will be within the VIM and therefore similar on analysis of dosimetric parameters. In other words, once the maximum dose exceeds a certain threshold, the key correlation with tremor-control outcome appears to be the precise location where the high dose is deposited, not how much VIM is irradiated. Except for the low-dose range (20–30 Gy), the DVH-related values are not sensitive to where the isocenter is located and cannot be used as a predictor for good patient outcome.

The DTI fiber tracking can potentially provide another way of locating the isocenter. In this project, DRTTs were created by the Elements software with a deterministic algorithm for a few patients. A logical speculation is that the optimal location should be situated where the DRTT overlaps with the VIM contour. Even though this is true (as shown in Fig. 1 for the patient in case 25) and for the patient in case 27 (not shown), we cannot make a definitive conclusion due to limited data from only 2 patients with pretreatment DTI data in the early responders and nonresponders cohort. We therefore expanded the analysis to include 4 patients: 2 early responders and 2 late responders. In all cases, the DRTT appears to be disrupted by 6–8 months after SRS, which suggests that the treatment-related outcome mechanism involves this tract. Furthermore, the DRTT passes the VIM laterally and inferiorly, which could explain why all the early responders have an isocenter located laterally to the VIM center. The expected white matter damage is consistent with decreased DTI fiber length in all patients analyzed posttreatment, although this includes early responders and late responders.

There are multiple challenges to determine the optimal treatment target inside the VIM with either autosegmentation or DTI. For example, the autosegmentation of VIM with Elements software is atlas based, not directly imaged, and that can impose some uncertainty. There are other imaging modalities and techniques that can be used to directly map subthalamic structures, including susceptibility-weighted imaging with stronger magnetic fields.26–31 However, even if direct imaging of the VIM is clinically available, this work shows that the 0.7–0.9 mm lateral to geometrical center of the VIM is probably the optimal target location. DTI fiber tracking can potentially provide another way to locate the optimal treatment isocenter, because the DRTT fibers probably intersect with the target. The challenge with DTI, however, is that resolution is somewhat limited given the current clinical equipment and software available at most medical facilities. We suspect that improved imaging modalities in the future will continue to enhance the ability to identify the optimal target location.

Although the treatment outcome data are acquired prospectively to identify responders and nonresponders, the weakness of this study includes the limited and unparalleled sample sizes. Unfortunately, the DTI data are available for very few patients in our study. For future study, we will standardize the imaging process to improve the completeness of data sets for every patient. Other probabilistic fiber tracking algorithms can also be used to analyze our data.

Conclusions

SRS for tremor is a high-dose radiation treatment that requires extreme precision in selecting the optimal target location for clinical success. For early clinical response, the patient-specific autocontour of the thalamic VIM using Elements software identifies the optimal isocenter that is 0.7–0.9 mm lateral to the VIM geometrical center. DTI data can also potentially aid with deriving the treatment target.

Acknowledgments

We appreciate funding from NIH/NCI Grant No. 5K12CA090625-18 from the Vanderbilt Clinical Oncology Research Career Development Program. We appreciate Drs. Nader Pouratian and Evangelia Tsolaki, University of California, Los Angeles, for discussion about tractography.

Disclosures

Brainlab AG provided support for this project in the form of hardware, software, and salary to Ms. Luo and research funding to Dr. Kirschner. Brainlab had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. Dr. Neimat serves on the scientific advisory board and performs periodic consulting for Abbott, Inc., and Boston Scientific, Inc., who make DBS devices that can also be used to treat tremor. The other authors declare no relevant conflicts of interest.

Author Contributions

Conception and design: Kirschner, Luo. Acquisition of data: Kirschner, Luo, Yu, Neimat, Hedera, Phibbs, Bradley, Cmelak. Analysis and interpretation of data: Kirschner, Luo, Cameron, Wang. Drafting the article: Kirschner, Luo, Wang. Critically revising the article: Kirschner, Cameron, Wang, Cmelak. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Kirschner. Statistical analysis: Kirschner, Luo, Wang. Administrative/technical/material support: Kirschner, Luo, Cameron, Yu, Neimat, Hedera, Phibbs, Bradley, Cmelak. Study supervision: Kirschner, Cmelak.

Supplemental Information

Online-Only Content

Supplemental material is available with the online version of the article.

Supplementary Table 1. https://thejns.org/doi/suppl/10.3171/2021.7.JNS21160.

Current Affiliations

Dr. Hedera: Department of Neurology, University of Louisville, KY.

References

  • 1

    Mendonça MD, Meira B, Fernandes M, Barbosa R, Bugalho P. Deep brain stimulation for lesion-related tremors: a systematic review and meta-analysis. Parkinsonism Relat Disord. 2018;47:814.

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

    Chiken S, Nambu A. Disrupting neuronal transmission: mechanism of DBS? Front Syst Neurosci. 2014;8:33.

  • 3

    Barbe MT, Liebhart L, Runge M, Deyng J, Florin E, Wojtecki L, et al. Deep brain stimulation of the ventral intermediate nucleus in patients with essential tremor: stimulation below intercommissural line is more efficient but equally effective as stimulation above. Exp Neurol. 2011;230(1):131137.

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

    Kondziolka D, Ong JG, Lee JYK, Moore RY, Flickinger JC, Lunsford LD. Gamma Knife thalamotomy for essential tremor. J Neurosurg. 2008;108(1):111117.

  • 5

    Young RF, Jacques S, Mark R, Kopyov O, Copcutt B, Posewitz A, Li F. Gamma knife thalamotomy for treatment of tremor: long-term results. J Neurosurg. 2000;93(suppl 3):128135.

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

    Campbell AM, Glover J, Chiang VLS, Gerrard J, Yu JB. Gamma knife stereotactic radiosurgical thalamotomy for intractable tremor: a systematic review of the literature. Radiother Oncol. 2015;114(3):296301.

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

    Luo G, Neimat JS, Cmelak A, Kirschner AN, Attia A, Morales-Paliza M, Ding GX. Margin of error for a frameless image guided radiosurgery system: direct confirmation based on posttreatment MRI scans. Pract Radiat Oncol. 2017;7(3):e223e231.

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

    Gevaert T, Verellen D, Tournel K, Linthout N, Bral S, Engels B, et al. Setup accuracy of the Novalis ExacTrac 6DOF system for frameless radiosurgery. Int J Radiat Oncol Biol Phys. 2012;82(5):16271635.

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

    Grimm J, Grimm SYL, Das IJ, Zhu Y, Yeo I, Xue J, et al. A quality assurance method with submillimeter accuracy for stereotactic linear accelerators. J Appl Clin Med Phys. 2010;12(1):3365.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Jin JY, Ryu S, Faber K, Mikkelsen T, Chen Q, Li S, Movsas B. 2D/3D image fusion for accurate target localization and evaluation of a mask based stereotactic system in fractionated stereotactic radiotherapy of cranial lesions. Med Phys. 2006;33(12):45574566.

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

    Cameron B, Wang L, Cmelak AJ, et al. A Prospective, Observational trial of LINAC-based stereotactic radiosurgery for essential tremor and parkinsonian tremor. Int J Radiat Oncol Biol Phys. 2017;99(2):S102.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Kooshkabadi A, Lunsford LD, Tonetti D, Flickinger JC, Kondziolka D. Gamma Knife thalamotomy for tremor in the magnetic resonance imaging era. J Neurosurg. 2013;118(4):713718.

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

    Niranjan A, Raju SS, Kooshkabadi A, Monaco E III, Flickinger JC, Lunsford LD. Stereotactic radiosurgery for essential tremor: retrospective analysis of a 19-year experience. Mov Disord. 2017;32(5):769777.

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

    Ohye C, Higuchi Y, Shibazaki T, Hashimoto T, Koyama T, Hirai T, et al. Gamma knife thalamotomy for Parkinson disease and essential tremor: a prospective multicenter study. Neurosurgery. 2012;70(3):526536.

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

    Witjas T, Carron R, Krack P, Eusebio A, Vaugoyeau M, Hariz M, et al. A prospective single-blind study of Gamma Knife thalamotomy for tremor. Neurology. 2015;85(18):15621568.

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

    Schaltenbrand G, Wahren W. Atlas for Stereotaxy of the Human Brain. 2nd ed. Thieme;1977.

  • 17

    Stacy MA, Elble RJ, Ondo WG, Wu SC, Hulihan J. Assessment of interrater and intrarater reliability of the Fahn-Tolosa-Marin Tremor Rating Scale in essential tremor. Mov Disord. 2007;22(6):833838.

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

    Hagell P, Nygren C. The 39 item Parkinson’s disease questionnaire (PDQ-39) revisited: implications for evidence based medicine. J Neurol Neurosurg Psychiatry. 2007;78(11):11911198.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Tröster AI, Pahwa R, Fields JA, Tanner CM, Lyons KE. Quality of life in Essential Tremor Questionnaire (QUEST): development and initial validation. Parkinsonism Relat Disord. 2005;11(6):367373.

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

    Martínez-Martín P, Jiménez-Jiménez FJ, Carroza García E, Alonso-Navarro H, Rubio L, Calleja P, et al. Most of the Quality of Life in Essential Tremor Questionnaire (QUEST) psychometric properties resulted in satisfactory values. J Clin Epidemiol. 2010;63(7):767773.

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

    Coenen VA, Allert N, Paus S, Kronenbürger M, Urbach H, Mädler B. Modulation of the cerebello-thalamo-cortical network in thalamic deep brain stimulation for tremor: a diffusion tensor imaging study. Neurosurgery. 2014;75(6):657670.

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

    Calabrese E. Diffusion tractography in deep brain stimulation surgery: a review. Front Neuroanat. 2016;10:45.

  • 23

    Klein JC, Lorenz B, Kang JS, Baudrexel S, Seifried C, van de Loo S, et al. Diffusion tensor imaging of white matter involvement in essential tremor. Hum Brain Mapp. 2011;32(6):896904.

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

    Ewert S, Plettig P, Li N, Chakravarty MM, Collins DL, Herrington TM, et al. Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity. Neuroimage. 2018;170:271282.

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

    Nowinski WL, Liu J, Thirunavuukarasuu A. Quantification and visualization of three-dimensional inconsistency of the ventrointermediate nucleus of the thalamus in the Schaltenbrand-Wahren brain atlas. Acta Neurochir (Wien). 2008;150(7):647653.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26

    Rasouli J, Ramdhani R, Panov FE, Dimov A, Zhang Y, Cho C, et al. Utilization of quantitative susceptibility mapping for direct targeting of the subthalamic nucleus during deep brain stimulation surgery. Oper Neurosurg (Hagerstown). 2018;14(4):412419.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27

    Deistung A, Schäfer A, Schweser F, Biedermann U, Güllmar D, Trampel R, et al. High-resolution MR imaging of the human brainstem in vivo at 7 Tesla. Front Hum Neurosci. 2013;7:710.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Liu T, Eskreis-Winkler S, Schweitzer AD, Chen W, Kaplitt MG, Tsiouris AJ, Wang Y. Improved subthalamic nucleus depiction with quantitative susceptibility mapping. Radiology. 2013;269(1):216223.

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

    Najdenovska E, Tuleasca C, Jorge J, Maeder P, Marques JP, Roine T, et al. Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T. Sci Rep. 2019;9(1):1119.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    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
  • 31

    King NKK, Krishna V, Basha D, Elias G, Sammartino F, Hodaie M, et al. Microelectrode recording findings within the tractography-defined ventral intermediate nucleus. J Neurosurg. 2017;126(5):16691675.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

Supplementary Materials

  • Collapse
  • Expand

Illustration from Serrato-Avila (pp 1410–1423). Copyright Johns Hopkins University, Art as Applied to Medicine. Published with permission.

  • View in gallery
    FIG. 1.

    Autocontoured VIM and DRTT fiber. As a representative example, the autosegmented VIM (cyan line) and DRTT fiber (orange line) contoured using the pretreatment MRI scan are shown for early clinical responder patient in case 25. The pretreatment and 3-month posttreatment MRI scans are fused and the contours are displayed on the posttreatment T1-weighted MRI in axial (A), sagittal (B), and coronal (C) planes. The posttreatment lesion (light pink line) was manually contoured. Figure is available in color online only.

  • View in gallery
    FIG. 2.

    VIM DVH shows no differences between early responders and nonresponders. Using the native MRI (A) or the distortion-corrected MRI (B), the DVH for the VIM autocontour between early clinical responders (n = 6) and nonresponders (n = 4) shows no statistically significant differences (p > 0.05) at 20-Gy intervals between 20 Gy and 140 Gy, individually analyzed by Mann-Whitney U-test.

  • View in gallery
    FIG. 3.

    The geometrical center for the autocontoured VIM can identify the best SRS target isocenter for early clinical responders. The physician-selected SRS target isocenter position relative to the VIM center was 0.9–0.7 mm lateral for early-responding patients compared to 0.9–1.1 mm medial for nonresponding patients, using the native MRI (A) or distortion-corrected MRI (B), respectively. The geometrical center of the posttreatment lesion relative to the VIM center was 0.5–0.6 mm lateral for early-responding patients compared to 1.1 mm medial for nonresponding patients, using the native MRI (C) or the distortion-corrected MRI (D), respectively. For all panels, there were no statistical differences between responders and nonresponders for the superior-inferior and anterior-posterior directions. The axes are defined in the neutral head holder position used for CT simulation. X-direction: positive is more lateral, negative is more medial. Y-direction: positive is more posterior, negative is more anterior. Z-direction: positive is more superior, negative is more inferior. The p values were calculated by Mann-Whitney U-test.

  • 1

    Mendonça MD, Meira B, Fernandes M, Barbosa R, Bugalho P. Deep brain stimulation for lesion-related tremors: a systematic review and meta-analysis. Parkinsonism Relat Disord. 2018;47:814.

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

    Chiken S, Nambu A. Disrupting neuronal transmission: mechanism of DBS? Front Syst Neurosci. 2014;8:33.

  • 3

    Barbe MT, Liebhart L, Runge M, Deyng J, Florin E, Wojtecki L, et al. Deep brain stimulation of the ventral intermediate nucleus in patients with essential tremor: stimulation below intercommissural line is more efficient but equally effective as stimulation above. Exp Neurol. 2011;230(1):131137.

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

    Kondziolka D, Ong JG, Lee JYK, Moore RY, Flickinger JC, Lunsford LD. Gamma Knife thalamotomy for essential tremor. J Neurosurg. 2008;108(1):111117.

  • 5

    Young RF, Jacques S, Mark R, Kopyov O, Copcutt B, Posewitz A, Li F. Gamma knife thalamotomy for treatment of tremor: long-term results. J Neurosurg. 2000;93(suppl 3):128135.

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

    Campbell AM, Glover J, Chiang VLS, Gerrard J, Yu JB. Gamma knife stereotactic radiosurgical thalamotomy for intractable tremor: a systematic review of the literature. Radiother Oncol. 2015;114(3):296301.

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

    Luo G, Neimat JS, Cmelak A, Kirschner AN, Attia A, Morales-Paliza M, Ding GX. Margin of error for a frameless image guided radiosurgery system: direct confirmation based on posttreatment MRI scans. Pract Radiat Oncol. 2017;7(3):e223e231.

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

    Gevaert T, Verellen D, Tournel K, Linthout N, Bral S, Engels B, et al. Setup accuracy of the Novalis ExacTrac 6DOF system for frameless radiosurgery. Int J Radiat Oncol Biol Phys. 2012;82(5):16271635.

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

    Grimm J, Grimm SYL, Das IJ, Zhu Y, Yeo I, Xue J, et al. A quality assurance method with submillimeter accuracy for stereotactic linear accelerators. J Appl Clin Med Phys. 2010;12(1):3365.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Jin JY, Ryu S, Faber K, Mikkelsen T, Chen Q, Li S, Movsas B. 2D/3D image fusion for accurate target localization and evaluation of a mask based stereotactic system in fractionated stereotactic radiotherapy of cranial lesions. Med Phys. 2006;33(12):45574566.

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

    Cameron B, Wang L, Cmelak AJ, et al. A Prospective, Observational trial of LINAC-based stereotactic radiosurgery for essential tremor and parkinsonian tremor. Int J Radiat Oncol Biol Phys. 2017;99(2):S102.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Kooshkabadi A, Lunsford LD, Tonetti D, Flickinger JC, Kondziolka D. Gamma Knife thalamotomy for tremor in the magnetic resonance imaging era. J Neurosurg. 2013;118(4):713718.

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

    Niranjan A, Raju SS, Kooshkabadi A, Monaco E III, Flickinger JC, Lunsford LD. Stereotactic radiosurgery for essential tremor: retrospective analysis of a 19-year experience. Mov Disord. 2017;32(5):769777.

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

    Ohye C, Higuchi Y, Shibazaki T, Hashimoto T, Koyama T, Hirai T, et al. Gamma knife thalamotomy for Parkinson disease and essential tremor: a prospective multicenter study. Neurosurgery. 2012;70(3):526536.

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

    Witjas T, Carron R, Krack P, Eusebio A, Vaugoyeau M, Hariz M, et al. A prospective single-blind study of Gamma Knife thalamotomy for tremor. Neurology. 2015;85(18):15621568.

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

    Schaltenbrand G, Wahren W. Atlas for Stereotaxy of the Human Brain. 2nd ed. Thieme;1977.

  • 17

    Stacy MA, Elble RJ, Ondo WG, Wu SC, Hulihan J. Assessment of interrater and intrarater reliability of the Fahn-Tolosa-Marin Tremor Rating Scale in essential tremor. Mov Disord. 2007;22(6):833838.

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

    Hagell P, Nygren C. The 39 item Parkinson’s disease questionnaire (PDQ-39) revisited: implications for evidence based medicine. J Neurol Neurosurg Psychiatry. 2007;78(11):11911198.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Tröster AI, Pahwa R, Fields JA, Tanner CM, Lyons KE. Quality of life in Essential Tremor Questionnaire (QUEST): development and initial validation. Parkinsonism Relat Disord. 2005;11(6):367373.

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

    Martínez-Martín P, Jiménez-Jiménez FJ, Carroza García E, Alonso-Navarro H, Rubio L, Calleja P, et al. Most of the Quality of Life in Essential Tremor Questionnaire (QUEST) psychometric properties resulted in satisfactory values. J Clin Epidemiol. 2010;63(7):767773.

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

    Coenen VA, Allert N, Paus S, Kronenbürger M, Urbach H, Mädler B. Modulation of the cerebello-thalamo-cortical network in thalamic deep brain stimulation for tremor: a diffusion tensor imaging study. Neurosurgery. 2014;75(6):657670.

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

    Calabrese E. Diffusion tractography in deep brain stimulation surgery: a review. Front Neuroanat. 2016;10:45.

  • 23

    Klein JC, Lorenz B, Kang JS, Baudrexel S, Seifried C, van de Loo S, et al. Diffusion tensor imaging of white matter involvement in essential tremor. Hum Brain Mapp. 2011;32(6):896904.

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

    Ewert S, Plettig P, Li N, Chakravarty MM, Collins DL, Herrington TM, et al. Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity. Neuroimage. 2018;170:271282.

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

    Nowinski WL, Liu J, Thirunavuukarasuu A. Quantification and visualization of three-dimensional inconsistency of the ventrointermediate nucleus of the thalamus in the Schaltenbrand-Wahren brain atlas. Acta Neurochir (Wien). 2008;150(7):647653.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26

    Rasouli J, Ramdhani R, Panov FE, Dimov A, Zhang Y, Cho C, et al. Utilization of quantitative susceptibility mapping for direct targeting of the subthalamic nucleus during deep brain stimulation surgery. Oper Neurosurg (Hagerstown). 2018;14(4):412419.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27

    Deistung A, Schäfer A, Schweser F, Biedermann U, Güllmar D, Trampel R, et al. High-resolution MR imaging of the human brainstem in vivo at 7 Tesla. Front Hum Neurosci. 2013;7:710.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Liu T, Eskreis-Winkler S, Schweitzer AD, Chen W, Kaplitt MG, Tsiouris AJ, Wang Y. Improved subthalamic nucleus depiction with quantitative susceptibility mapping. Radiology. 2013;269(1):216223.

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

    Najdenovska E, Tuleasca C, Jorge J, Maeder P, Marques JP, Roine T, et al. Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T. Sci Rep. 2019;9(1):1119.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    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
  • 31

    King NKK, Krishna V, Basha D, Elias G, Sammartino F, Hodaie M, et al. Microelectrode recording findings within the tractography-defined ventral intermediate nucleus. J Neurosurg. 2017;126(5):16691675.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

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