Magnetic resonance–guided focused ultrasound thalamotomy restored distinctive resting-state networks in patients with essential tremor

Sachiko Kato Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;
Focused Ultrasound Therapy Center, Nagoya Kyoritsu Hospital, Nakagawa, Nagoya;

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Satoshi Maesawa Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;
Brain and Mind Research Center, Nagoya University, Showa, Nagoya;

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Epifanio Bagarinao Brain and Mind Research Center, Nagoya University, Showa, Nagoya;

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Daisuke Nakatsubo Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;
Focused Ultrasound Therapy Center, Nagoya Kyoritsu Hospital, Nakagawa, Nagoya;

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Takahiko Tsugawa Focused Ultrasound Therapy Center, Nagoya Kyoritsu Hospital, Nakagawa, Nagoya;

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Satomi Mizuno Department of Rehabilitation, National Hospital Organization, Nagoya Medical Center, Naka, Nagoya;

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Kazuya Kawabata Department of Neurology, Nagoya University Graduate School of Medicine, Showa, Nagoya;

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Takashi Tsuboi Department of Neurology, Nagoya University Graduate School of Medicine, Showa, Nagoya;

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Masashi Suzuki Department of Neurology, Nagoya University Graduate School of Medicine, Showa, Nagoya;

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Masashi Shibata Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;

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Sou Takai Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;

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Tomotaka Ishizaki Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;

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Jun Torii Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;

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Manabu Mutoh Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;

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Ryuta Saito Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya;

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Toshihiko Wakabayashi Focused Ultrasound Therapy Center, Nagoya Kyoritsu Hospital, Nakagawa, Nagoya;

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Masahisa Katsuno Department of Neurology, Nagoya University Graduate School of Medicine, Showa, Nagoya;

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Norio Ozaki Brain and Mind Research Center, Nagoya University, Showa, Nagoya;
Department of Psychiatry, Nagoya University Graduate School of Medicine, Showa, Nagoya; and

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Hirohisa Watanabe Brain and Mind Research Center, Nagoya University, Showa, Nagoya;
Department of Neurology, Fujita Medical University, Kutsukake, Toyoake; and

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Gen Sobue Brain and Mind Research Center, Nagoya University, Showa, Nagoya;
Aichi Medical University, Karimata, Nagakute, Aichi, Japan

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OBJECTIVE

Magnetic resonance–guided focused ultrasound (MRgFUS) thalamotomy ameliorates symptoms in patients with essential tremor (ET). How this treatment affects canonical brain networks has not been elucidated. The purpose of this study was to clarify changes of brain networks after MRgFUS thalamotomy in ET patients by analyzing resting-state networks (RSNs).

METHODS

Fifteen patients with ET were included in this study. Left MRgFUS thalamotomy was performed in all cases, and MR images, including resting-state functional MRI (rsfMRI), were taken before and after surgery. MR images of 15 age- and sex-matched healthy controls (HCs) were also used for analysis. Using rsfMRI data, canonical RSNs were extracted by performing dual regression analysis, and the functional connectivity (FC) within respective networks was compared among pre-MRgFUS patients, post-MRgFUS patients, and HCs. The severity of tremor was evaluated using the Clinical Rating Scale for Tremor (CRST) score pre- and postoperatively, and its correlation with RSNs was examined.

RESULTS

Preoperatively, ET patients showed a significant decrease in FC in the sensorimotor network (SMN), primary visual network (VN), and visuospatial network (VSN) compared with HCs. The decrease in FC in the SMN correlated with the severity of tremor. After MRgFUS thalamotomy, ET patients still exhibited a significant decrease in FC in a small area of the SMN, but they exhibited an increase in the cerebellar network (CN). In comparison between pre- and post-MRgFUS patients, the FC in the SMN and the VSN significantly increased after treatment. Quantitative evaluation of the FCs in these three groups showed that the SMN and VSN increased postoperatively and demonstrated a trend toward those of HCs.

CONCLUSIONS

The SMN and CN, which are considered to be associated with the cerebello-thalamo-cortical loop, exhibited increased connectivity after MRgFUS thalamotomy. In addition, the FC of the visual network, which declined in ET patients compared with HCs, tended to normalize postoperatively. This could be related to the hypothesis that visual feedback is involved in tremor severity in ET patients. Overall, the analysis of the RSNs by rsfMRI reflected the pathophysiology with the intervention of MRgFUS thalamotomy in ET patients and demonstrated a possibility of a biomarker for successful treatment.

ABBREVIATIONS

BOLD = blood oxygen level–dependent; CN = cerebellar network; CRST = Clinical Rating Scale for Tremor; DMN = default mode network; ECN = executive control network; ET = essential tremor; FC = functional connectivity; FWE = family-wise error; HC = healthy control; IC = independent component; ICA = IC analysis; MNI = Montreal Neurological Institute; MRgFUS = MR-guided focused ultrasound; ROI = region of interest; rsfMRI = resting-state functional MRI; RSN = resting-state network; SMN = sensorimotor network; SN = salience network; Vim = ventral intermediate nucleus; VN = primary visual network; VSN = visuospatial network.

OBJECTIVE

Magnetic resonance–guided focused ultrasound (MRgFUS) thalamotomy ameliorates symptoms in patients with essential tremor (ET). How this treatment affects canonical brain networks has not been elucidated. The purpose of this study was to clarify changes of brain networks after MRgFUS thalamotomy in ET patients by analyzing resting-state networks (RSNs).

METHODS

Fifteen patients with ET were included in this study. Left MRgFUS thalamotomy was performed in all cases, and MR images, including resting-state functional MRI (rsfMRI), were taken before and after surgery. MR images of 15 age- and sex-matched healthy controls (HCs) were also used for analysis. Using rsfMRI data, canonical RSNs were extracted by performing dual regression analysis, and the functional connectivity (FC) within respective networks was compared among pre-MRgFUS patients, post-MRgFUS patients, and HCs. The severity of tremor was evaluated using the Clinical Rating Scale for Tremor (CRST) score pre- and postoperatively, and its correlation with RSNs was examined.

RESULTS

Preoperatively, ET patients showed a significant decrease in FC in the sensorimotor network (SMN), primary visual network (VN), and visuospatial network (VSN) compared with HCs. The decrease in FC in the SMN correlated with the severity of tremor. After MRgFUS thalamotomy, ET patients still exhibited a significant decrease in FC in a small area of the SMN, but they exhibited an increase in the cerebellar network (CN). In comparison between pre- and post-MRgFUS patients, the FC in the SMN and the VSN significantly increased after treatment. Quantitative evaluation of the FCs in these three groups showed that the SMN and VSN increased postoperatively and demonstrated a trend toward those of HCs.

CONCLUSIONS

The SMN and CN, which are considered to be associated with the cerebello-thalamo-cortical loop, exhibited increased connectivity after MRgFUS thalamotomy. In addition, the FC of the visual network, which declined in ET patients compared with HCs, tended to normalize postoperatively. This could be related to the hypothesis that visual feedback is involved in tremor severity in ET patients. Overall, the analysis of the RSNs by rsfMRI reflected the pathophysiology with the intervention of MRgFUS thalamotomy in ET patients and demonstrated a possibility of a biomarker for successful treatment.

In Brief

The objective was to investigate alterations of canonical brain networks before and after magnetic resonance–guided focused ultrasound thalamotomy in patients with essential tremor. A key finding was that the sensorimotor network and the cerebellar network, which involved in the cerebello-thalamo-cortical loop, exhibited increased connectivity after treatment. Furthermore, the visual network declined preoperatively and normalized postoperatively, which could be related to the visual feedback. These network profiles demonstrated the possibility of a biomarker for successful treatment.

For the last decade, MR-guided focused ultrasound (MRgFUS) thalamotomy has been attracting attention as a novel treatment for essential tremor (ET) with favorable outcomes reported by many institutions worldwide.13 A target structure for this treatment is the ventral intermediate nucleus (Vim) in the thalamus in order to modify the abnormality in the cerebello-thalamo-cortical network, considered the main pathological basis in ET.46 Recently, however, instead of considering ET as a single pathological disease, different pathological conditions have been considered, such as those accompanied by cognitive decline in addition to motor dysfunction.79 This paradigm shift is expressed in a new concept called ET-plus.10 Thus, for pathophysiology in ET, alteration of some networks beyond the cerebello-thalamo-cortical network has drawn substantial interest from researchers.

Given this background, we hypothesized that ET patients exhibit characteristic changes in brain networks that could be identified by imaging studies. In addition, such characteristics could be modified by MRgFUS thalamotomy, visualized by the degree of modification, and eventually used as a biomarker for treatment prognosis. To validate this hypothesis, we evaluated alterations in the brain’s resting-state networks (RSNs) using resting-state functional MRI (rsfMRI) in patients with ET. Resting-state fMRI is effective in identifying several large-scale networks by examining the synchronization of the blood oxygen level–dependent (BOLD) signals from various brain regions during task-free functional MRI. It has been using in evaluating changes in brain networks in healthy aging1114 and various diseases, including Alzheimer disease, schizophrenia, autism, epilepsy, Parkinson disease, and other disorders of the central nervous system.1519

Until now, only a few network studies have been performed for ET using rsfMRI or task fMRI.2028 These reports mostly focused on the cerebello-thalamo-cortical network by setting specific regions of interest (ROIs) in the target anatomical structures. In this study, we used a data-driven approach based on independent component analysis (ICA)29 to explore network changes more objectively, eliminating arbitrary manipulations caused by predefining of the ROIs. Using this technique, we can independently evaluate several canonical RSNs, including the default mode network (DMN), the executive control network (ECN), the salience network (SN), the sensorimotor network (SMN), the visual network (VN), and the cerebellar network (CN), among other networks.30 To identify specific characteristics of brain networks in ET patients, we compared the RSNs between the patient group and age- and sex-matched healthy controls (HCs). In addition, the RSNs of ET patients were also compared before and after MRgFUS thalamotomy. To our knowledge, this is the first report that comprehensively evaluates network alterations in ET patients compared with HCs using rsfMRI with independent component analysis and that longitudinally investigates changes before and after surgery with the aim of comprehensively uncovering the neural network alterations specific to the pathology of ET and the influence of neuromodulation using MRgFUS thalamotomy.

Methods

Patient Population

In this study, we included patients who were 18 years of age or older with drug-resistant ET that was diagnosed by neurological examination and imaging studies at Nagoya University Hospital (Aichi, Japan) based on the International Parkinson and Movement Disorder Society tremor classification in 2018.10 We excluded patients who had 1) bleeding tendency, 2) thyroid disease, 3) brain or peripheral tissue damage that may cause tremor, 4) psychiatric disorders, 5) dementia, and 6) any other disease that may cause tremor. In addition, those with a contraindication for MRgFUS thalamotomy due to low skull density ratio (< 0.3) and with contraindications to MRI such as the presence of metal in the body or claustrophobia were further excluded. This study was approved by the local ethics committees of Nagoya University, and all patients provided informed consent.

From July 2017 to October 2020, 71 consecutive patients with ET were treated by MRgFUS thalamotomy in Nagoya Kyoritsu Hospital (Aichi, Japan) in cooperation with the functional neurosurgery team at Nagoya University Hospital. During this period, we introduced the study to all 71 patients and invited them to participate. Only 26 patients agreed. Reasons for declining participation included the unwillingness to visit a different institution just for research, extra time needed for the study, monetary problems, intolerance for longer MRI times, and COVID-19. None of the reasons for declining participation were because of treatment outcomes. Of the 26 patients, 11 dropped out after the operation. The remaining 15 patients (4 females and 11 males) met the inclusion criteria, provided informed consent, and were included in this study. The mean age of those who participated was 72.8 ± 5.39 years (mean ± SD, range 64–81 years). The average disease duration was 27.6 ± 20.86 years. The patients’ basic information was collected, including age, sex, disease duration, medication, and cognition, assessed using the Japanese version of Addenbrooke’s Cognitive Examination–Revised (Table 1).

TABLE 1.

Patient characteristics

Value
No. of pts15
Female/male4:11
Mean age, yrs72.8 ± 5.39 (64–81)
Mean disease duration, yrs27.6 ± 20.86 (6–65)
Total ACE-R score91.2 ± 7.3 (77–100)

ACE-R = Addenbrooke’s Cognitive Examination–Revised; pt = patient. Mean values are presented as mean ± SD (range).

For HCs, we used the rsfMRI and structural MRI data from our ongoing aging cohort study.31 This study was approved by the ethics committee of Nagoya University. Fifteen age- and sex-matched controls were chosen from the database of participants. Of these 15 HCs, 4 were female and 11 were male. The mean age was 73.4 ± 4.72 years (mean ± SD, range 65–83 years). The ages of HCs and patients were not significantly different (p = 0.912, two-sample t-test). In terms of head motion during rsfMRI, which typically affects the estimation of the functional connectivity, the mean frame-wise displacement values32 were 0.168 ± 0.070 mm in pre-MRgFUS patients, 0.164 ± 0.075 mm in post-MRgFUS patients, and 0.180 ± 0.072 mm in HCs on average.

MRgFUS Procedure and Clinical Evaluation

All patients underwent MRgFUS thalamotomy targeting the Vim using the ExAblate 4000 (Insightec). The surgical procedure was described in our previous report.3 The Vim was determined as the initial target, 11.5–12.0 mm lateral to the lateral wall of the third ventricle (i.e., 15–17 mm lateral to the anterior commissure–to–posterior commissure [AC-PC] line, one-third of the length of AC-PC − 1.5 mm anterior to the PC, and 1.5–2.0 mm superior to the AC-PC plane). Sonication was administered with more than two shots of high-dose ultrasonic waves to create permanent lesions, with temperature targets exceeding 54°C but below 60°C, under MRI guidance and intraoperative symptomatic inspection by neurosurgeons (Supplementary Fig. 1).

Follow-up evaluations were performed after 1 week, 1 month, 3 months, and 6 months postoperatively. The severity of the tremor was assessed by Clinical Rating Scale for Tremor (CRST) score.45 The percentage improvement in CRST score was calculated in the score of parts A, B, and C for the total body and for the affected upper limb. CRST part A relates to the tremor in 9 parts of the body, and part B assesses tremor for writing and pouring liquids. The CRST score for part C was assessed by a patient’s questionnaire for one’s daily quality of life. We note that the improvement of the CRST (A + B + C) 6 months after the operation of the patients who did not participate was approximately 48%, almost equal to those who participated in the study.

Acquisition of MRI Data and Image Preprocessing

T1 anatomical images and rsfMRI data were acquired from all patients pre- and postoperatively. Postoperative images were obtained 6.7 ± 1.2 months (mean ± SD, range 5–8 months) postoperatively. All MRI data were acquired at the Brain and Mind Research Center, Nagoya University (Aichi, Japan) using a Magnetom Verio (Siemens) 3.0-T MRI scanner with a 32-channel head coil. Using a 3D MPRAGE sequence, high-resolution T1-weighted images were acquired in all participants with the following imaging parameters: TR 2.5 seconds, TE 2.48 msec, 192 sagittal slices and 1-mm thickness, FOV 256 mm, 256 × 256 matrix size, and a 1 × 1–mm2 in-plane voxel resolution. In addition, rsfMRI data were also acquired using a gradient-echo, echo-planar imaging sequence with TR 2.5 seconds, TE 30 msec, 39 transversal slices (0.5-mm interslice interval and 3-mm thickness), FOV 192 mm, 64 × 64 matrix dimension, flip angle 80°, and 198 volumes in total. Participants were instructed to close their eyes but stay awake during rsfMRI. Head motion was minimized by tightly fixing the participant’s head with cushions. The same MRI protocols were used for the HCs.

We used the Statistical Parametric Mapping (SPM12, Wellcome Trust Center for Neuroimaging) software running on MATLAB (R2016a, MathWorks) to preprocess all MRI data. The T1-weighted images were segmented into component images including gray matter, white matter, and CSF using the segmentation approach of SPM12. In addition, bias-corrected T1-weighted images and the transformation information needed to normalize images from subject space to the Montreal Neurological Institute (MNI) space were also extracted during segmentation. For the rsfMRI data, the first 5 images in the series were removed to account for the inhomogeneity in the initial images. The remaining images were slice-time corrected relative to the middle slice (slice 20), realigned to the mean functional image, coregistered to the bias-corrected T1-weighted image, normalized to the MNI space using the transformation information obtained during segmentation, resampled to an isotropic voxel with resolution equal to 2 × 2 × 2 mm3, and smoothed using an isotropic 8-mm full-width-at-half-maximum 3D Gaussian filter. Additionally, head motion was corrected by regressing out the following 24 motion-related time series: Rt Rt2 Rt−1 Rt−12, where R = (x, y, z, roll, pitch, and yaw) represents the estimated motion parameters (3 translations and 3 rotations). Signals extracted from spherical ROIs (radius 4 mm) within the CSF (center’s MNI coordinate 20, −32, 18) and white matter (center’s MNI coordinate 24, −12, 34), the global signal, and their derivatives were also removed. The preprocessed images were then bandpass filtered within 0.01–0.1 Hz. These additional preprocessing steps were performed using in-house MATLAB scripts as reported previously.33 The preprocessed data set was used in the subsequent analysis.

RSN Analysis

We utilized dual regression analysis29 to evaluate functional connectivity (FC) changes within canonical RSNs. Specifically, we performed three pairs of group comparisons: 1) between pre-MRgFUS patients and HCs, 2) between post-MRgFUS patients and HCs, and 3) between pre-MRgFUS patients and post-MRgFUS patients. For each comparison, group independent component analysis (ICA) was performed using the MELODIC software from the FSL package.34 This is done by temporally concatenating the preprocessed rsfMRI data sets from each group (total of 30 subjects) and extracting 20 independent components (ICs). The extracted ICs were visually compared with a set of reference RSN templates (http://findlab.stanford.edu/functional_ROIs.html)30 to identify several canonical RSNs. Using the extracted group ICs as spatial regressors, the corresponding temporal dynamics associated with each IC were estimated from each subject’s rsfMRI data. Subject-specific maps associated with the group ICs were generated in a second regression using these time courses as temporal regressors. Each component map was separately analyzed using a nonparametric permutation test using 5000 permutations with age and sex included as covariates. Regions showing statistically significant connectivity differences were identified between the two groups. We used a mask created by each component map to limit the analysis within networks. Statistical significance was evaluated using p < 0.05 corrected for multiple comparisons using family-wise error (FWE) correction.

Quantitative Evaluation for Alteration of the Functional Connectivity in Distinctive RSNs After MRgFUS Thalamotomy

In this analysis, all 45 preprocessed rsfMRI data sets (15 pre-MRgFUS patients, 15 post-MRgFUS patients, and 15 HCs) were used for group ICA. Similar to the previous analysis, 20 ICs were extracted and RSNs were identified by visually comparing each IC with a set of reference RSN templates. Using dual regression analysis, individual RSNs were constructed. Then, for each subject, the mean FC was calculated within the affected RSNs identified in the above RSN analyses. In addition, the mean FC values were also calculated in regions showing a significant difference in each RSN. The extracted values from the three groups were then compared using one-way ANOVA (Kruskal-Wallis test; p < 0.05) followed by multiple comparisons using the Steel-Dwass test.

Correlation Analysis for the RSNs With Clinical Factors

We also performed correlation analyses between clinical features and the FCs in affected RSNs using Pearson’s correlation coefficient method for parametric data and Spearman’s rank correlation coefficient method for nonparametric data. The mean FC was calculated in affected RSNs and specific regions showing significant differences in the previous analysis. Variables examined included age, sex, disease duration, the CRST score (A, B, and C) of the total body and the affected upper limb, the improvement rate in each score of the CRST, and the total score of Addenbrooke’s Cognitive Examination–Revised. The threshold for statistical significance was set at p < 0.05.

Results

Dual Regression Analysis Between Pre-MRgFUS Patients and HCs

In the comparison between pre-MRgFUS patients and HCs, 12 RSNs were examined, including the ventral DMN, dorsal DMN, SN, left ECN, right ECN, SMN, primary VN, visuospatial network (VSN), frontoparietal network, language network, precuneus network, and CN. Pre-MRgFUS patients demonstrated a significant decrease in FC compared with HCs in the SMN, primary VN, and VSN (p < 0.05, FWE) (Fig. 1). No significant increases in FC were observed in the pre-MRgFUS patients compared with HCs.

FIG. 1.
FIG. 1.

Results of dual regression analysis between pre-MRgFUS patients and HCs. Pre-MRgFUS patients demonstrated a significant decrease in FC compared with HCs in the SMN, primary VN, and VSN (p < 0.05, FWE). The RSN (white) and the regions showing significant decrease (blue) were superimposed on the anatomical standard brain. Figure is available in color online only.

Dual Regression Analysis Between Post-MRgFUS Patients and HCs

In the comparison between the post-MRgFUS patients and HCs, 12 RSNs were examined, including the ventral DMN, dorsal DMN, SN, left ECN, right ECN, SMN, primary VN, VSN, higher VN, language network, precuneus network, and CN. Post-MRgFUS patients demonstrated a significant decrease in FC compared with the HCs only in the SMN (p < 0.05, FWE) (Fig. 2A left). The regions with significant decrease in the SMN were smaller than those observed in the pre-MRgFUS patients compared with HCs. No significant difference was found in the primary VN and VSN, different from what was found in the comparison of pre-MRgFUS patients and HCs. However, the CN showed a significant increase of FC in the post-MRgFUS patients compared with HC (Fig. 2A right).

FIG. 2.
FIG. 2.

A: Results of dual regression analysis between post-MRgFUS patients and HCs. Post-MRgFUS patients demonstrated a significant decrease in FC compared with HCs only in the SMN (p < 0.05, FWE) (left). However, the CN showed a significant increase in the FC in post-MRgFUS patients compared with HCs (right). The RSN (white) and the regions showing significant decrease (blue) or increase (orange) were superimposed on the anatomical standard brain. B: Results of dual regression analysis between pre-MRgFUS and post-MRgFUS patients. Post-MRgFUS patients demonstrated a significant increase in FC compared with pre-MRgFUS patients in the SMN and VSN (p < 0.05, FWE). The RSN (white) and the regions showing significant increase (orange) were superimposed on the anatomical standard brain. Figure is available in color online only.

Dual Regression Analysis Between Pre- and Post-MRgFUS Patients

In this comparison, 11 RSNs were examined, including the DMN, anterior SN, posterior SN, left ECN, right ECN, SMN, primary VN, VSN, language network, precuneus network, and CN. Post-MRgFUS patients demonstrated a significant increase in FC compared with pre-MRgFUS patients in the SMN and VSN (p < 0.05, FWE) (Fig. 2B). The difference in the opposite comparison was not statistically significant.

Quantitative Evaluation for Alteration of FC in Affected RSNs After MRgFUS Thalamotomy

For the three-group (pre-MRgFUS, post-MRgFUS, and HC) ICA analysis, 12 RSNs were extracted, including the DMN, anterior SN, posterior SN, left ECN, right ECN, SMN, primary VN, higher VN, VSN, language network, precuneus network, and CN. Focusing on the four affected networks (SMN, primary VN, VSN, and CN) identified in the previous analyses, the strength of the mean FC was compared. A significant difference was seen in the FC of the SMN network between pre-MRgFUS patients and HCs (one-way ANOVA, p < 0.05). The FC of post-MRgFUS patients showed an intermediate value between the other two groups, demonstrating that the FC of the SMN after MRgFUS thalamotomy tends to normalize toward that of the HCs (Fig. 3 upper). Similar behavior was observed for the FC of the VSN (Fig. 3 lower). The FC of the primary VN and CN did not show significant difference among three groups.

FIG. 3.
FIG. 3.

Results of the quantitative evaluation of the alterations of the functional connectivity in affected RSNs after MRgFUS thalamotomy. A significant difference was seen in the FC of the SMN between the pre-MRgFUS patients and HCs (p < 0.05) (upper). The FC of the VSN after MRgFUS thalamotomy also tends to normalize toward that of the HCs (lower).

Correlation Analysis for the RSNs With Clinical Factors

The correlation analysis was performed between the FC of the affected networks and clinical characteristics. Postoperative changes of the tremor are summarized in Table 2 and Supplementary Fig. 2. The FC of the regions showing significance in those networks was also evaluated. The MNI coordinate of the peak intensity’s location of those anatomical regions and cluster size are shown in Table 3. The FC in the left precentral gyrus, where a significant difference was seen in the SMN between pre-MRgFUS patients and HCs, showed negative correlation with the score of the part A of the CRST in the total body (R = −0.554, p = 0.032, Pearson’s correlation coefficient method). The FC in the same region was also negatively correlated with the degree of improvement in CRST in the affected limb after 1 month (R = −0.521, p = 0.047, Spearman’s rank correlation coefficient method) (Fig. 4). No association was found in the FC of other networks and other regions with clinical factors.

TABLE 2.

Tremor severity according to CRST scores

CRST ScoreMean ± SD
Whole BodyRt Upper Limb
Preop
 Total49.3 ± 1219 ± 3.42
 A12.07 ± 5.595 ± 1.25
 B23.13 ± 5.1814 ± 3.14
 C14.07 ± 3.45NA
1 wk
 Total17.67 ± 8.852.47 ± 2.72
 A5.33 ± 2.020.33 ± 0.49
 B10.53 ± 5.382.13 ± 2.56
 C1.8 ± 2.21NA
 Improvement, %65.01 ± 13.0486.97 ± 13.92
1 mo
 Total21.47 ± 11.475.13 ± 5.44
 A5.6 ± 2.530.8 ± 0.86
 B12.93 ± 7.254.33 ± 4.86
 C2.93 ± 3.08NA
 Improvement, %55.85 ± 23.8372.1 ± 28.9
3 mos
 Total24.57 ± 10.077.14 ± 4.28
 A6 ± 2.691.43 ± 1.22
 B14.57 ± 6.145.71 ± 4.05
 C3.79 ± 3.07NA
 Improvement, %50.44 ± 18.4660.78 ± 25.97
6 mos
 Total26.79 ± 12.327.71 ± 5.36
 A7 ± 3.261.64 ± 1.55
 B15.29 ± 7.426.07 ± 4.99
 C4.5 ± 3.61NA
 Improvement, %47.29 ± 18.7559.68 ± 26.31

NA = not applicable.

TABLE 3.

Anatomical regions showing significant changes in functional connectivity

Canonical NetworkClustersPeak MNI CoordinatePeak Anatomical Regionp Value at Peak RegionVoxel Counts
Pre-MRgFUS vs HCs*
 SMN1−42, −22, 68Lt precentral gyrus0.0092437
240, −16, 44Rt precentral gyrus0.031840
3−6, −22, 52Lt SMA0.036678
422, −26, 64Rt precentral gyrus0.0168453
512, −20, 80Rt precentral gyrus0.04316
 VSN152, −34, 54Rt inferior parietal lobe0.019469
 VN1−14, −46, −12Lt cerebellum0.01223082
222, −64, −2Rt lingual gyrus0.025395
Post-MRgFUS vs HCs*
 SMN118, −28, −54Rt paracentral lobule0.041834
216, −52, 64Rt superior parietal lobule0.029458
Post-MRgFUS vs HCs
 CN1−20, −56, −26Lt cerebellum0.025820
Post-MRgFUS vs pre-MRgFUS
 VSN118, −62, 48Rt superior parietal lobule0.04568
2−34, −52, 62Rt superior parietal lobule0.04910
 SMN148, −18, 48Rt precentral gyrus0.0337

SMA = supplementary motor area.

Significant decrease compared with HCs.

Significant increase compared with HCs.

Significant increase in the post-MRgFUS group compared with the pre-MRgFUS group.

FIG. 4.
FIG. 4.

Results of correlation analysis for the RSNs with clinical factors. Left: The FC in the left precentral gyrus showed negative correlation with the CRST part A score in the total body (R = −0.554, p = 0.032). Right: The FC in the same region was also negatively correlated with the degree of improvement in CRST score in the affected limb after 1 month (R = −0.4741, p = 0.047).

Discussion

In this study, our results showed the following. 1) Patients with ET had lower FC in the SMN, VSN, and primary VN than did HCs, and the severity of tremor negatively correlated with the FC in the SMN (i.e., the higher the tremor, the lower the FC). 2) After MRgFUS thalamotomy, although some regions still showed lower FC in SMN in patients compared with the HCs, the extent was reduced. However, the CN showed significantly higher FC in patients compared with HCs. 3) In longitudinal comparison, the FC in the SMN and the VSN tended to normalize toward that of the HCs after MRgFUS thalamotomy, indicating the possibility that the FC of the affected networks were partially restored after surgery. Although several network studies have been performed (Table 4), this is the first report that comprehensively demonstrates the network changes in the SMN, VN, VSN, and the CN in ET patients before and after MRgFUS (Fig. 5).

TABLE 4.

Summary of major literature for network analysis using rsfMRI and task-specific fMRI in ET patients

Authors & YearNo. of SubjectsAnalysis MethodsStudy DesignFindings
Archer et al., 20182019 ET pts, 18 HCsTask fMRI analysis w/ grip force task, seed basedET vs HCTremor exacerbated by visual feedback associated w/ changes in BOLD amplitude & entropy in CTC network to visual & parietal areas
Benito-León et al., 20152123 ET pts, 22 HCsICAET vs HCFCs ↓ in CN & VN; FC ↑ in DMN & frontoparietal network
Benito-León et al., 20192223 ET pts, 23 HCsGraph theory analysisET vs HCDisrupted efficiency of overall network in & beyond SMN
Buijink et al., 20152340 ET pts, 22 HCsSeed-based, dynamic causal modelingET vs HCFC ↓ btwn motor cortex & cerebellum; FC ↑ btwn cerebellum & thalamus
DeSimone et al., 20192418 ET, 20 dystonic tremor pts, 22HCsTask fMRI analysis w/ grip force task, seed basedET vs dystonic tremorWidespread reductions in FC in dystonic tremor pts in higher cortical, basal ganglia, & cerebellar regions, compared w/ ET pts
Fang et al., 20152535 ET pts, 35 HCsICAET vs HCFC ↓ w/in CN, btwn SMN & CN, btwn SMN & DMN; FC ↑ w/in SMN
Gallea et al., 20152619 ET pts, 19 HCsBOLD, dynamic causal modelingET vs HCEffective connectivity ↓ in CN, in SMA
Lenka et al., 20172730 ET pts, 30 HCsSeed-basedET vs HCFC ↓ btwn motor, SMA & the cerebellum; FC ↓ btwn the thalamus & the cerebellum
Nicoletti et al., 20202823 ET pts, 23 HCsSeed-basedET vs HCFC ↓ the primary motor to premotor, SMA, parietal areas; FC ↑ from thalamus to cerebellum; FC ↓ cerebellum to premotor cortex
Jang et al., 2016408 ET ptsSeed-based graph theoryMRgFUS, longitudinalFC ↓ among the motor-related areas, btwn substantia nigra & external globus pallidum
Park et al., 2017418 ET ptsDynamic causal modelingMRgFUS, longitudinalChanges in effective connectivity from ventrolateral nuclei & SMA to dentate nucleus
Popa et al., 20134211 ET pts, 11 HCsICATMS, longitudinalFC ↓ in CTC network preop; restored FC in CTC network postop
Tuleasca et al., 20184317 ET pts,Seed-basedGamma Knife, longitudinalFC ↑ in visual function related networks postop
Present study15 ET pts, 15 HCsICAMRgFUS, longitudinalFC ↓ in SMN, VN preop; restored in SMN, VN & CN postop

CTC = cerebello-thalamo-cortical; TMS = transcranial magnetic stimulation; ↑ = increase; ↓ = decrease.

FIG. 5.
FIG. 5.

Diagram showing the networks associated with ET. The white arrow represents the increase in FC, and the black arrow represents the decrease in FC. Author names and publication years for related literature are listed in parentheses. Pre = preintervention; post = postintervention; rTMS = repeated transcranial magnetic stimulation.

Changes in the Cerebello-Thalamo-Cortical Network in ET

A dysfunction of the cerebello-thalamo-cortical network is considered to be a main pathology of ET.4 The cerebellum plays an important role in this pathophysiology, and some morphological abnormalities in the cerebellar Purkinje cells35 and functional abnormalities of the GABA receptors in the cerebellum were reported,36 although it is under debate whether these abnormalities are truly a pathological basis for ET. Several reports have stated that abnormalities in the cerebellum caused hyperexcitability in the relayed nucleus in the thalamus (i.e., the Vim, which in turn, excessively excited the motor cortex, resulting in worsening tremor).5,6 Thus, many network studies focused on the cerebello-thalamo-cortical network, examining predetermined ROIs in each anatomical structure in this network. Using seed-based connectivity analysis, Lenka et al. reported that in ET patients, the primary motor cortex and the primary somatosensory cortex demonstrated decreased connectivity with several cerebellar lobules, whereas the bilateral thalamus showed increased connectivity with several posterior cerebellar regions correlating with the tremor severity.27 Although there were differences in analysis techniques, similar results have been reported.23,37

Changes in the SMN and CN Evaluated by rsfMRI in ET

In this study, the decrease in FC within the SMN in ET patients was observed. Our approach mainly evaluated the FC within the SMN, consisting of the primary motor cortex, the primary sensory cortex, and the supplementary motor area, and therefore could not be used to directly assess the connectivity between the motor cortex and the thalamus or cerebellum. However, the observed decrease of the FC in the SMN correlated with the severity of tremor in our study, justifying the usefulness of our method for network evaluation in ET patients. Moreover, Gallea et al. reported reduced connectivity between the supplementary motor area and the primary motor cortex in ET patients,26 which supports our results. Studies have shown that connectivity within the SMN markedly decreased with aging,1114 reflecting in the decrease of one’s motor performance over age. The ET patients recruited in our study had long periods of severe tremor before MRgFUS thalamotomy, leading to generally reduced motor performance. In this sense, the observed decrease in FC in the SMN in ET patients seemed reasonable. However, contrary to our expectation, the CN showed no decrease in ET patients preoperatively compared with HCs. This analysis was limited within the CN and does not discount the possibility that the connectivity between some regions in the CN and other brain regions may be altered. In addition, the identified CN included the whole cerebellum, and subtle changes in several regions within the cerebellum may cancel each other.

Influence of Visual Function in ET

The decrease of FC in the primary VN and VSN, found in pre-MRgFUS patients in this study, was also intriguing. There had been reports indicating that visual feedback may play an important role in the pathophysiology of ET. Archer et al. evaluated the influence of visual feedback in ET patients using task fMRI and found that a worsening tremor correlated to the changes in BOLD signal in the cerebello-thalamo-cortical loop and the visual cortex.20 Similar results have also been reported in both behavioral and neuroimaging experiments.21,3739 In this sense, our results also reinforced such a hypothesis that tremor may be affected by abnormal neural processing in areas outside of the cerebello-thalamo-cortical network, such as the visual network.

Connectivity Changes After Intervention in ET

Several longitudinal studies also reported network analysis in ET patients before and after various interventions. Jang et al. studied rsfMRI using graph theory before and after MRgFUS thalamotomy and showed that some internetwork connectivity related to motor areas was altered after surgery.40 Park et al. also evaluated longitudinal data sets after MRgFUS thalamotomy using dynamic causal modeling and concluded that the efficiency of the network from the ventrolateral thalamus and the SMA to the contralateral dentate nucleus in the cerebellum was improved.41 Popa et al. reported that the network between the cerebellum and the motor cortex, restored after transcranial magnetic stimulation to the posterior cerebellum, in ET patients correlated with improvement of the tremor.42 Tuleasca et al. showed that some visual function–related networks improved after the thalamotomy by stereotactic radiosurgery, in correlation with tremor suppression.43 Consistent with these results, we also found that some canonical networks, including the SMN, VSN, and CN, changed after MRgFUS thalamotomy. Taken together, our results seem to suggest restoration of these networks by MRgFUS thalamotomy.

Network Profiles as Possible Biomarkers and Study Limitations

Prospectively, we believed that network analysis could be used to identify relevant biomarkers for ET. Some reports already demonstrated such potentials for clinical application, including the differentiation from dystonic tremor,24 the correlation between tremor severity and FC,20,23,25,27,28 and the correlation with nonmotor symptoms such as cognition.21,22,25 In addition, network analyses could be useful for individuals, applying preoperative determination of the effective target for stereotactic functional neurosurgery including MRgFUS thalamotomy and deep brain stimulation.44 Finally, we would like to mention our study’s limitations. First, the number of subjects was relatively small. Additional patients could provide clearer clinical correlation with estimated network measures. Second, the analysis of the interaction among networks will be necessary to fully understand how brain networks are altered after the intervention of MRgFUS thalamotomy. A between-network analysis among the SMN, CN, and thalamic network may further elucidate the neuromodulatory mechanism associated with MRgFUS thalamotomy.

Conclusions

Taken together, our study showed that the SMN and the CN, important components of the cerebello-thalamo-cortical loop, demonstrated an increase in FCs after MRgFUS thalamotomy. In addition, the significantly lower FC value of the VN preoperatively was restored postoperatively, which could be related to the hypothesis that visual feedback is involved in the severity of the tremor in ET patients. Thus, findings from the analysis of the RSNs using rsfMRI reflected the pathophysiology with the intervention of MRgFUS thalamotomy in ET patients and demonstrated the possibility of using RSN changes as biomarkers for successful treatment.

Acknowledgments

This study was supported by a grant-in-aid for scientific research (KAKENHI, no. 22H03184).

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: Maesawa, Kato, Nakatsubo, Tsugawa, Saito, Wakabayashi, Watanabe, Sobue. Acquisition of data: Maesawa, Kato, Nakatsubo, Tsugawa, Mizuno, Kawabata, Tsuboi, Suzuki, Shibata, Takai, Ishizaki, Torii, Mutoh, Wakabayashi, Katsuno, Watanabe. Analysis and interpretation of data: Maesawa, Kato, Bagarinao, Mizuno, Kawabata, Tsuboi, Suzuki, Takai, Ishizaki, Torii, Mutoh, Saito, Ozaki, Watanabe. Drafting the article: Maesawa, Kato, Bagarinao, Mizuno, Torii, Sobue. Statistical analysis: Maesawa. Study supervision: Maesawa, Saito, Wakabayashi, Katsuno, Ozaki, Sobue.

Supplemental Information

Online-Only Content

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

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  • Collapse
  • Expand
Images from Holland et al. (pp 329–336).
  • FIG. 1.

    Results of dual regression analysis between pre-MRgFUS patients and HCs. Pre-MRgFUS patients demonstrated a significant decrease in FC compared with HCs in the SMN, primary VN, and VSN (p < 0.05, FWE). The RSN (white) and the regions showing significant decrease (blue) were superimposed on the anatomical standard brain. Figure is available in color online only.

  • FIG. 2.

    A: Results of dual regression analysis between post-MRgFUS patients and HCs. Post-MRgFUS patients demonstrated a significant decrease in FC compared with HCs only in the SMN (p < 0.05, FWE) (left). However, the CN showed a significant increase in the FC in post-MRgFUS patients compared with HCs (right). The RSN (white) and the regions showing significant decrease (blue) or increase (orange) were superimposed on the anatomical standard brain. B: Results of dual regression analysis between pre-MRgFUS and post-MRgFUS patients. Post-MRgFUS patients demonstrated a significant increase in FC compared with pre-MRgFUS patients in the SMN and VSN (p < 0.05, FWE). The RSN (white) and the regions showing significant increase (orange) were superimposed on the anatomical standard brain. Figure is available in color online only.

  • FIG. 3.

    Results of the quantitative evaluation of the alterations of the functional connectivity in affected RSNs after MRgFUS thalamotomy. A significant difference was seen in the FC of the SMN between the pre-MRgFUS patients and HCs (p < 0.05) (upper). The FC of the VSN after MRgFUS thalamotomy also tends to normalize toward that of the HCs (lower).

  • FIG. 4.

    Results of correlation analysis for the RSNs with clinical factors. Left: The FC in the left precentral gyrus showed negative correlation with the CRST part A score in the total body (R = −0.554, p = 0.032). Right: The FC in the same region was also negatively correlated with the degree of improvement in CRST score in the affected limb after 1 month (R = −0.4741, p = 0.047).

  • FIG. 5.

    Diagram showing the networks associated with ET. The white arrow represents the increase in FC, and the black arrow represents the decrease in FC. Author names and publication years for related literature are listed in parentheses. Pre = preintervention; post = postintervention; rTMS = repeated transcranial magnetic stimulation.

  • 1

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

  • 2

    Abe K, Horisawa S, Yamaguchi T, et al. Focused ultrasound thalamotomy for refractory essential tremor: a Japanese multicenter single-arm study. Neurosurgery. 2021;88(4):751757.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3

    Maesawa S, Nakatsubo D, Tsugawa T, et al. Techniques, indications, and outcomes in magnetic resonance-guided focused ultrasound thalamotomy for tremor. Neurol Med Chir (Tokyo). 2021;61(11):629639.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    Hallett M. Tremor: pathophysiology. Parkinsonism Relat Disord. 2014;20(suppl 1):S118S122.

  • 5

    Wills AJ, Jenkins IH, Thompson PD, Findley LJ, Brooks DJ. Red nuclear and cerebellar but no olivary activation associated with essential tremor: a positron emission tomographic study. Ann Neurol. 1994;36(4):636642.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Britton TC, Thompson PD, Day BL, Rothwell JC, Findley LJ, Marsden CD. Rapid wrist movements in patients with essential tremor. The critical role of the second agonist burst. Brain. 1994;117(Pt 1):3947.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Jung NY, Park CK, Chang WS, Jung HH, Chang JW. Effects on cognition and quality of life with unilateral magnetic resonance-guided focused ultrasound thalamotomy for essential tremor. Neurosurg Focus. 2018;44(2):E8.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Meng Y, Lipsman N. Editorial. Tremor, thalamotomy, and cognition. Neurosurg Focus. 2018;44(2):E9.

  • 9

    Janicki SC, Cosentino S, Louis ED. The cognitive side of essential tremor: what are the therapeutic implications? Ther Adv Neurol Disord. 2013;6(6):353368.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Bhatia KP, Bain P, Bajaj N, et al. Consensus Statement on the classification of tremors. From the Task Force on Tremor of the International Parkinson and Movement Disorder Society. Mov Disord. 2018;33(1):7587.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Huang CC, Hsieh WJ, Lee PL, et al. Age-related changes in resting-state networks of a large sample size of healthy elderly. CNS Neurosci Ther. 2015;21(10):817825.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Damoiseaux JS, Beckmann CF, Arigita EJ, et al. Reduced resting-state brain activity in the “default network” in normal aging. Cereb Cortex. 2008;18(8):18561864.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Bagarinao E, Watanabe H, Maesawa S, et al. Aging impacts the overall connectivity strength of regions critical for information transfer among brain networks. Front Aging Neurosci. 2020;12:592469.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Maesawa S, Mizuno S, Bagarinao E, et al. Resting state networks related to the maintenance of good cognitive performance during healthy aging. Front Hum Neurosci. 2021;15:753836.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Greicius MD, Srivastava G, Reiss AL, Menon V. Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A. 2004;101(13):46374642.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Mulders PC, van Eijndhoven PF, Schene AH, Beckmann CF, Tendolkar I. Resting-state functional connectivity in major depressive disorder: A review. Neurosci Biobehav Rev. 2015;56:330344.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Putcha D, Ross RS, Cronin-Golomb A, Janes AC, Stern CE. Altered intrinsic functional coupling between core neurocognitive networks in Parkinson’s disease. Neuroimage Clin. 2015;7:449455.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Abbott AE, Nair A, Keown CL, et al. Patterns of atypical functional connectivity and behavioral links in autism differ between default, salience, and executive networks. Cereb Cortex. 2016;26(10):40344045.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Maesawa S, Bagarinao E, Nakatsubo D, et al. Multitier network analysis using resting-state functional MRI for epilepsy surgery. Neurol Med Chir (Tokyo). 2022;62(1):4555.

    • PubMed
    • Search Google Scholar
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