VBM Reveals Brain Volume Differences between Parkinson's Disease and Essential Tremor Patients

Cerebellar Structural and N-Acetylaspartate, Choline, and Creatine Metabolic Profiles in Parkinson's Disease and Essential Tremor

BACKGROUND

The role of the cerebellum in Parkinson's disease (PD), particularly in tremor-dominant subtypes, is increasingly recognized. Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) provide anatomical and metabolic insights, suggesting compensatory hyperactivity or degenerative changes in the cerebellum in PD. Volumetric analysis of cerebellar structures in MRI images, combined with metabolic profiles from MRS, offers possibilities for differentiating PD from essential tremor (ET). The cerebellum may be a potential therapeutic target due to its role in neurocircuitry of PD and ET.

METHODS

Brain structural data were obtained using MRI, and cerebellar metabolic profiles, focusing on the quantification of N-acetylaspartate (NAA), choline, and creatine peaks were obtained using MRS. This study enrolled patients with ET and PD, both with and without tremor, as well as disease controls with cerebellar atrophy (including spinocerebellar ataxia and multiple system atrophy). Volumetric analysis of cerebellar structures was performed. Differences in MRI and MRS parameters were analyzed using one-way analysis of covariance with a significance threshold of p < 0.05.

RESULTS

From November 2018 to March 2023, 111 patients were enrolled, including 29 ET, 29 cerebellar atrophy, 12 PD without tremor, and 41 PD with tremor. No significant differences in cerebellar volume and N-acetylaspartate/creatine and choline/creatine ratios were found between ET and PD with tremor.

CONCLUSIONS

This preliminary retrospective study suggests similarities in cerebellar structures and metabolic profiles between ET and PD, highlighting the need for advanced imaging techniques to better differentiate between these conditions. Future research should integrate clinical data, such as tremor severity and cognitive assessments, to explore the relationships with cerebellar MRI parameters.

Prefrontal-Limbic Circuitry Is Associated With Reward Sensitivity in Nonhuman Primates

BACKGROUND

Abnormal reward sensitivity is a risk factor for psychiatric disorders, including eating disorders such as overeating and binge-eating disorder, but the brain structural mechanisms that underlie it are not completely understood. Here, we sought to investigate the relationship between multimodal whole-brain structural features and reward sensitivity in nonhuman primates.

METHODS

Reward sensitivity was evaluated through behavioral economic analysis in which monkeys (adult rhesus macaques; 7 female, 5 male) responded for sweetened condensed milk (10%, 30%, 56%), Gatorade, or water using an operant procedure in which the response requirement increased incrementally across sessions (i.e., fixed ratio 1, 3, 10). Animals were divided into high (n = 6) or low (n = 6) reward sensitivity groups based on essential value for 30% milk. Multimodal magnetic resonance imaging was used to measure gray matter volume and white matter microstructure. Brain structural features were compared between groups, and their correlations with reward sensitivity for various stimuli was investigated.

RESULTS

Animals in the high sensitivity group had greater dorsolateral prefrontal cortex, centromedial amygdaloid complex, and middle cingulate cortex volumes than animals in the low sensitivity group. Furthermore, compared with monkeys in the low sensitivity group, high sensitivity monkeys had lower fractional anisotropy in the left dorsal cingulate bundle connecting the centromedial amygdaloid complex and middle cingulate cortex to the dorsolateral prefrontal cortex, and in the left superior longitudinal fasciculus 1 connecting the middle cingulate cortex to the dorsolateral prefrontal cortex.

CONCLUSIONS

These results suggest that neuroanatomical variation in prefrontal-limbic circuitry is associated with reward sensitivity. These brain structural features may serve as predictive biomarkers for vulnerability to food-based and other reward-related disorders.

Distinguishing essential tremor from Parkinson's disease: clinical and experimental tools

INTRODUCTION

Essential tremor (ET) and Parkinson's disease (PD) are the most common causes of tremor and the most prevalent movement disorders, with overlapping clinical features that can lead to diagnostic challenges, especially in the early stages.

AREAS COVERED

In the present paper, the authors review the clinical and experimental studies and emphasized the major aspects to differentiate between ET and PD, with particular attention to cardinal phenomenological features of these two conditions. Ancillary and experimental techniques, including neurophysiology, neuroimaging, fluid biomarker evaluation, and innovative methods, are also discussed for their role in differential diagnosis between ET and PD. Special attention is given to investigations and tools applicable in the early stages of the diseases, when the differential diagnosis between the two conditions is more challenging. Furthermore, the authors discuss knowledge gaps and unsolved issues in the field.

EXPERT OPINION

Distinguishing ET and PD is crucial for prognostic purposes and appropriate treatment. Additionally, accurate diagnosis is critical for optimizing clinical and experimental research on pathophysiology and innovative therapies. In a few years, integrated technologies could enable accurate, reliable diagnosis from early disease stages or prodromal stages in at-risk populations, but further research combining different techniques is needed.

Differential patterns of functional connectivity in tremor dominant Parkinson's disease and essential tremor plus

Tremor dominant Parkinson's disease (TDPD) and essential tremor plus (ETP) syndrome are commonly encountered tremor dominant neurological disorders. Although the basal ganglia thalamocortical (BGTC) and cerebello thalamocortical (CTC) networks are implicated in tremorogenesis, the extent of functional connectivity alterations across disorders is uncertain. This study aims to evaluate functional connectivity of the BGTC and CTC in TDPD and ETP. Resting state functional MRI was acquired for 25 patients with TDPD, ETP and 22 healthy controls (HC). Following pre-processing and denoising, seed-to-voxel based connectivity was carried out at FDR < 0.05 using ROIs belonging to the BGTC and CTC. Fahn-Tolosa-Marin tremor rating scale (FTMRS) was correlated with the average connectivity values at FDR < 0.05. Compared to HC, TDPD showed decreased connectivity between cerebellum and pre, post central gyrus. While, ETP showed decreased connectivity between pallidum and occipital cortex, precuneus, cuneus compared to HC. In comparison to ETP, TDPD showed increased connectivity between precentral gyrus, pallidum, SNc with the default mode network (DMN), and decreased connectivity between cerebellum with superior, middle frontal gyrus was observed. Tremor severity positively correlated with connectivity between SNc and DMN in TDPD, and negatively correlated with pallidal connectivity in ETP. Pattern of BGTC, CTC involvement is differential i.e., higher connectivity of the BGTC nodes in TDPD, and higher connectivity of cerebellar nodes in ETP. The interesting observation of pallidal involvement in ETP suggests the role of BGTC in the pathogenesis of ETP, and indicated similarities in concepts of tremor genesis in TDPD and ETP.

Combination of static and dynamic neural imaging features to distinguish sensorineural hearing loss: a machine learning study

Purpose

Sensorineural hearing loss (SNHL) is the most common form of sensory deprivation and is often unrecognized by patients, inducing not only auditory but also nonauditory symptoms. Data-driven classifier modeling with the combination of neural static and dynamic imaging features could be effectively used to classify SNHL individuals and healthy controls (HCs).

Methods

We conducted hearing evaluation, neurological scale tests and resting-state MRI on 110 SNHL patients and 106 HCs. A total of 1,267 static and dynamic imaging characteristics were extracted from MRI data, and three methods of feature selection were computed, including the Spearman rank correlation test, least absolute shrinkage and selection operator (LASSO) and t test as well as LASSO. Linear, polynomial, radial basis functional kernel (RBF) and sigmoid support vector machine (SVM) models were chosen as the classifiers with fivefold cross-validation. The receiver operating characteristic curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated for each model.

Results

SNHL subjects had higher hearing thresholds in each frequency, as well as worse performance in cognitive and emotional evaluations, than HCs. After comparison, the selected brain regions using LASSO based on static and dynamic features were consistent with the between-group analysis, including auditory and nonauditory areas. The subsequent AUCs of the four SVM models (linear, polynomial, RBF and sigmoid) were as follows: 0.8075, 0.7340, 0.8462 and 0.8562. The RBF and sigmoid SVM had relatively higher accuracy, sensitivity and specificity.

Conclusion

Our research raised attention to static and dynamic alterations underlying hearing deprivation. Machine learning-based models may provide several useful biomarkers for the classification and diagnosis of SNHL.

Complemental Value of Microstructural and Macrostructural MRI in the Discrimination of Neurodegenerative Parkinson Syndromes

PURPOSE

Various MRI-based techniques were tested for the differentiation of neurodegenerative Parkinson syndromes (NPS); the value of these techniques in direct comparison and combination is uncertain. We thus compared the diagnostic performance of macrostructural, single compartmental, and multicompartmental MRI in the differentiation of NPS.

METHODS

We retrospectively included patients with NPS, including 136 Parkinson's disease (PD), 41 multiple system atrophy (MSA) and 32 progressive supranuclear palsy (PSP) and 27 healthy controls (HC). Macrostructural tissue probability values (TPV) were obtained by CAT12. The microstructure was assessed using a mesoscopic approach by diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and diffusion microstructure imaging (DMI). After an atlas-based read-out, a linear support vector machine (SVM) was trained on a training set (n = 196) and validated in an independent test cohort (n = 40). The diagnostic performance of the SVM was compared for different inputs individually and in combination.

RESULTS

Regarding the inputs separately, we observed the best diagnostic performance for DMI. Overall, the combination of DMI and TPV performed best and correctly classified 88% of the patients. The corresponding area under the receiver operating characteristic curve was 0.87 for HC, 0.97 for PD, 1.0 for MSA, and 0.99 for PSP.

CONCLUSION

We were able to demonstrate that (1) MRI parameters that approximate the microstructure provided substantial added value over conventional macrostructural imaging, (2) multicompartmental biophysically motivated models performed better than the single compartmental DTI and (3) combining macrostructural and microstructural information classified NPS and HC with satisfactory performance, thus suggesting a complementary value of both approaches.

Artificial-intelligence-based MRI brain volumetry in patients with essential tremor and tremor-dominant Parkinson's disease

Essential tremor and Parkinson's disease patients may present with various tremor types. Overlapping tremor features can be challenging to diagnosis and misdiagnosis is common. Although underlying neurodegenerative mechanisms are suggested, neuroimaging studies arrived at controversial results and often the different tremor types were not considered. We investigated whether different tremor types displayed distinct structural brain features. Structural MRI of 61 patients with essential tremor and 29 with tremor-dominant Parkinson's disease was analysed using a fully automated artificial-intelligence-based brain volumetry to compare volumes of several cortical and subcortical regions. Furthermore, essential tremor subgroups with and without rest tremor or more pronounced postural and kinetic tremor were investigated. Deviations from an internal reference collective of age- and sex-adjusted healthy controls and volumetric differences between groups were examined; regression analysis was used to determine the contribution of disease-related factors on volumetric measurements. Compared with healthy controls, essential tremor and tremor-dominant Parkinson's disease patients displayed deviations in the occipital lobes, hippocampus, putamen, pallidum and mesencephalon while essential tremor patients exhibited decreased volumes within the nucleus caudatus and thalamus. Analysis of covariance revealed similar volumetric patterns in both diseases. Essential tremor patients without rest tremor showed a significant atrophy within the thalamus compared to tremor-dominant Parkinson's disease and atrophy of the mesencephalon and putamen were found in both subgroups compared to essential tremor with rest tremor. Disease-related factors contribute to volumes of occipital lobes in both diseases and to volumes of temporal lobes in essential tremor and the putamen in Parkinson's disease. Fully automated artificial-intelligence-based volumetry provides a fast and rater-independent method to investigate brain volumes in different neurological disorders and allows comparisons with an internal reference collective. Our results indicate that essential tremor and tremor-dominant Parkinson's disease share structural changes, indicative of neurodegenerative mechanisms, particularly of the basal-ganglia-thalamocortical circuitry. A discriminating, possibly disease-specific involvement of the thalamus was found in essential tremor patients without rest tremor and the mesencephalon and putamen in tremor-dominant Parkinson's disease and essential tremor without rest tremor.

A systematic comparison of VBM pipelines and their application to age prediction

Voxel-based morphometry (VBM) analysis is commonly used for localized quantification of gray matter volume (GMV). Several alternatives exist to implement a VBM pipeline. However, how these alternatives compare and their utility in applications, such as the estimation of aging effects, remain largely unclear. This leaves researchers wondering which VBM pipeline they should use for their project. In this study, we took a user-centric perspective and systematically compared five VBM pipelines, together with registration to either a general or a study-specific template, utilizing three large datasets (n>500 each). Considering the known effect of aging on GMV, we first compared the pipelines in their ability of individual-level age prediction and found markedly varied results. To examine whether these results arise from systematic differences between the pipelines, we classified them based on their GMVs, resulting in near-perfect accuracy. To gain deeper insights, we examined the impact of different VBM steps using the region-wise similarity between pipelines. The results revealed marked differences, largely driven by segmentation and registration steps. We observed large variability in subject-identification accuracies, highlighting the interpipeline differences in individual-level quantification of GMV. As a biologically meaningful criterion we correlated regional GMV with age. The results were in line with the age-prediction analysis, and two pipelines, CAT and the combination of fMRIPrep for tissue characterization with FSL for registration, reflected age information better.

Structural brain differences in essential tremor and Parkinson's disease deep brain stimulation patients

BACKGROUND

Essential tremor (ET) and Parkinson's disease (PD) are the most common tremor disorders and are common indications for deep brain stimulation (DBS). In some patients, PD and ET symptoms overlap and diagnosis can be challenging based on clinical criteria alone. The objective of this study was to identify structural brain differences between PD and ET DBS patients to help differentiate these disorders and improve our understanding of the different brain regions involved in these pathologic processes.

METHODS

We included ET and PD patients scheduled to undergo DBS surgery in this observational study. Patients underwent 3T brain MRI while under general anesthesia as part of their procedure. Cortical thicknesses and subcortical volumes were quantified from T1-weighted images using automated multi-atlas segmentation. We used logistic regression analysis to identify brain regions associated with diagnosis of ET or PD.

RESULTS

149 ET and 265 PD patients were included. Smaller volumes in the pallidum and thalamus and reduced thickness in the anterior orbital gyrus, lateral orbital gyrus, and medial precentral gyrus were associated with greater odds of ET diagnosis. Conversely, reduced volumes in the caudate, amygdala, putamen, and basal forebrain, and reduced thickness in the orbital part of the inferior frontal gyrus, supramarginal gyrus, and posterior cingulate were associated with greater odds of PD diagnosis.

CONCLUSIONS

These findings identify structural brain differences between PD and ET patients. These results expand our understanding of the different brain regions involved in these disorders and suggest that structural MRI may help to differentiate patients with these two disorders.

Reproducibility of cerebellar involvement as quantified by consensus structural MRI biomarkers in advanced essential tremor

Essential tremor (ET) is the most prevalent movement disorder with poorly understood etiology. Some neuroimaging studies report cerebellar involvement whereas others do not. This discrepancy may stem from underpowered studies, differences in statistical modeling or variation in magnetic resonance imaging (MRI) acquisition and processing. To resolve this, we investigated the cerebellar structural differences using a local advanced ET dataset augmented by matched controls from PPMI and ADNI. We tested the hypothesis of cerebellar involvement using three neuroimaging biomarkers: VBM, gray/white matter volumetry and lobular volumetry. Furthermore, we assessed the impacts of statistical models and segmentation pipelines on results. Results indicate that the detected cerebellar structural changes vary with methodology. Significant reduction of right cerebellar gray matter and increase of the left cerebellar white matter were the only two biomarkers consistently identified by multiple methods. Results also show substantial volumetric overestimation from SUIT-based segmentation-partially explaining previous literature discrepancies. This study suggests that current estimation of cerebellar involvement in ET may be overemphasized in MRI studies and highlights the importance of methods sensitivity analysis on results interpretation. ET datasets with large sample size and replication studies are required to improve our understanding of regional specificity of cerebellum involvement in ET. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 21 March 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.6084/m9.figshare.19697776 .

Postmortem Cerebellar Volume Is Not Reduced in Essential Tremor: A Comparison with Multiple System Atrophy and Controls

BACKGROUND

Essential tremor (ET) is a common movement disorder in which cerebellar microscopic and volume alterations have been repeatedly reported although with disagreement between studies. However, pronounced heterogeneity was found with regard to cerebellar volume alterations.

OBJECTIVE

This study aimed to assess postmortem cerebellar volume in subjects with or without ET, as compared with subjects with multiple system atrophy (MSA), a well-established cerebellar neurodegeneration.

METHODS

Cases with ET (n = 29), MSA (n = 7), and non-demented control cases without any movement disorder (n = 22) were selected from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND), a longitudinal clinicopathological study with annual research-dedicated clinical assessments by neuropsychologists, subspecialist movement disorders, and cognitive/behavioral neurologists, with comprehensive neuropathological examinations after death. Group comparisons were controlled for common age-related neurodegenerative and cerebrovascular pathologies. Cerebellar volumes were calculated using digital images of slices taken at the time of autopsy, immediately after brain removal and before fixation.

RESULTS

Cerebellar volume was not reduced in ET subjects compared to controls. The two groups did not differ in terms of incidental cerebrovascular and Alzheimer's disease neuropathology. In contrast, cerebellar volume was significantly reduced in subjects with MSA when compared to ET and control subjects.

CONCLUSION

In a well-characterized cohort, postmortem cerebellar volume measurements suggest that there are no volume alterations in ET when compared to controls, in contrast to significant cerebellar atrophy in subjects with MSA.

Evaluation of Cerebral Volume Changes in Patients with Tremor Treated by MRgFUS Thalamotomy

The purpose of the study is to quantify volumetric variations of cortical and subcortical brain structures after Vim ablation using MRgFUS, and correlate them with the patients’ clinical features and treatment outcomes. For this pilot retrospective study we enrolled 31 patients with a mean age of 70.86 years who were eligible for unilateral Vim thalamotomy. Clinical evaluation included tremor severity assessment using the FTM scale and cognitive assessment using the MoCA score. MRI data were acquired with a 3T scanner, using a dedicated 32-channel coil and acquiring a volumetric sequence of T1 3D IR FSPGR (BRAVO), before treatment and one year after MRgFUS thalamotomy. Image processing and volume data extraction were conducted with dedicated software. A volumetric analysis showed a significant reduction (p < 0.05) of the left thalamus 1 year after the treatment in patients with ET. Other significant results were found on the same side in the other nuclei of the basal ganglia and in the cerebellar cortex. In confronting the two groups (ET, PD), no significant differences were found in terms of age, FTM, MoCA scores, or brain volumes. Similarly, no significant correlations were found between the FTM and MoCA scores and the brain volumes before the treatment.

Identifying and distinguishing of essential tremor and Parkinson's disease with grouped stability analysis based on searchlight-based MVPA

BACKGROUND

Since both essential tremor (ET) and Parkinson's disease (PD) are movement disorders and share similar clinical symptoms, it is very difficult to recognize the differences in the presentation, course, and treatment of ET and PD, which leads to misdiagnosed commonly.

PURPOSE

Although neuroimaging biomarker of ET and PD has been investigated based on statistical analysis, it is unable to assist the clinical diagnosis of ET and PD and ensure the efficiency of these biomarkers. The aim of the study was to identify the neuroimaging biomarkers of ET and PD based on structural magnetic resonance imaging (MRI). Moreover, the study also distinguished ET from PD via these biomarkers to validate their classification performance.

METHODS

This study has developed and implemented a three-level machine learning framework to identify and distinguish ET and PD. First of all, at the model-level assessment, the searchlight-based machine learning method has been used to identify the group differences of patients (ET/PD) with normal controls (NCs). And then, at the feature-level assessment, the stability of group differences has been tested based on structural brain atlas separately using the permutation test to identify the robust neuroimaging biomarkers. Furthermore, the identified biomarkers of ET and PD have been applied to classify ET from PD based on machine learning techniques. Finally, the identified biomarkers have been compared with the previous findings of the biology-level assessment.

RESULTS

According to the biomarkers identified by machine learning, this study has found widespread alterations of gray matter (GM) for ET and large overlap between ET and PD and achieved superior classification performance (PCA + SVM, accuracy = 100%).

CONCLUSIONS

This study has demonstrated the significance of a machine learning framework to identify and distinguish ET and PD. Future studies using a large data set are needed to confirm the potential clinical application of machine learning techniques to discern between PD and ET.

Morphological and morphometric changes in the Purkinje cells of patients with essential tremor

Essential tremor (ET) is a progressive neurological syndrome characterised by involuntary tremors of the hands or arms, head, jaw and voice. The pathophysiology of ET is not clearly understood yet. However, previous studies have reported several changes in the brain of patients with ET. One of the brain areas extensively investigated is the cerebellum. In the present study, a morphometric analysis of Purkinje cells in patients with ET and ET-plus was performed, and subsequently compared with normal controls using the Golgi silver staining method and 3D neuronal reconstruction. Substantial morphological changes were uncovered in the Purkinje cells of patients with ET compared with normal controls, including a decreased dendritic length and field density, an overall loss of terminal branches and a decreased density of dendritic spines.

The Contribution of Neuroimaging to the Understanding of Essential Tremor Pathophysiology: a Systematic Review

Essential tremor (ET) is one of the most common movement disorders. Over the last 10 years, magnetic resonance imaging (MRI) has shed light on the structural and functional abnormalities possibly involved in ET pathophysiology. In this systematic review, we aimed to identify the cortical and subcortical structures involved and the role that different brain areas play in the pathophysiology of motor and non-motor ET features. We found that structural (grey and white matter) cerebellar damage and connectivity alterations between the cerebellum and various cortical areas play a role in both motor and non-motor symptoms of ET. In particular, many studies found an association between MRI findings and non-motor symptoms.

Differentiating Parkinson's disease motor subtypes: A radiomics analysis based on deep gray nuclear lesion and white matter

OBJECTIVE

To investigate the feasibility of radiomics analysis of brain MR images to differentiate Parkinson's disease motor subtypes.

METHODS

42 postural instability gait difficulty (PIGD) patients, 92 tremor-dominant (TD) patients and 96 healthy controls were included from the Parkinson's Progressive Marker Initiative public database. For each subject, 4850 radiomic features from 148 cortical and 14 subcortical brain regions were extracted. The variance threshold and the least absolute shrinkage and selection operator were used to select the optimal features. Classification models based on Support Vector Machine, Logistic Regrcession, and Multi-Layer Perceptron were constructed to assess the performance of optimal features in the discrimination of the two subtypes. Correlations between radiomic features and clinical scores of the two subtypes were estimated.

RESULTS

The Support Vector Machine demonstrated the best performance in discriminating between the two subtypes, and the mean area under the curve was 0.833 (specificity = 83.3%, sensitivity = 75.0%, and accuracy = 80.7%). For the postural instability gait difficulty patients, these optimal features in the hippocampal showed closed correlations with the Montreal Cognitive Assessment scores (P < 0.05).

CONCLUSION

The results of our study provide preliminary evidence that radiomics analysis of brain MR images could allow discrimination between patients with TD, PIGD and control subjects and has great potential value in the clinical practice.

Imaging the Pathophysiology of Essential Tremor-A Systematic Review

Background: The pathophysiology underlying essential tremor (ET) still is poorly understood. Recent research suggests a pivotal role of the cerebellum in tremor genesis, and an ongoing controversy remains as to whether ET constitutes a neurodegenerative disorder. In addition, mounting evidence indicates that alterations in the gamma-aminobutyric acid neurotransmitter system are involved in ET pathophysiology. Here, we systematically review structural, functional, and metabolic neuroimaging studies and discuss current concepts of ET pathophysiology from an imaging perspective. Methods: We conducted a PubMed and Scopus search from 1966 up to December 2020, entering essential tremor in combination with any of the following search terms and their corresponding abbreviations: positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and gamma-aminobutyric acid (GABA). Results: Altered functional connectivity in the cerebellum and cerebello-thalamico-cortical circuitry is a prevalent finding in functional imaging studies. Reports from structural imaging studies are less consistent, and there is no clear evidence for cerebellar neurodegeneration. However, diffusion tensor imaging robustly points toward microstructural cerebellar changes. Radiotracer imaging suggests that the dopaminergic axis is largely preserved in ET. Similarly, measurements of nigral iron content and neuromelanin are unremarkable in most studies; this is in contrast to Parkinson's disease (PD). PET and MRS studies provide limited evidence for cerebellar and thalamic GABAergic dysfunction. Conclusions: There is robust evidence indicating that the cerebellum plays a key role within a multiple oscillator tremor network which underlies tremor genesis. However, whether cerebellar dysfunction relies on a neurodegenerative process remains unclear. Dopaminergic and iron imaging do not suggest a substantial overlap of ET with PD pathophysiology. There is limited evidence for alterations of the GABAergic neurotransmitter system in ET. The clinical, demographical, and genetic heterogeneity of ET translates into neuroimaging and likely explains the various inconsistencies reported.

Anatomical texture patterns identify cerebellar distinctions between essential tremor and Parkinson's disease

Voxel-based morphometry is an established technique to study focal structural brain differences in neurologic disease. More recently, texture-based analysis methods have enabled a pattern-based assessment of group differences, at the patch level rather than at the voxel level, allowing a more sensitive localization of structural differences between patient populations. In this study, we propose a texture-based approach to identify structural differences between the cerebellum of patients with Parkinson's disease (n = 280) and essential tremor (n = 109). We analyzed anatomical differences of the cerebellum among patients using two features: T1-weighted MRI intensity, and a texture-based similarity feature. Our results show anatomical differences between groups that are localized to the inferior part of the cerebellar cortex. Both the T1-weighted intensity and texture showed differences in lobules VIII and IX, vermis VIII and IX, and middle peduncle, but the texture analysis revealed additional differences in the dentate nucleus, lobules VI and VII, vermis VI and VII. This comparison emphasizes how T1-weighted intensity and texture-based methods can provide a complementary anatomical structure analysis. While texture-based similarity shows high sensitivity for gray matter differences, T1-weighted intensity shows sensitivity for the detection of white matter differences.

A Voxel-Wise Meta-Analysis on the Cerebellum in Essential Tremor

Background and Objectives: Essential tremor is a chronic progressive neurological condition. The clinical presentation of essential tremor is heterogeneous and includes involuntary tremor on hands or arms and progressively on head, jaw, and voice. More extensive and complex symptoms may also be noticed in several patients. Many studies have been carried out to identify biomarkers to help the diagnosis, however, all the efforts have not shown any substantial results yet. Materials and Methods: Here, we aimed to perform a voxel-based meta-analysis using a dedicated cerebellar mask to clarify whether the results from the previous studies are robust and have any clinical significance. We included studies with a total of 377 essential tremor patients and 338 healthy control individuals. Results: A significant regional decrease in the volume of the gray matter was detected in the right cerebellar hemispheric lobule IV/V, and in the cerebellar vermic lobule IV/V. Conclusions: This is the first study focused on the cerebellum and using a specific cerebellar mask, which increases the sensitivity. It showed regional statistically significant changes that could not be seen in the whole-brain analysis.

Impaired integrity of commissural and association fibers in essential tremor patients: Evidence from a diffusion tensor imaging study

Background/aim

The evolving understanding of essential tremors (ET) has led to a new definition of neurodegenerative disease, pointing to diffuse brain network involvement with a wide spectrum of associated motor and nonmotor symptoms. Considering the fact that white matter should also be affected by the nature of the disease, our study aimed to evaluate the integrity of white matter and its clinical correlations in ET patients.

Materials and methods

Approximately 40 patients diagnosed with ET and 40 age-and sex-matched control subjects (ranging between 18–80 years old) were included in the study. The sociodemographic characteristics and clinical features of the patients were recorded. Tremors were assessed using the Fahn-Tolosa-Marin Tremor Rating Scale (FTM-TRS). Diffusion Tensor Imaging (DTI) was performed to evaluate the integrity of white matter. The selected white matter regions used for DTI assessment were the corpus callosum (CC) (i.e., the largest commissural tract in the human brain), the superior longitudinal fasciculus (SLF), and the inferior longitudinal fasciculus (ILF) (i.e., the largest association fiber bundles).

Results

The mean age of the ET patients and control subjects was 44.23 ± 18.91 and 37.45 ± 10.95 years old (P = 0.542). The fractional anisotropy (FA) values of the CC body (P = 0.003), ILF (p = 0.016), average diffusion coefficient (ADC) values of the CC body (p = 0.001), genu (P = 0.049), SLF (V < 0.001), and ILF (P < 0.001) differed between groups. After controlling for age and sex, there was no correlation between tremor severity and DTI parameters, but impaired integrity in the genu of CC FA (P = 0.035, r = 0.442) and the splenium of CC ADC (P = 0.007, r = 0.543) were related with a longer duration of tremor. Finally, positive family history was correlated with the splenium of CC FA and ADC (P = 0.008, r = 0.536; P = 0.027, r = 0.461) and ILF ADC (P = 0.011, r = –0.519).

Conclusion

In our study, major white matter structure changes were found in the ET patients. The results suggest that possible neurodegeneration also affects white matter structures in ET patients and that the duration of the tremor and family history are related with impaired integrity of white matter.

Increased Left Putamen Volume Correlates With Pain in Ankylosing Spondylitis Patients

Ankylosing spondylitis (AS) mainly affects the axial skeleton and is an important factor leading to chronic lower back pain in young individuals. However, few studies have explored alterations of brain gray matter volume in AS patients. The purpose of the present study was to describe brain gray matter abnormalities associated with AS pain. A total of 61 AS patients and 52 healthy controls (HCs) were included in this study. Using voxel-based morphometrics, we detected abnormal gray matter volume in AS patients. Based on the voxel-wise analysis, the gray matter volume in the left putamen of the AS group was increased significantly compared with that of the HC group. In addition, we found that the gray matter volume of the left putamen was positively correlated with the duration of AS and total back pain scores, whereas it was not significantly correlated with Bath Ankylosing Spondylitis Disease Activity Index scores, C-reactive protein, or erythrocyte sedimentation rate in AS patients. Taken together, our findings improve our understanding of the neural substrates of pain in AS and provide evidence of AS-related neurological impairment. Hence, further investigation of the pathophysiology of the left putamen in AS is warranted.

Voxel-based morphometry and task functional magnetic resonance imaging in essential tremor: evidence for a disrupted brain network

The pathophysiology of essential tremor (ET) is controversial and might be further elucidated by advanced neuroimaging. Focusing on homogenous ET patients diagnosed according to the 2018 consensus criteria, this study aimed to: (1) investigate whether task functional MRI (fMRI) can identify networks of activated and deactivated brain areas, (2) characterize morphometric and functional modulations, relative to healthy controls (HC). Ten ET patients and ten HC underwent fMRI while performing two motor tasks with their upper limb: (1) maintaining a posture (both groups); (2) simulating tremor (HC only). Activations/deactivations were obtained from General Linear Model and compared across groups/tasks. Voxel-based morphometry and linear regressions between clinical and fMRI data were also performed. Few cerebellar clusters of gray matter loss were found in ET. Conversely, widespread fMRI alterations were shown. Tremor in ET (task 1) was associated with extensive deactivations mainly involving the cerebellum, sensory-motor cortex, and basal ganglia compared to both tasks in HC, and was negatively correlated with clinical tremor scales. Homogeneous ET patients demonstrated deactivation patterns during tasks triggering tremor, encompassing a network of cortical and subcortical regions. Our results point towards a marked cerebellar involvement in ET pathophysiology and the presence of an impaired cerebello-thalamo-cortical tremor network.

Prodromal Markers of Parkinson's Disease in Patients With Essential Tremor

Background: Essential tremor (ET) is manifested as an isolated syndrome of bilateral upper limb action tremor. Parkinson's disease (PD) is the second most common neurodegenerative disease, with typical motor symptoms of bradykinesia, rigidity, and resting tremor. ET-PD describes the new-onset of PD in ET patients. Recently, numerous studies on epidemiology, genetics, pathology, clinical features, and neuroimaging studies are challenging the idea that ET is an isolated disease, suggesting that patients with ET have the tendency to develop PD. Methods: In this review article, we collected recent findings that reveal prodromal markers of PD in patients with ET. Results: Substantia nigra hyperechogenicity serves as a prodromal marker for predicting the development of PD in patients with ET and provides a reference for therapeutic strategies. Additional potential markers include other neuroimaging, clinical features, heart rate, and genetics, whereas others lack sufficient evidence. Conclusion: In consideration of the limited research of PD in patients with ET, we are still far from revealing the prodromal markers. However, from the existing follow-up studies on ET patients, Substantia nigra hyperechogenicity may enable further exploration of the relationship between ET and PD and the search for pathogenesis-based therapies.

Essential tremor: the most common form of cerebellar degeneration?

Background

The degenerative cerebellar ataxias comprise a large and heterogeneous group of neurological diseases whose hallmark clinical feature is ataxia, and which are accompanied, to variable degrees, by other features that are attributable to cerebellar dysfunction. Essential tremor (ET) is an exceptionally common neurological disease whose primary motor feature is action tremor, although patients often manifest intention tremor, mild gait ataxia and several other features of cerebellar dysfunction.

Main Body

In this paper, we review the abundant evidence derived from clinical, neuroimaging and postmortem studies, linking ET to cerebellar dysfunction. Furthermore, we review the combination of clinical, natural history and postmortem features suggesting that ET is neurodegenerative. We then compare the prevalence of ET (400 – 900 cases per 100,000) to that of the other cerebellar degenerations (ranging from <0.5 – 9 cases per 100,000, and in composite likely to be on the order of 20 cases per 100,000) and conclude that ET is 20 to 45 times more prevalent than all other forms of cerebellar degeneration combined.

Conclusion

Given the data we present, it is logical to conclude that ET is, by far, the most common form of cerebellar degeneration.

Structural Correlates of the Sensorimotor Cerebellum in Parkinson's Disease and Essential Tremor

BACKGROUND

Parkinson's disease (PD) and essential tremor (ET) are commonly encountered movement disorders. Pathophysiologic processes that localize to the cerebellum are described in both. There are limited studies investigating cerebellar structural changes in these conditions, largely because of inherent challenges in the efficiency of segmentation.

METHODS

We applied a novel multiatlas cerebellar segmentation method to T1-weighted images in 282 PD and 111 essential tremor patients to define 26 cerebellar lobule volumes. The severity of postural and resting tremor in both populations and gait and postural instability in PD patients were defined using subscores of the UPDRS and Washington Heights-Inwood Genetic Study motor scales. These clinical measurements were related to lobule volume size. Multiple comparisons were controlled using a false discovery rate method.

RESULTS

Group differences were identified between ET and PD patients, with reductions in deep cerebellar nucleus volume in ET versus reduced lobule VI volume in PD. In ET patients, lobule VIII was negatively correlated with the severity of postural tremor. In PD patients, lobule IV was positively correlated with resting tremor and total tremor severity. We observed differences in cerebellar structure that localized to sensorimotor lobules of the cerebellum. Lobule volumes appeared to differentially relate to clinical symptoms, suggesting important clinicopathologic distinctions between these conditions. These results emphasize the role of the cerebellum in tremor symptoms and should foster future clinical and pathologic investigations of the sensorimotor lobules of the cerebellum. © 2020 International Parkinson and Movement Disorder Society.

Brain structural alterations are distributed following functional, anatomic and genetic connectivity

The pathological brain is characterized by distributed morphological or structural alterations in the grey matter, which tend to follow identifiable network-like patterns. We analysed the patterns formed by these alterations (increased and decreased grey matter values detected with the voxel-based morphometry technique) conducting an extensive transdiagnostic search of voxel-based morphometry studies in a large variety of brain disorders. We devised an innovative method to construct the networks formed by the structurally co-altered brain areas, which can be considered as pathological structural co-alteration patterns, and to compare these patterns with three associated types of connectivity profiles (functional, anatomical, and genetic). Our study provides transdiagnostical evidence that structural co-alterations are influenced by connectivity constraints rather than being randomly distributed. Analyses show that although all the three types of connectivity taken together can account for and predict with good statistical accuracy, the shape and temporal development of the co-alteration patterns, functional connectivity offers the better account of the structural co-alteration, followed by anatomic and genetic connectivity. These results shed new light on the possible mechanisms at the root of neuropathological processes and open exciting prospects in the quest for a better understanding of brain disorders.

Neuroimaging and neuropathological findings in essential tremor

Essential tremor is a chronic neurological syndrome of heterogenous clinical phenotypes and multiple etiologies. Numerous studies have been done in order to investigate the pathological, neuroimaging, physiological, and clinical features of essential tremor; however, a clear pathophysiological mechanism has not been identified. One of the brain structures has been extensively investigated at the macroscopic and the microscopic level in the cerebellum. In the present study, we aim to discuss the main neuroimaging and neuropathological changes of the cerebellum in essential tremor.

White matter rather than gray matter damage characterizes essential tremor

OBJECTIVES

We investigated changes in gray matter (GM) and white matter (WM) in the whole brain, including both cortical and subcortical structures, and their relationship with tremor severity, psychiatric symptoms, and cognitive impairment in patients affected by essential tremor (ET).

METHODS

We studied 19 ET patients and 15 healthy subjects (HS). All the subjects underwent a 3-T MRI study based on 3D-T1 and diffusion tensor images. For the GM analysis, cortical thickness was assessed by using the Computational Anatomy Tool, basal ganglia and thalamus volumes by using the FMRIB software library, and cerebellum lobular volumes by using the spatial unbiased atlas template. For the WM assessment, we performed a voxel-wise analysis by means of tract-based spatial statistics. Patients' tremor severity and psychiatric and cognitive disorders were evaluated by means of standard clinical scales. Neuroimaging data were correlated with clinical scores.

RESULTS

We found significantly smaller right and left thalamic volumes in ET patients than in HS, which correlated with cognitive scores. We did not observe any significant differences either in cortical thickness or in cerebellar lobular volumes between patients and HS. WM abnormalities were detected in most hemisphere bundles, particularly in the corticospinal tract, cerebellar peduncles, and corpus callosum. The WM abnormalities significantly correlated with tremor severity, cognitive profile, and depression.

CONCLUSION

Our study indicates that ET is characterized by several GM and WM changes of both infra- and supratentorial brain structures. The results may help to better understand mechanisms underlying tremor severity and psychiatric and cognitive impairment in ET.

KEY POINTS

• We performed a comprehensive evaluation of gray and white matter in the same sample of patients with essential tremor using recently developed data analysis methods. • Essential tremor is characterized by widespread gray and white matter changes in both infra- and supratentorial brain structures. The results may help to better understand motor and non-motor symptoms in patients with essential tremor.

No reliable gray matter changes in essential tremor

BACKGROUND

Voxel-based morphometry (VBM) has been used to study human brain gray matter (GM) alterations in essential tremor (ET) for over one decade. However, the literature revealed heterogeneous findings.

METHODS

We therefore conducted a coordinate-based meta-analysis to synthesize the VBM studies to examine which brain regions show the most reliable GM alterations in patients with ET relative to healthy controls.

RESULTS

A total of 16 original VBM studies, comprising 387 patients with ET and 355 healthy controls, were included in this meta-analysis. This quantitative meta-analysis revealed no evidence of robust and reliable alterations in regional brain GM structures in ET. Meta-regression analyses indicate that many moderators (e.g., MR field strength, statistical methodology, age, onset age, gender, illness severity, illness duration, and family history) account for some of the heterogeneity in GM across studies.

CONCLUSIONS

High heterogeneity in GM alterations across studies may reflect true heterogeneity in ET regarding the clinic, etiology, and pathology, as well as possibly the VBM methodological variations. Currently, this heterogeneity limits the use of VBM as a reliable tool to distinguish ET from healthy controls. In order to improve reproducibility of VBM results in ET, future research may benefit from increasing the sample size, comprehensively subtyping ET phenotypes, and using well-designed and standardized imaging acquisition and analytical protocols. Furthermore, data sharing should be considered as a high priority.

Dissociation between Cerebellar and Cerebral Neural Activities in Humans with Long-Term Bilateral Sensorineural Hearing Loss

Abnormal neural activity in the cerebellum has been implicated in hearing impairments, but the effects of long-term hearing loss on cerebellar function are poorly understood. To further explore the role of long-term bilateral sensorineural hearing loss on cerebellar function, we investigated hearing loss-induced changes among neural networks within cerebellar subregions and the changes in cerebellar-cerebral connectivity patterns using resting-state functional MRI. Twenty-one subjects with long-term bilateral moderate-to-severe sensorineural hearing loss and 21 matched controls with clinically normal hearing underwent MRI scanning and a series of neuropsychological tests targeting cognition and emotion. Voxel-wise functional connectivity (FC) analysis demonstrated decreased couplings between the cerebellum and other cerebral areas, including the temporal pole (TP), insula, supramarginal gyrus, inferior frontal gyrus (IFG), medial frontal gyrus, and thalamus, in long-term bilateral sensorineural hearing loss patients. An ROI-wise FC analysis found weakened interregional connections within cerebellar subdivisions. Moreover, there was a negative correlation between anxiety and FC between the left cerebellar lobe VI and left insula. Hearing ability and anxiety scores were also correlated with FC between the left cerebellar lobe VI and left TP, as well as the right cerebellar lobule VI and left IFG. Our results suggest that sensorineural hearing loss disrupts cerebellar-cerebral circuits, some potentially linked to anxiety, and interregional cerebellar connectivity. The findings contribute to a growing body showing that auditory deprivation caused by cochlear hearing loss disrupts not only activity with the classical auditory pathway but also portions of the cerebellum that communicates with other cortical networks.

FDG-PET hypometabolism is more sensitive than MRI atrophy in Parkinson's disease: A whole-brain multimodal imaging meta-analysis

Recently, revised diagnostic criteria for Parkinson's disease (PD) were introduced (Postuma et al., 2015). Yet, except for well-established dopaminergic imaging, validated imaging biomarkers for PD are still missing, though they could improve diagnostic accuracy. We conducted systematic meta-analyses to identify PD-specific markers in whole-brain structural magnetic resonance imaging (MRI), [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) and diffusion tensor imaging (DTI) studies. Overall, 74 studies were identified including 2323 patients and 1767 healthy controls. Studies were first grouped according to imaging modalities (MRI 50; PET 14; DTI 10) and then into subcohorts based on clinical phenotypes. To ensure reliable results, we combined established meta-analytical algorithms - anatomical likelihood estimation and seed-based D mapping - and cross-validated them in a conjunction analysis. Glucose hypometabolism was found using FDG-PET extensively in bilateral inferior parietal cortex and left caudate nucleus with both meta-analytic methods. This hypometabolism pattern was confirmed in subcohort analyses and related to cognitive deficits (inferior parietal cortex) and motor symptoms (caudate nucleus). Structural MRI showed only small focal gray matter atrophy in the middle occipital gyrus that was not confirmed in subcohort analyses. DTI revealed fractional anisotropy reductions in the cingulate bundle near the orbital and anterior cingulate gyri in PD. Our results suggest that FDG-PET reliably identifies consistent functional brain abnormalities in PD, whereas structural MRI and DTI show only focal alterations and rather inconsistent results. In conclusion, FDG-PET hypometabolism outperforms structural MRI in PD, although both imaging methods do not offer disease-specific imaging biomarkers for PD.

Performance analysis of different classification algorithms using different feature selection methods on Parkinson's disease detection

BACKGROUND

In diagnosis of neurodegenerative diseases, the three-dimensional magnetic resonance imaging (3D-MRI) has been heavily researched. Parkinson's disease (PD) is one of the most common neurodegenerative disorders.

NEW METHOD

The performances of five different classification approaches using five different attribute rankings each followed with an adaptive Fisher stopping criteria feature selection (FS) method are evaluated. To improve the performance of PD detection, a source fusion technique which combines the gray matter (GM) and white (WM) tissue maps and a decision fusion technique which combines the outputs of all classifiers using the correlation-based feature selection (CFS) method by majority voting are used.

RESULTS

Among the five FS methods, the CFS provides the highest results for all five classification algorithms and the SVM provides the best classification performances for all five different FS methods. The classification accuracy of 77.50% and 81.25% are obtained for the GM and WM tissues, respectively. However, the fusion of GM and WM datasets improves the classification accuracy of the proposed methodology up to 95.00%.

COMPARISON WITH EXISTING METHODS

An f-contrast is used to generate 3D masks for GM and WM datasets and a fusion technique, combining the GM and WM datasets is used. Several classification algorithms using several FS methods are performed and a decision fusion technique is used.

CONCLUSIONS

Using the combination of the 3D masked GM and WM tissue maps and the fusion of the outputs of multiple classifiers with CFS method gives the classification accuracy of 95.00%.

Considering total intracranial volume and other nuisance variables in brain voxel based morphometry in idiopathic PD

Voxel-based morphometry (VBM) studies of Parkinson's disease (PD), have yielded mixed results, possibly due to several studies not accounting for common nuisance variables (age, sex, and total intracranial volume [TICV]). TICV is particularly important because there is evidence for larger TICV in PD. We explored the influence of these covariates on VBM by 1) comparing PD patients and controls before adding covariates, after adding age and sex, and after adding age, sex and TICV, and 2) by comparing controls split into large and small TICV before and after controlling for TICV, with age and sex accounted for in both analyses. Experiment 1 consisted of 40 PD participants and 40 controls. Experiment 2 consisted of 88 controls median split by TICV. All participants completed an MRI on a 3 T scanner. TICV was calculated as gray + white + CSF from Freesurfer. VBM was performed on T1 images using an optimized VBM protocol. Volume differences were assessed using a voxel-wise GLM analysis. Clusters were considered significant at >10 voxels and p < .05 corrected for familywise error. Before controlling for covariates, PD showed reduced GM in temporal, occipital, and cerebellar regions. Controlling for age and sex did not affect the pattern of significance. Controlling for TICV reduced the size of the significant region although it still contained portions of bilateral temporal lobes, occipital lobes and cerebellum. The large TICV group showed reduced volume in temporal, parietal, and cerebellar areas. None of these differences survived controlling for TICV. This demonstrates that TICV influences VBM results independently from other factors. Controlling for TICV in VBM studies is recommended.

Resting-state fMRI study on drug-naive patients of essential tremor with and without head tremor

This study used resting-state functional MRI (r-fMRI) to evaluate intrinsic brain activity in drug-naive patients with essential tremor (ET) with and without head tremor. We enrolled 20 patients with ET with hand and head tremor (h-ET), 27 patients with ET without head tremor (a-ET), and 27 healthy controls (HCs). All participants underwent r-fMRI scans on a 3-T MR system. The amplitude of low-frequency fluctuation (ALFF) of blood oxygen level-dependent signals was used to characterize regional cerebral function. We identified increased ALFF value in the bilateral posterior lobe of cerebellum in the h-ET patients relative to a-ET and HCs and demonstrated that h-ET is related to abnormalities in the cerebello-cortical areas, while the a-ET is related to abnormalities in the thalamo-cortical areas. In addition, we observed the ALFF abnormality in the cerebellum (left cerebellum VIII and right cerebellum VI) correlated with the tremor score in h-ET patients and abnormal ALFF in the left precentral gyrus correlated with the age at onset and disease duration in h-ET patients. These findings may be helpful for facilitating further understanding of the potential mechanisms underlying different subtypes of ET.

Resting state fMRI reveals the altered synchronization of BOLD signals in essential tremor

Essential tremor (ET) is one of the most common movement disorders in humans. Nevertheless, there remain several controversies surrounding ET, such as whether it is a disorder of abnormal neuronal oscillations within the tremor network. In this work, the resting-state fMRI data were collected from 17 ET patients and 17 age- and gender-matched healthy controls. First, using FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) the abnormal synchronization of fMRI signals in ET patients were investigated. Then, global functional connectivity intensity (gFCI) and density (gFCD) were analyzed in the regions exhibiting significant FOCA differences. Compared with healthy controls, patients with ET showed the increased FOCA values found in the bilateral cuneus, the left lingual gyrus, the left paracentral lobule, the right middle temporal gyrus, the bilateral precentral gyrus, the right postcentral gyrus, the pallidum and putamen. Decreased FOCA values in ET patients were located in the frontal gyrus, the bilateral anterior cingulate and the medial dorsal nucleus of right thalamus. In ET patients, significant changes in gFCI and gFCD were located in the cuneus, the middle temporal gyrus and the middle frontal gyrus. Changes in gFCI were also found in the medial frontal gyrus and thalamus in addition to changes in gFCD in the precentral gyrus. Our results provided further evidence that ET might present with abnormal spontaneous activity in the tremor network, including motor-related cotex, basal ganglia and thalamus, as well as distributed non-motor areas. This work also demonstrated that FOCA and functional connectivity have the potential to provide important insight into the pathophysiological mechanism of ET.

A Voxel-Wise Meta-Analysis of Gray Matter Abnormalities in Essential Tremor

Objective: To identify the consistent gray matter (GM) volume changes from the whole brain voxel-based morphometry (VBM) studies on essential tremor (ET).

Methods: The whole brain VBM studies comparing ET patients and healthy controls (HCs) were systematically searched in the PubMed, Embase and Web of Science from January 2000 to December 2017. Coordinates with significant differences in regional GM volume between ET patients and HCs were extracted from included studies and the meta-analysis was performed using effect size-based signed differential mapping (ES-SDM).

Results: A total of 10 studies with 241 ET patients and 213 HCs were included in the meta-analysis. The consistent GM volume reduction was detected in the left precuneus extending to the left posterior cingulate gyrus. The subgroup meta-analysis which included studies performed on a 3.0 T scanner revealed significant GM volume increases in the bilateral frontal lobes, bilateral temporal lobes, left insula, left striatum and left pons, but obvious publication biases of these findings were detected through funnel plots and Egger's tests.

Conclusions: The consistent result of our meta-analysis showed a structural damage in the left precuneus extending to the left posterior cingulate gyrus, which possibly played a role in the cognitive dysfunction and depression in ET patients. It might enhance our understanding of the pathophysiological mechanisms underlying ET.

Cerebral gray matter volume losses in essential tremor: A case-control study using high resolution tissue probability maps

INTRODUCTION

Essential tremor (ET) is increasingly recognized as a multi-dimensional disorder with both motor and non-motor features. For this reason, imaging studies are more broadly examining regions outside the cerebellar motor loop. Reliable detection of cerebral gray matter (GM) atrophy requires optimized processing, adapted to high-resolution magnetic resonance imaging (MRI). We investigated cerebral GM volume loss in ET cases using automated segmentation of MRI T1-weighted images.

METHODS

MRI was acquired on 47 ET cases and 36 controls. Automated segmentation and voxel-wise comparisons of volume were performed using Statistical Parametric Mapping (SPM) software. To improve upon standard protocols, the high-resolution International Consortium for Brain Mapping (ICBM) 2009a atlas and tissue probability maps were used to process each subject image. Group comparisons were performed: all ET vs. Controls, ET with head tremor (ETH) vs. Controls, and severe ET vs. Controls. An analysis of variance (ANOVA) was performed between ET with and without head tremor and controls. Age, sex, and Montreal Cognitive Assessment (MoCA) score were regressed out from each comparison.

RESULTS

We were able to consistently identify regions of cerebral GM volume loss in ET and in ET subgroups in the posterior insula, superior temporal gyri, cingulate cortex, inferior frontal gyri and other occipital and parietal regions. There were no significant increases in GM volume in ET in any comparisons with controls.

CONCLUSION

This study, which uses improved methodologies, provides evidence that GM volume loss in ET is present beyond the cerebellum, and in fact, is widespread throughout the cerebrum as well.

Cerebellar Atrophy in Cortical Myoclonic Tremor and Not in Hereditary Essential Tremor-a Voxel-Based Morphometry Study

Essential tremor (ET) presumably has a cerebellar origin. Imaging studies showed various cerebellar and also cortical structural changes. A number of pathology studies indicated cerebellar Purkinje cell pathology. ET is a heterogeneous disorder, possibly indicating different underlying disease mechanisms. Familial cortical myoclonic tremor with epilepsy (FCMTE), with evident Purkinje cell degeneration, can be an ET mimic. Here, we investigate whole brain and, more specifically, cerebellar morphological changes in hereditary ET, FCMTE, and healthy controls. Anatomical magnetic resonance images were preprocessed using voxel-based morphometry. Study 1 included voxel-wise comparisons of 36 familial, propranolol-sensitive ET patients, with subgroup analysis on age at onset and head tremor, and 30 healthy controls. Study 2 included voxel-wise comparisons in another nine ET patients, eight FCMTE patients, and nine healthy controls. Study 3 compared total cerebellar volume between 45 ET patients, 8 FCTME patients, and 39 controls. In our large sample of selected hereditary ET patients and ET subgroups, no local atrophy was observed compared to healthy controls or FCMTE. In ET patients with head tremor, a volume increase in cortical motor regions was observed. In FCMTE, a decrease in total cerebellar volume and in local cerebellar gray matter was observed compared to healthy controls and ET patients. The current study did not find local atrophy, specifically not in the cerebellum in hereditary ET, contrary to FCMTE. Volume increase of cortical motor areas in ET patients with head tremor might suggest cortical plasticity changes due to continuous involuntary head movements.

The Olivary Hypothesis of Essential Tremor: Time to Lay this Model to Rest?

BACKGROUND

Although essential tremor (ET) is the most common tremor disorder, its pathogenesis is not fully understood. The traditional model of ET, proposed in the early 1970s, posited that the inferior olivary nucleus (ION) was the prime generator of tremor in ET and that ET is a disorder of electrophysiological derangement, much like epilepsy. This article comprehensively reviews the origin and basis of this model, its merits and problems, and discusses whether it is time to lay this model to rest.

METHODS

A PubMed search was performed in March 2017 to identify articles for this review.

RESULTS

The olivary model gains support from the recognition of neurons with pacemaker property in the ION and the harmaline-induced tremor models (as the ION is the prime target of harmaline). However, the olivary model is problematic, as neurons with pacemaker property are not specific to the ION and the harmaline model does not completely represent the human disease ET. In addition, a large number of neuroimaging studies in ET have not detected structural or functional changes in the ION; rather, abnormalities have been reported in structures related to the cerebello-thalamo-cortical network. Moreover, a post-mortem study of microscopic changes in the ION did not detect any differences between ET cases and controls.

DISCUSSION

The olivary model largely remains a physiological construct. Numerous observations have cast considerable doubt as to the validity of this model in ET. Given the limitations of the model, we conclude that it is time now to lay this model to rest.

Gray matter density loss in essential tremor: a lobule by lobule analysis of the cerebellum

Background

The pathophysiological basis for essential tremor (ET) remains unclear, although evidence increasingly links it to a disordered and perhaps degenerative cerebellum. Prior imaging studies have treated the cerebellum en bloc. Our hypothesis was that regional differences in cerebellar gray matter (GM) density may better distinguish ET cases from controls.

Forty-seven ET cases and 36 control subjects were imaged using magnetic resonance imaging (MRI). The cerebellum was segmented into 34 lobes using a Spatially Unbiased Infra-Tentorial Template (SUIT) atlas within the Statistical Parametric Mapping (SPM) analysis package. Age, gender and Montreal Cognitive Assessment (MoCA) scores were regressed out from the statistical models to isolate group effects. ET cases were further stratified into phenotypically-defined subgroups. The Benjamini-Hochberg False Discovery Rate procedure (BH FDR) (α = 0.1) was used to correct for multiple comparisons.

Results

When all ET cases and controls were compared, none of the regions met the BH FDR criteria for significance. When compared with controls, ET cases with head or jaw tremor (n = 27) had significant changes in GM density in nine cerebellar lobules, with a majority in the left cerebellar region, and each meeting the BH FDR criteria. Likewise, ET cases with voice tremor (n = 22) exhibited significant changes in 11 lobules in both left and right regions and the vermis. These analyses, in sum, indicated decreases in GM density in lobules I-IV, V, VI, VII and VIII as well as the vermis. ET cases with severe tremor (n = 20) did not show regions of change that survived the BH FDR procedure when compared to controls.

Conclusions

We showed that ET cases with various forms of cranial tremor differed from controls with respect to cerebellar GM density, with evidence of GM reduction across multiple cerebellar regions. Additional work, using a lobule-by-lobule approach, is needed to confirm these results and precisely map the regional differences in ET cases, subgroups of ET cases, and controls.

Structural differences in impaired verbal fluency in essential tremor patients compared to healthy controls

OBJECTIVE

We wanted to identify differences in grey and white matter in essential tremor patients compared to controls in the non-motor domain, using the example of impaired verbal fluency.

BACKGROUND

A disturbance of verbal fluency in essential tremor patients compared to healthy controls is behaviorally well described.

METHODS

Voxel-based morphometry and tract-based spatial statistics were used to analyze structural differences in grey and white matter in 19 essential tremor patients compared to 23 age- and gender-matched controls.

RESULTS

Several significant observations were made. (I) There was less grey matter in the predominantly right precuneus in the essential tremor group compared to controls [p < .001]. (II) In ET patients mean, axial, and radial diffusivity values broadly correlated with the tremor rating scale, pronounced in fronto-parietal regions [p < .05]. (III) In ET patients there was a significant decline in fractional anisotropy values in the corpus callosum in the correlation with verbal fluency results [p < .05]; by inclusion of the tremor rating scale as covariate of no interest this significance was however diminished to a tendency (p < .1). No significant results were found in these within-group correlations in grey matter analyses for ET patients (p > .05).

CONCLUSION

The present results indicate that non-motor symptoms such as verbal fluency (VBF) in ET have a structural substrate; their reproduction requires the integration of potential environmental plasticity effects, differentiation into individual clinical subtypes and a careful handling with methodological peculiarities of structural MR imaging.

Linking Essential Tremor to the Cerebellum-Neuroimaging Evidence

Essential tremor (ET) is the most common pathological tremor disorder in the world, and post-mortem evidence has shown that the cerebellum is the most consistent area of pathology in ET. In the last few years, advanced neuroimaging has tried to confirm this evidence. The aim of the present review is to discuss to what extent the evidence provided by this field of study may be generalised. We performed a systematic literature search combining the terms ET with the following keywords: MRI, VBM, MRS, DTI, fMRI, PET and SPECT. We summarised and discussed each study and placed the results in the context of existing knowledge regarding the cerebellar involvement in ET. A total of 51 neuroimaging studies met our search criteria, roughly divided into 19 structural and 32 functional studies. Despite clinical and methodological differences, both functional and structural imaging studies showed similar findings but without defining a clear topography of neurodegeneration. Indeed, the vast majority of studies found functional and structural abnormalities in several parts of the anterior and posterior cerebellar lobules, but it remains to be established to what degree these neural changes contribute to clinical symptoms of ET. Currently, advanced neuroimaging has confirmed the involvement of the cerebellum in pathophysiological processes of ET, although a high variability in results persists. For this reason, the translation of this knowledge into daily clinical practice is again partially limited, although new advanced multivariate neuroimaging approaches (machine-learning) are proving interesting changes of perspective.

Atrophy of the Cerebellar Vermis in Essential Tremor: Segmental Volumetric MRI Analysis

Postmortem studies of essential tremor (ET) have demonstrated the presence of degenerative changes in the cerebellum, and imaging studies have examined related structural changes in the brain. However, their results have not been completely consistent and the number of imaging studies has been limited. We aimed to study cerebellar involvement in ET using MRI segmental volumetric analysis. In addition, a unique feature of this study was that we stratified ET patients into subtypes based on the clinical presence of cerebellar signs and compared their MRI findings. Thirty-nine ET patients and 36 normal healthy controls, matched for age and sex, were enrolled. Cerebellar signs in ET patients were assessed using the clinical tremor rating scale and International Cooperative Ataxia Rating Scale. ET patients were divided into two groups: patients with cerebellar signs (cerebellar-ET) and those without (classic-ET). MRI volumetry was performed using CIVET pipeline software. Data on whole and segmented cerebellar volumes were analyzed using SPSS. While there was a trend for whole cerebellar volume to decrease from controls to classic-ET to cerebellar-ET, this trend was not significant. The volume of several contiguous segments of the cerebellar vermis was reduced in ET patients versus controls. Furthermore, these vermis volumes were reduced in the cerebellar-ET group versus the classic-ET group. The volume of several adjacent segments of the cerebellar vermis was reduced in ET. This effect was more evident in ET patients with clinical signs of cerebellar dysfunction. The presence of tissue atrophy suggests that ET might be a neurodegenerative disease.

Current concepts of essential tremor

Essential tremor is clinically defined but there is increasing evidence that it is not a unique entity. Its pathophysiology has been studied with many methods but may also vary between subtypes. Neurophysiologically, there is strong evidence that a specific cerebello-thalamo-cortical loop is abnormally oscillating. The cause of its uncontrolled oscillation is not yet understood. The clear proof of a degenerative cause is still lacking and abnormal receptors or other causes of altered non-progressive functional disturbance cannot be excluded. Strong evidence supports the major involvement of the cerebellum and there is ample evidence that GABA is the main neurotransmitter involved in the pathophysiology in ET. Genetics have provided so far only a few rare subtypes which are due to specific mutations but there is no doubt that it is mostly a hereditary condition. There is evidence that the large subgroup of late onset tremor is a separate condition and this tremor is an independent risk factor for earlier mortality and comes with signs of premature aging (aging-related tremor). It will be important to improve phenotyping of patients in more detail possibly to include not only features of the tremor itself but also other clinical assessments like force measurements or cognitive testing. Based on these variables, we may be able to better understand the presumably different mechanisms underlying different variants of the disease.

Subcortical Volumes Differ in Parkinson's Disease Motor Subtypes: New Insights into the Pathophysiology of Disparate Symptoms

Objectives: Patients with Parkinson’s disease (PD) can be classified, based on their motor symptoms into the Postural Instability Gait Difficulty (PIGD) subtype or the Tremor Dominant (TD) subtype. Gray matter changes between the subtypes have been reported using whole brain Voxel-Based Morphometry (VBM), however, the evaluation of subcortical gray matter volumetric differences between these subtypes using automated volumetric analysis has only been studied in relatively small sample sizes and needs further study to confirm that the negative findings were not due to the sample size. Therefore, we aimed to evaluate volumetric changes in subcortical regions and their association with PD motor subtypes.

Methods: Automated volumetric magnetic resonance imaging (MRI) analysis quantified the subcortical gray matter volumes of patients with PD in the PIGD subtype (n = 30), in the TD subtype (n = 30), and in 28 healthy controls (HCs).

Results: Significantly lower amygdala and globus pallidus gray matter volume was detected in the PIGD, as compared to the TD subtype, with a trend for an association between globus pallidus degeneration and higher (worse) PIGD scores. Furthermore, among all the patients with PD, higher hippocampal volumes were correlated with a higher (better) dual tasking gait speed (r = 0.30, p < 0.002) and with a higher global cognitive score (r = 0.36, p < 0.0001). Lower putamen volume was correlated with a higher (worse) freezing of gait score (r = −0.28, p < 0.004), an episodic symptom which is common among the PIGD subtype. As expected, differences detected between HCs and patients in the PD subgroups included regions within the amygdala and the dorsal striatum but not the ventral striatum, a brain region that is generally considered to be more preserved in PD.

Conclusions: The disparate patterns of subcortical degeneration can explain some of the differences in symptoms between the PD subtypes such as gait disturbances and cognitive functions. These findings may, in the future, help to inform a personalized therapeutic approach.

Essential tremor is associated with disruption of functional connectivity in the ventral intermediate Nucleus--Motor Cortex--Cerebellum circuit

The clinical benefits of targeting the ventral intermediate nucleus (VIM) for the treatment of tremors in essential tremor (ET) patients suggest that the VIM is a key hub in the network of tremor generation and propagation and that the VIM can be considered as a seed region to study the tremor network. However, little is known about the central tremor network in ET patients. Twenty-six ET patients and 26 matched healthy controls (HCs) were included in this study. After considering structural and head-motion factors and establishing the accuracy of our seed region, a VIM seed-based functional connectivity (FC) analysis of resting-state functional magnetic resonance imaging (RS-fMRI) data was performed to characterize the VIM FC network in ET patients. We found that ET patients and HCs shared a similar VIM FC network that was generally consistent with the VIM anatomical connectivity network inferred from normal nonhuman primates and healthy humans. Compared with HCs, ET patients displayed VIM-related FC changes, primarily within the VIM-motor cortex (MC)-cerebellum (CBLM) circuit, which included decreased FC in the CBLM and increased FC in the MC. Importantly, tremor severity correlated with these FC changes. These findings provide the first evidence that the pathological tremors observed in ET patients might be based on a physiologically pre-existing VIM - MC - CBLM network and that disruption of FC in this physiological network is associated with ET. Further, these findings demonstrate a potential approach for elucidating the neural network mechanisms underlying this disease.

Widespread increase of functional connectivity in Parkinson's disease with tremor: a resting-state FMRI study

Parkinson’s disease (PD) is a clinically heterogeneous disease in the symptomatology dominated by tremor, akinesia, or rigidity. Focusing on PD patients with tremor, this study investigated their discoordination patterns of spontaneous brain activity by combining voxel-wise centrality, seed-based functional connectivity, and network efficiency methods. Sixteen patients and 20 matched healthy controls (HCs) were recruited and underwent structural and resting-state functional MRI scan. Compared with the HCs, the patients exhibited increased centrality in the frontal, parietal, and occipital regions while decreased centrality in the cerebellum anterior lobe and thalamus. Seeded at these regions, a distributed network was further identified that encompassed cortical (default mode network, sensorimotor cortex, prefrontal and occipital areas) and subcortical (thalamus and basal ganglia) regions and the cerebellum and brainstem. Graph-based analyses of this network revealed increased information transformation efficiency in the patients. Moreover, the identified network correlated with clinical manifestations in the patients and could distinguish the patients from HCs. Morphometric analyses revealed decreased gray matter volume in multiple regions that largely accounted for the observed functional abnormalities. Together, these findings provide a comprehensive view of network disorganization in PD with tremor and have important implications for understanding neural substrates underlying this specific type of PD.

Neuroimaging studies of essential tremor: how well do these studies support/refute the neurodegenerative hypothesis?

Background

Tissue-based research has recently led to a new patho-mechanistic model of essential tremor (ET)—the cerebellar degenerative model. We are not aware of a study that has reviewed the current neuroimaging evidence, focusing on whether the studies support or refute the neurodegenerative hypothesis of ET. This was our aim.

Methods

References for this review were identified by searches of PubMed (1966 to February 2014).

Results

Several neuroimaging methods have been used to study ET, most of them based on magnetic resonance imaging (MRI). The methods most specific to address the question of neurodegeneration are MRI-based volumetry, magnetic resonance spectroscopy, and diffusion-weighted imaging. Studies using each of these methods provide support for the presence of cerebellar degeneration in ET, finding reduced cerebellar brain volumes, consistent decreases in cerebellar N-acetylaspartate, and increased mean diffusivity. Other neuroimaging techniques, such as functional MRI and positron emission tomography (PET) are less specific, but still sensitive to potential neurodegeneration. These techniques are used for measuring a variety of brain functions and their impairment. Studies using these modalities also largely support cerebellar neuronal impairment. In particular, changes in ¹¹C-flumazenil binding in PET studies and changes in iron deposition in an MRI study provide evidence along these lines. The composite data point to neuronal impairment and likely neuronal degeneration in ET.

Discussion

Recent years have seen a marked increase in the number of imaging studies of ET. As a whole, the combined data provide support for the presence of cerebellar neuronal degeneration in this disease.