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

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.

Differentiation between Parkinson's Disease and the Parkinsonian Subtype of Multiple System Atrophy Using the Magnetic Resonance T1w/T2w Ratio in the Middle Cerebellar Peduncle

Multiple system atrophy with predominant parkinsonism (MSA-P) can hardly be distinguished from Parkinson's disease (PD) clinically in the early stages. This study investigated whether a standardized T1-weighted/T2-weighted ratio (sT1w/T2w ratio) can effectively detect degenerative changes in the middle cerebellar peduncle (MCP) associated with MSA-P and PD and evaluated its potential to distinguish between these two diseases. We included 35 patients with MSA-P, 32 patients with PD, and 17 controls. T1w and T2w scans were acquired using a 1.5-T MR system. The MCP sT1w/T2w ratio was analyzed via SPM12 using a region-of-interest approach in a normalized space. The diagnostic performance of the MCP sT1w/T2w ratio was compared between the MSA-P, PD, and controls. Patients with MSA-P had significantly lower MCP sT1w/T2w ratios than patients with PD and controls. Furthermore, MCP sT1w/T2w ratios were lower in patients with PD than in the controls. The MCP sT1w/T2w ratio showed excellent or good accuracy for differentiating MSA-P or PD from the control (area under the curve (AUC) = 0.919 and 0.814, respectively) and substantial power for differentiating MSA-P from PD (AUC = 0.724). Therefore, the MCP sT1w/T2w ratio is sensitive in detecting degenerative changes in the MCP associated with MSA-P and PD and is useful in distinguishing MSA-P from PD.

Aging, Neurodegenerative Disorders, and Cerebellum

An important part of the central nervous system (CNS), the cerebellum is involved in motor control, learning, reflex adaptation, and cognition. Diminished cerebellar function results in the motor and cognitive impairment observed in patients with neurodegenerative disorders such as Alzheimer's disease (AD), vascular dementia (VD), Parkinson's disease (PD), Huntington's disease (HD), spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS), Friedreich's ataxia (FRDA), and multiple sclerosis (MS), and even during the normal aging process. In most neurodegenerative disorders, impairment mainly occurs as a result of morphological changes over time, although during the early stages of some disorders such as AD, the cerebellum also serves a compensatory function. Biological aging is accompanied by changes in cerebellar circuits, which are predominantly involved in motor control. Despite decades of research, the functional contributions of the cerebellum and the underlying molecular mechanisms in aging and neurodegenerative disorders remain largely unknown. Therefore, this review will highlight the molecular and cellular events in the cerebellum that are disrupted during the process of aging and the development of neurodegenerative disorders. We believe that deeper insights into the pathophysiological mechanisms of the cerebellum during aging and the development of neurodegenerative disorders will be essential for the design of new effective strategies for neuroprotection and the alleviation of some neurodegenerative disorders.

Linking the cerebellum to Parkinson disease: an update

Parkinson disease (PD) is characterized by heterogeneous motor and non-motor symptoms, resulting from neurodegeneration involving various parts of the central nervous system. Although PD pathology predominantly involves the nigral-striatal system, growing evidence suggests that pathological changes extend beyond the basal ganglia into other parts of the brain, including the cerebellum. In addition to a primary involvement in motor control, the cerebellum is now known to also have an important role in cognitive, sleep and affective processes. Over the past decade, an accumulating body of research has provided clinical, pathological, neurophysiological, structural and functional neuroimaging findings that clearly establish a link between the cerebellum and PD. This Review presents an overview and update on the involvement of the cerebellum in the clinical features and pathogenesis of PD, which could provide a novel framework for a better understanding the heterogeneity of the disease.

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.

Mapping Essential Tremor to a Common Brain Network Using Functional Connectivity Analysis

BACKGROUND AND OBJECTIVES

The cerebello-thalamo-cortical circuit plays a critical role in essential tremor (ET). However, abnormalities have been reported in multiple brain regions outside this circuit, leading to inconsistent characterization of ET pathophysiology. Here, we test whether these mixed findings in ET localize to a common functional network and whether this network has therapeutic relevance.

METHODS

We conducted a systematic literature search to identify studies reporting structural or metabolic brain abnormalities in ET. We then used 'coordinate network mapping,' which leverages a normative connectome (n = 1,000) of resting-state fMRI data to identify regions commonly connected to findings across all studies. To assess whether these regions may be relevant for the treatment of ET, we compared our network with a therapeutic network derived from lesions that relieved ET. Finally, we investigated whether the functional connectivity of this ET symptom network is abnormal in an independent cohort of patients with ET as compared with healthy controls.

RESULTS

Structural and metabolic brain abnormalities in ET were located in heterogeneous regions throughout the brain. However, these coordinates were connected to a common functional brain network, including the cerebellum, thalamus, motor cortex, precuneus, inferior parietal lobe, and insula. The cerebellum was identified as the hub of this network because it was the only brain region that was both functionally connected to the findings of over 90% of studies and significantly different in connectivity compared with a control data set of other movement disorders. This network was strikingly similar to the therapeutic network derived from lesions improving ET, with key regions aligning in the thalamus and cerebellum. Furthermore, positive functional connectivity between the cerebellar network hub and the sensorimotor cortices was significantly reduced in patients with ET compared with healthy controls, and connectivity within this network was correlated with tremor severity and cognitive functioning.

DISCUSSION

These findings suggest that the cerebellum is the central hub of a network commonly connected to structural and metabolic abnormalities in ET. This network may have therapeutic utility in refining and informing new targets for neuromodulation of ET.

Essential tremor impairs the ability to suppress involuntary action impulses

Essential tremor (ET) is a movement disorder characterized primarily by action tremor which affects the regulation of movements. Disruptions in cerebello-thalamocortical networks could interfere with cognitive control over actions in ET, for example, the ability to suppress a strong automatic impulse over a more appropriate action (conflict control). The current study investigated whether ET impacts conflict control proficiency. Forty-one ET patients and 29 age-matched healthy controls (HCs) performed a conflict control task (Simon task). Participants were instructed to give a left or right response to a spatially lateralized arrow (direction of the arrow). When the action signaled by the spatial location and direction of the arrow were non-corresponding (induced conflict), the inappropriate action impulse required suppression. Overall, ET patients responded slower and less accurately compared to HCs. ET patients were especially less accurate on non-corresponding conflict (Nc) versus corresponding (Cs) trials. A focused analysis on fast impulsive response rates (based on the accuracy rate at the fastest reaction times on Nc trials) showed that ET patients made more fast errors compared to HCs. Results suggest impaired conflict control in ET compared to HCs. The increased impulsive errors seen in the ET population may be a symptom of deficiencies in the cerebello-thalamocortical networks, or, be caused by indirect effects on the cortico-striatal pathways. Future studies into the functional networks impacted by ET (cortico-striatal and cerebello-thalamocortical pathways) could advance our understanding of inhibitory control in general and the cognitive deficits in ET.

Texture analysis of dorsal striatum in functional neurological (conversion) disorder

In this study, it was aimed to evaluate the dorsal striatum nuclei of patients diagnosed with Functional Neurological Disorder by texture analysis method from magnetic resonance imaging images and to compare them with healthy controls. Study groups consisted of 20 female patients and 20 healthy women. The brains of patients and controls were scanned for high-resolution images with a 1.5T scanner using the sagittal plane and 3D spiral fast spin echo sequence. Using the texture analysis method, mean, standard deviation, minimum, maximum, median, variance, entropy, size %L, size %U, size %M, kurtosis, skewness and homogeneity values of the dorsal striatum nuclei were calculated from the images. The data were compared with comparison tests according to Kolmogorov-Smirnov test results. There was no statistically significant difference between paired regions in terms of texture analysis findings in the cross-sectional images of the participants. In patients, mean, standard deviation, minimum, maximum, median, variance and entropy values for the putamen nucleus, and mean, standard deviation, minimum, maximum, median, variance, entropy and kurtosis values for the caudate nucleus were found significantly higher than controls. Additional receiver operating characteristic curve and logistic regression analyzes were performed. The implications of the results of the study are that there are significant microstructural changes in the dorsal striatum nuclei of patients and their reflection on brain images. Texture analysis is a useful technique to show tissue changes in the dorsal striatum of patients using images. It is highly recommended to use texture analysis to identify and evaluate potentially affected areas of the brain in new studies.

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.