Multimodal imaging and electrophysiological study in the differential diagnosis of rest tremor.

Introduction: Distinguishing tremor-dominant Parkinson's disease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data. Methods: We enrolled 72 patients including 40 tPD patients and 32 rET patients, and 45 control subjects (HC). RT electrophysiological features (frequency, amplitude, and phase) were calculated using surface electromyography (sEMG). Several MRI morphometric variables (cortical thickness, surface area, cortical/subcortical volumes, roughness, and mean curvature) were extracted using Freesurfer. ML models based on a tree-based classification algorithm termed XGBoost using MRI and/or electrophysiological data were tested in distinguishing tPD from rET patients. Results: Both structural MRI and sEMG data showed acceptable performance in distinguishing the two patient groups. Models based on electrophysiological data performed slightly better than those based on MRI data only (mean AUC: 0.92 and 0.87, respectively; p = 0.0071). The top-performing model used a combination of sEMG features (amplitude and phase) and MRI data (cortical volumes, surface area, and mean curvature), reaching AUC: 0.97 ± 0.03 and outperforming models using separately either MRI (p = 0.0001) or EMG data (p = 0.0231). In the best model, the most important feature was the RT phase. Conclusion: Machine learning models combining electrophysiological and MRI data showed great potential in distinguishing between tPD and rET patients and may serve as biomarkers to support clinicians in the differential diagnosis of rest tremor syndromes in the absence of expensive and invasive diagnostic procedures such as dopamine imaging.

Combined cortical thickness and blink reflex recovery cycle to differentiate essential tremor with and without resting tremor.

Objective: To investigate the performance of structural MRI cortical and subcortical morphometric data combined with blink-reflex recovery cycle (BRrc) values using machine learning (ML) models in distinguishing between essential tremor (ET) with resting tremor (rET) and classic ET. Methods: We enrolled 47 ET, 43 rET patients and 45 healthy controls (HC). All participants underwent brain 3 T-MRI and BRrc examination at different interstimulus intervals (ISIs, 100-300 msec). MRI data (cortical thickness, volumes, surface area, roughness, mean curvature and subcortical volumes) were extracted using Freesurfer on T1-weighted images. We employed two decision tree-based ML classification algorithms (eXtreme Gradient Boosting [XGBoost] and Random Forest) combining MRI data and BRrc values to differentiate between rET and ET patients. Results: ML models based exclusively on MRI features reached acceptable performance (AUC: 0.85-0.86) in differentiating rET from ET patients and from HC. Similar performances were obtained by ML models based on BRrc data (AUC: 0.81-0.82 in rET vs. ET and AUC: 0.88-0.89 in rET vs. HC). ML models combining imaging data (cortical thickness, surface, roughness, and mean curvature) together with BRrc values showed the highest classification performance in distinguishing between rET and ET patients, reaching AUC of 0.94 ± 0.05. The improvement in classification performances when BRrc data were added to imaging features was confirmed by both ML algorithms. Conclusion: This study highlights the usefulness of adding a simple electrophysiological assessment such as BRrc to MRI cortical morphometric features for accurately distinguishing rET from ET patients, paving the way for a better classification of these ET syndromes.

Development of a New Wearable Device for the Characterization of Hand Tremor.

Rest tremor (RT) is observed in subjects with Parkinson's disease (PD) and Essential Tremor (ET). Electromyography (EMG) studies have shown that PD subjects exhibit alternating contractions of antagonistic muscles involved in tremors, while the contraction pattern of antagonistic muscles is synchronous in ET subjects. Therefore, the RT pattern can be used as a potential biomarker for differentiating PD from ET subjects. In this study, we developed a new wearable device and method for differentiating alternating from a synchronous RT pattern using inertial data. The novelty of our approach relies on the fact that the evaluation of synchronous or alternating tremor patterns using inertial sensors has never been described so far, and current approaches to evaluate the tremor patterns are based on surface EMG, which may be difficult to carry out for non-specialized operators. This new device, named "RT-Ring", is based on a six-axis inertial measurement unit and a Bluetooth Low-Energy microprocessor, and can be worn on a finger of the tremulous hand. A mobile app guides the operator through the whole acquisition process of inertial data from the hand with RT, and the prediction of tremor patterns is performed on a remote server through machine learning (ML) models. We used two decision tree-based algorithms, XGBoost and Random Forest, which were trained on features extracted from inertial data and achieved a classification accuracy of 92% and 89%, respectively, in differentiating alternating from synchronous tremor segments in the validation set. Finally, the classification response (alternating or synchronous RT pattern) is shown to the operator on the mobile app within a few seconds. This study is the first to demonstrate that different electromyographic tremor patterns have their counterparts in terms of rhythmic movement features, thus making inertial data suitable for predicting the muscular contraction pattern of tremors.

Cortical involvement in essential tremor with and without rest tremor: a machine learning study.

INTRODUCTION: There is some debate on the relationship between essential tremor with rest tremor (rET) and the classic ET syndrome, and only few MRI studies compared ET and rET patients. This study aimed to explore structural cortical differences between ET and rET, to improve the knowledge of these tremor syndromes. METHODS: Thirty-three ET patients, 30 rET patients and 45 control subjects (HC) were enrolled. Several MR morphometric variables (thickness, surface area, volume, roughness, mean curvature) of brain cortical regions were extracted using Freesurfer on T1-weighted images and compared among groups. The performance of a machine learning approach (XGBoost) using the extracted morphometric features was tested in discriminating between ET and rET patients. RESULTS: rET patients showed increased roughness and mean curvature in some fronto-temporal areas compared with HC and ET, and these metrics significantly correlated with cognitive scores. Cortical volume in the left pars opercularis was also lower in rET than in ET patients. No differences were found between ET and HC. XGBoost discriminated between rET and ET with mean AUC of 0.86 ± 0.11 in cross-validation analysis, using a model based on cortical volume. Cortical volume in the left pars opercularis was the most informative feature for classification between the two ET groups. CONCLUSION: Our study demonstrated higher cortical involvement in fronto-temporal areas in rET than in ET patients, which may be linked to the cognitive status. A machine learning approach based on MR volumetric data demonstrated that these two ET subtypes can be distinguished using structural cortical features.

Cerebellar voxel-based morphometry in essential tremor.

BACKGROUND: Imaging studies investigating cerebellar gray matter (GM) in essential tremor (ET) showed conflicting results. Moreover, no large study explored the cerebellum in ET patients with resting tremor (rET), a syndrome showing enhanced blink reflex recovery cycle (BRrc). OBJECTIVE: To investigate cerebellar GM in ET and rET patients using voxel-based morphometry (VBM) analysis. METHODS: Seventy ET patients with or without resting tremor and 39 healthy controls were enrolled. All subjects underwent brain 3 T-MRI and BRrc recording. We compared the cerebellar GM volumes between ET (n = 40) and rET (n = 30) patients and controls through a VBM analysis. Moreover, we investigated possible correlations between cerebellar GM volume and R2 component of BRrc. RESULTS: rET and ET patients had similar disease duration. All rET patients and none of ET patients had enhanced BRrc. No differences in the cerebellar volume were found when ET and rET patients were compared to each other or with controls. By considering together the two tremor syndromes in a large patient group, the VBM analysis showed bilateral clusters of reduced GM volumes in Crus II in comparison with controls. The linear regression analysis in rET patients revealed a cluster in the left Crus II where the decrease in GM volume correlated with the R2BRrc increase. CONCLUSION: Our study suggests that ET and rET are different tremor syndromes with similar mild cerebellar gray matter involvement. In rET patients, the left Crus II may play a role in modulating the brainstem excitability, encouraging further studies on the role of cerebellum in these patients.

Evaluation of rest tremor in different positions in Parkinson's disease and essential tremor plus.

BACKGROUND: Rest tremor (RT) can be observed in several positions (seated, standing, lying down) but it is unknown whether the tremor features may vary across them. This study aimed to compare the RT electrophysiological features across different positions in tremor-dominant Parkinson's disease (PD) and essential tremor plus (ET with RT, rET). METHODS: We consecutively enrolled 90 tremor-dominant PD and 24 rET patients. The RT presence was evaluated in three positions: with the patient seated, the arm flexed at 90°, the forearm supported against gravity, and the hand hanging down from the chair armrest (hand-hanging position), in lying down supine and in standing position. RT electrophysiological features (amplitude, frequency, burst duration, pattern) were compared between the two patient groups and across the different positions. RESULTS: All PD and rET patients showed RT in hand-hanging position. Supine and standing RT were significantly more common in PD (67.8% and 75.6%, respectively) than in rET patients (37.5% and 45.8%, respectively). RT amplitude, frequency and pattern were significantly different between groups in hand-hanging position whereas only pattern was significantly different between PD and rET in both standing and supine positions. In each patient group, all RT electrophysiological features did not significantly vary across different recording positions (p > 0.05). DISCUSSION: In our study, PD and rET showed RT in hand-hanging, supine, and standing positions. RT pattern was the only electrophysiological feature significantly different between PD and rET patients in all these positions, enabling clinicians to perform the RT analysis for diagnostic purposes in different tremor positions.

Aceruloplasminemia: a multimodal imaging study in an Italian family with a novel mutation.

OBJECTIVE: Structural abnormalities in thalami and basal ganglia, in particular the globus pallidus (GP), are a neuroimaging hallmark of hereditary aceruloplasminemia (HA), yet few functional imaging data exit in HA carriers. This study investigated the iron-related structural and functional abnormalities in an Italian HA family. METHODS: Multimodal imaging was used including structural 3 T MRI, functional imaging (SPECT imaging with 123I-ioflupane (DAT-SPECT), cardiac 123I metaiodobenzylguanidine (123I-MIBG) scintigraphy, and 18F-fluorodeoxyglucose (18F-FDG)-PET imaging). In the proband, MRI and scintigraphic evaluations were performed at baseline, 2 and 4 years (structural imaging), and 2 years of follow-up period (functional imaging). RESULTS: We investigated two cousins carrying a novel splicing homozygous mutation in intron 6 (IVS6 + 1 G > A) of CP gene. Interestingly, MRI features in both subjects were characterized by marked iron accumulation in the thalami and basal ganglia nuclei, while GP was not affected. MRI performed in the proband at 2 and 4 years of follow-up confirmed progressive neurodegeneration of the thalami and basal ganglia without the involvement of GP. Functional imaging showed reduced putaminal DAT uptake in both cousins, whereas cardiac MIBG and FDG uptakes performed in the proband were normal. Longitudinal scintigraphic investigations did not show significant changes over the time. CONCLUSIONS: For HA carriers, our findings demonstrate that GP was spared by iron accumulation over the time. The nigrostriatal presynaptic dopaminergic system was damaged while the cardiac sympathetic system remained longitudinally preserved, thus expanding the imaging features of this rare inherited disorder.

Blink reflex recovery cycle distinguishes patients with idiopathic normal pressure hydrocephalus from elderly subjects.

BACKGROUND: The R2 component of blink reflex recovery cycle (R2BRrc) is a simple neurophysiological tool to detect the brainstem hyperexcitability commonly occurring in several neurological diseases such as Parkinson's disease and atypical parkinsonisms. In our study, we investigated for the first time the usefulness of R2BRrc to assess brainstem excitability in patients with idiopathic Normal Pressure Hydrocephalus (iNPH) in comparison with healthy subjects. METHODS: Eighteen iNPH patients and 25 age-matched control subjects were enrolled. R2BRrc was bilaterally evaluated at interstimulus intervals (ISIs) of 100, 150, 200, 300, 400, 500 and 750 ms in all participants. We investigated the diagnostic performance of R2BRrc in differentiating iNPH patients from control subjects using ROC analysis. Midbrain area and Magnetic Resonance Hydrocephalic Index (MRHI), an MRI biomarker for the diagnosis of iNPH, were measured on T1-weighted MR images, and correlations between R2BRrc values and MRI measurements were investigated. RESULTS: Fourteen (78%) of 18 iNPH patients showed an enhanced R2BRrc at ISIs 100-150-200 ms, while no control subjects had abnormal R2BRrc. The mean amplitude of bilateral R2BRrc at the shortest ISIs (100-150-200 ms) showed high accuracy in differentiating iNPH patients from controls (AUC = 0.89). R2BRrc values significantly correlated with midbrain area and MRHI values. CONCLUSIONS: This study represents the first evidence of brainstem hyperexcitability in iNPH patients. Given its low cost and wide availability, R2BRrc could be a useful tool for selecting elderly subjects with mild gait and urinary dysfunction who should undergo an extensive diagnostic workup for the diagnosis of NPH.

Wearable Devices for Assessment of Tremor.

Tremor is an impairing symptom associated with several neurological diseases. Some of such diseases are neurodegenerative, and tremor characterization may be of help in differential diagnosis. To date, electromyography (EMG) is the gold standard for the analysis and diagnosis of tremors. In the last decade, however, several studies have been conducted for the validation of different techniques and new, non-invasive, portable, or even wearable devices have been recently proposed as complementary tools to EMG for a better characterization of tremors. Such devices have proven to be useful for monitoring the efficacy of therapies or even aiding in differential diagnosis. The aim of this review is to present systematically such new solutions, trying to highlight their potentialities and limitations, with a hint to future developments.

Development and Validation of a New Wearable Mobile Device for the Automated Detection of Resting Tremor in Parkinson's Disease and Essential Tremor.

Involuntary tremor at rest is observed in patients with Parkinson's disease (PD) or essential tremor (ET). Electromyography (EMG) studies have shown that phase displacement between antagonistic muscles at prevalent tremor frequency can accurately differentiate resting tremor in PD from that detected in ET. Currently, phase evaluation is qualitative in most cases. The aim of this study is to develop and validate a new mobile tool for the automated and quantitative characterization of phase displacement (resting tremor pattern) in ambulatory clinical settings. A new low-cost, wearable mobile device, called µEMG, is described, based on low-end instrumentation amplifiers and simple digital signal processing (DSP) capabilities. Measurements of resting tremor characteristics from this new device were compared with standard EMG. A good level of agreement was found in a sample of 21 subjects (14 PD patients with alternating resting tremor pattern and 7 ET patients with synchronous resting tremor pattern). Our results demonstrate that tremor analysis using µEMG is easy to perform and it can be used in routine clinical practice for the automated quantification of resting tremor patterns. Moreover, the measurement process is handy and operator-independent.

Magnetic Resonance Imaging Biomarkers Distinguish Normal Pressure Hydrocephalus From Progressive Supranuclear Palsy.

BACKGROUND: Idiopathic normal pressure hydrocephalus and PSP share several clinical and radiological features, making differential diagnosis, at times, challenging. OBJECTIVES: To differentiate idiopathic normal pressure hydrocephalus from PSP using MR volumetric and linear measurements. METHODS: Twenty-seven idiopathic normal pressure hydrocephalus patients, 103 probable PSP patients, and 43 control subjects were consecutively enrolled. Automated ventricular volumetry was performed using Freesurfer 6 on MR T1 -weighted images. Linear measurements, such as callosal angle and a new measure, termed MR Hydrocephalic Index, were calculated on MR T1 -weighted images. Receiver operating characteristic analyses were used for differentiating between patient groups. Generalizability and reproducibility of the results were validated, dividing each participant group in two cohorts used as training and testing subsets. RESULTS: Ventricular volumes and linear measurements (callosal angle and Magnetic Resonance Hydrocephalic Index) revealed greater ventricular enlargement in patients with idiopathic normal pressure hydrocephalus than in PSP patients and controls. PSP patients had ventricular volume larger than controls. Automated ventricular volumetry and Magnetic Resonance Hydrocephalic Index were the most accurate measures (98.5%) in differentiating patients with idiopathic normal pressure hydrocephalus from PSP patients, whereas callosal angle misclassified several PSP patients and showed low positive predictive value (70.0%) in differentiating between these two diseases. All measurements accurately differentiated idiopathic normal pressure hydrocephalus patients from controls. Accuracy values obtained in the training set (automated ventricular volumetry, 98.4%; Magnetic Resonance Hydrocephalic Index, 98.4%; callosal angle, 87.5%) were confirmed in the testing set. CONCLUSIONS: Our study demonstrates that AVV and Magnetic Resonance Hydrocephalic Index were the most accurate measures for differentiation between idiopathic normal pressure hydrocephalus and PSP patients. Magnetic Resonance Hydrocephalic Index is easy to measure and can be used in clinical practice to prevent misdiagnosis and ineffective shunt procedures in idiopathic normal pressure hydrocephalus mimics. © 2020 International Parkinson and Movement Disorder Society.

Hippocampal impairment in patients with Essential Tremor.

INTRODUCTION: There is growing evidence that a proportion of patients with Essential Tremor (ET) may develop a memory impairment over time. However, no studies have evaluated whether hippocampal damage really occur in ET. This study investigated the macro and micro-structural integrity of the hippocampus in ET subjects using a multimodal MRI approach. METHODS: Neuropsychological and MRI data were acquired from 110 participants (60 patients with ET and 50 age-, sex-, and education-matched healthy controls [HC]). Whole-brain T1-weighted and Diffusion Tensor Imaging (DTI) were performed to assess macro-and microstructural alterations. MRI parameters (volume; mean diffusivity [MD]; fractional anisotropy [FA]) of bilateral hippocampi were obtained. In order to evaluate the relationship between MRI alterations and neurocognitive impairment, hippocampal parameters were also correlated with cognitive test scores. RESULTS: Compared to controls, ET patients showed a subclinical memory impairment with significantly lower memory scores, but within the normal ranges. Despite the subclinical damage, however, ET patients showed a significant increase in MD values in the bilateral hippocampi in comparison with HC. A significant correlation was also found between MD and memory scores in ET. CONCLUSION: This study improves the knowledge on memory impairment in ET, as our results demonstrate for the first time the hippocampal microstructural damage related to subclinical memory impairment in ET patients. Further studies are needed before these findings can be considered predictive of a distinct ET subtype or suggestive of a co-occurent dementia.

Magnetic Resonance Parkinsonism Index for evaluating disease progression rate in progressive supranuclear palsy: A longitudinal 2-year study.

INTRODUCTION: We investigated the disease progression rate in patients with progressive supranuclear palsy-Richardson syndrome (PSP-RS) and PSP-parkinsonism (PSP-P) in comparison with Parkinson disease (PD) patients, using MRPI (Magnetic Resonance Parkinsonism Index), and MRPI 2.0. METHODS: Fifteen PSP-RS patients (disease duration, y, mean ± SD: 2.5 ± 1.1), 16 PSP-P patients (disease duration, y, mean ± SD: 6.5 ± 3.2) and 19 PD patients (disease duration, y, mean ± SD: 3.2 ± 2.3) were enrolled. All patients underwent clinical assessment and MRI at baseline, 1-year, and 2-year follow-up. MRPI, MRPI 2.0 and clinical scores over 1 and 2-years were used to evaluate disease progression rate, and to calculate sample sizes required to power placebo-controlled trials. RESULTS: All groups showed increased clinical motor scores over time whereas only PSP groups had increased MRPI and MRPI 2.0 values over T1 and T2 intervals. The percentage increase over 1 and 2-years of MRPI and MRPI 2.0 values was significantly higher in PSP groups than in PD group, and in PSP-RS than in PSP-P patients while no difference between patient groups was observed when clinical motor scores were considered. Sample size estimates showed that MRPI 2.0 performed better than MRPI and clinical scales. Treatment trials with MRPI 2.0 could be performed over 2-years both in PSP-RS and PSP-P with a sample size per treatment arm of 89 and 170 patients, respectively. CONCLUSIONS: Our results demonstrate that MRPI 2.0 was more powerful than MRPI and clinical motor scales in evaluating PSP progression, and in providing the best sample size estimates for clinical trials.

Assessment of the Corticospinal Tract Profile in Pure Lower Motor Neuron Disease: A Diffusion Tensor Imaging Study.

AIM: The aim of this study was to evaluate the corticospinal tract (CST) diffusion profile in pure lower motor neuron disease (pLMND) patients who at baseline did not show any clinical or electrophysiological involvement of upper motor neurons (UMN), and in amyotrophic lateral sclerosis (ALS) patients. MATERIALS AND METHODS: Fifteen ALS patients with delayed central motor conduction time (CMCT) and 14 pLMND patients with normal CMCT were enrolled together with 15 healthy controls. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) maps were obtained. The tract profile of CST was reconstructed with the automated fiber quantification tool and its diffusion properties were quantified voxel-by-voxel and then compared pairwise between groups. Moreover, a random forest (RF) classifier was trained to evaluate the ability of CST diffusion metrics in distinguishing pairwise the groups from the controls. RESULTS: ALS patients presented wide microstructural abnormalities in the entire CST as assessed by FA decrease and RD increase while pLMND patients showed focal FA decrease and a larger AD increase in the cerebral peduncle and posterior limb of the internal capsule in comparison with controls. RF revealed that diffusion tensor imaging (DTI) metrics accurately distinguished ALS patients and pLMND patients from controls (96.67 and 95.71% accuracy, respectively). CONCLUSIONS: Our study demonstrates that the CST was impaired in both ALS and pLMND patients, thus suggesting that DTI metrics are a reliable tool in detecting subtle changes of UMN in pLMND patients, also in the absence of clinical and CMCT abnormalities.

Apomorphine-induced reorganization of striato-frontal connectivity in patients with tremor-dominant Parkinson's disease.

INTRODUCTION: Apomorphine is a dopamine agonist used in Parkinson's disease (PD), which matches levodopa in terms of the magnitude of effect on the cardinal motor features, such as tremor and bradykinesia. The beneficial effect of this treatment on PD patients with tremor-dominant has widely been demonstrated, although the underlying neural correlates are unknown. We sought to examine the effects of apomorphine on topological characteristics of resting-state functional connectivity networks in tremor-dominant PD (tdPD) patients. METHODS: Sixteen tdPD patients were examined using a combined electromyography-functional magnetic resonance imaging approach. Patients were scanned twice following either placebo (subcutaneous injection of 1 mL saline solution) or 1 mg of apomorphine injection. Graph analysis methods were employed to investigate the modular organization of functional connectivity networks before and after drug treatment. RESULTS: After injection of apomorphine, evident reduction of tremor symptoms was mirrored by a significant increase in overall connectivity strength and reorganization of the modular structure of the basal ganglia and of the fronto-striatal module. Moreover, we found an increase in the centrality of motor and premotor regions. No differences were found between pre- and post-placebo sessions. CONCLUSION: These results provide new evidence about the effects of apomorphine at a large-scale neural network level showing that drug treatment modifies the brain functional organization of tdPD, increasing the overall resting-state functional connectivity strength, the segregation of striato-frontal regions and the integrative role of motor areas.

The embodiment of language in tremor-dominant Parkinson's disease patients.

According to embodied cognition, processing language with motor content involves a simulation of this content by the brain motor system. Patients with brain lesions involving the motor system are characterized by deficits in action verbs processing in the absence of dementia. We sought to assess whether action verbs interfere with the motor behavior of patients with Parkinson's disease (PD) having tremor dominant symptoms. PD tremor is considered to result from dysfunction of cortical-subcortical motor circuits driven by dopamine depletion. In addition, PD tremor is reduced during active movement execution. Therefore, likewise movement execution, the motor simulation of bodily actions predicted by the embodiment may show to be effective in modifying tremor by interfering with a dysfunctional motor system. Here, we asked to simply read and repeat words expressing a hand-related bodily action. Abstract verbs served as control. Changes in tremor kinematics were evaluated using a monoaxial accelerometer. Seventeen PD patients with rest tremor of the upper limbs were enrolled. Tremor amplitude was significantly smaller when reading action verbs as compared to abstract verbs. We provide empirical evidence supporting the embodied cognition theory by showing that circuits mediating tremor of PD patients are distinctively affected by processing action language.