Rest tremor revisited: Parkinson's disease and other disorders

Bedside clinical assessment of patients with common upper limb tremor and algorithmic approach

The diagnostic approach for patients with tremor is challenging due to the complex and overlapping phenotypes among tremor syndromes. The first step in the evaluation of tremor is to identify the tremulous movement and exclude the tremor mimics. The second step is to classify the tremor syndrome based on the characteristics of tremor from historical clues and focused examination (Axis 1). Comprehensive tremor examinations involve the assessment of tremor in different conditions (rest, action or mixed, position or task-specific), distribution of tremor (upper limb, lower limb, head, jaw), positive signs for functional tremor (FT) if suspected (distractibility, entrainment, co-contraction), and associated neurological signs including parkinsonism, dystonic posture, cerebellar/brainstem signs, neuropathy, and cognitive impairment. A pivotal feature in this step is to determine any distinct feature of a specific isolated or combined tremor syndrome. In this review, we propose an algorithm to assess upper limb tremors. Ancillary testing should be performed if clinical evaluation is unclear. The choice of investigation depends on the types of tremors considered to narrow down the spectrum of etiology (Axis 2). Laboratory blood tests are considered for acute onset and acute worsening of tremors, while structural neuroimaging is indicated in unilateral tremors with acute onset, nonclassical presentations, and a combination of neurological symptoms. Neurophysiological study is an important tool that aids in distinguishing between tremor and myoclonus, etiology of tremor and document specific signs of FT. Treatment is mainly symptomatic based depending on the etiology of the tremor and the patient's disabilities.

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.

Brain Noradrenergic Innervation Supports the Development of Parkinson's Tremor: A Study in a Reserpinized Rat Model

The pathophysiology of tremor in Parkinson's disease (PD) is evolving towards a complex alteration to monoaminergic innervation, and increasing evidence suggests a key role of the locus coeruleus noradrenergic system (LC-NA). However, the difficulties in imaging LC-NA in patients challenge its direct investigation. To this end, we studied the development of tremor in a reserpinized rat model of PD, with or without a selective lesioning of LC-NA innervation with the neurotoxin DSP-4. Eight male rats (Sprague Dawley) received DSP-4 (50 mg/kg) two weeks prior to reserpine injection (10 mg/kg) (DR-group), while seven male animals received only reserpine treatment (R-group). Tremor, rigidity, hypokinesia, postural flexion and postural immobility were scored before and after 20, 40, 60, 80, 120 and 180 min of reserpine injection. Tremor was assessed visually and with accelerometers. The injection of DSP-4 induced a severe reduction in LC-NA terminal axons (DR-group: 0.024 ± 0.01 vs. R-group: 0.27 ± 0.04 axons/um2, p < 0.001) and was associated with significantly less tremor, as compared to the R-group (peak tremor score, DR-group: 0.5 ± 0.8 vs. R-group: 1.6 ± 0.5; p < 0.01). Kinematic measurement confirmed the clinical data (tremor consistency (% of tremor during 180 s recording), DR-group: 37.9 ± 35.8 vs. R-group: 69.3 ± 29.6; p < 0.05). Akinetic-rigid symptoms did not differ between the DR- and R-groups. Our results provide preliminary causal evidence for a critical role of LC-NA innervation in the development of PD tremor and foster the development of targeted therapies for PD patients.

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.

A Case of Long-Term Exposure to Valproic Acid Mimicking Tremor-Dominant Parkinson's Disease

Background

Valproic acid is associated with increased risks of tremor and parkinsonism.

Case Report

A 67-year-old man with a diagnosis of epilepsy who had been treated with valproic acid (VPA) for 32 years noticed right-dominant upper-limb resting tremor accompanied by mild rigidity and bradykinesia. He was initially diagnosed with tremor-dominant Parkinson's disease (TDPD), but dopamine transporter single-photon emission computed tomography demonstrated no nigrostriatal degeneration. At 3 months after discontinuing VPA, his symptoms dramatically improved.

Discussion

VPA-induced tremor usually consists of postural or kinetic tremor without asymmetry. Our case indicated that careful evaluation is needed, even in cases of asymmetrical resting tremor and mild parkinsonism resembling TDPD after long term exposure to VPA.

Highlights

We report an atypical case of valproic acid-induced tremor and parkinsonism that mimics tremor-dominant Parkinson's disease. Physicians should not exclude the possible relation to valproic acid in patients presenting unilateral resting tremor and parkinsonism even in the absence of long-term side effects.

Dystonia and tremor: Do they have a shared biology?

Dystonia and tremor are the two most commonly encountered hyperkinetic movement disorders encountered in clinical practice. While there has been substantial progress in the research on these two disorders, there also exists a lot of gray areas. Entities such as dystonic tremor and tremor associated with dystonia occupy a major portion of the "gray zone". In addition, there is a marked clinical heterogeneity and overlap of several clinical and epidemiological features among dystonia and tremor. These facts raise the possibility that dystonia and tremor could be having shared biology. In this chapter, we revisit critical aspects of this possibility that may have important clinical and research implications in the future. We comprehensively review the points in favor and against the theory that dystonia and tremor have shared biology from clinical, epidemiological, genetic and neuroimaging studies.

Short pulse and directional thalamic deep brain stimulation have differential effects in parkinsonian and essential tremor

The aim of this study was to assess the effects of novel stimulation algorithms of deep brain stimulation (short pulse and directional stimulation) in the ventrointermediate thalamus and posterior subthalamic area (VIM/PSA-DBS) on tremor in Parkinson’s disease (PD) and to compare the effects with those in essential tremor (ET). We recruited six PD patients (70.8 ± 10.4 years) and seven ET patients (64.4 ± 9.9 years) with implanted VIM/PSA-DBS in a stable treatment condition (> 3 months postoperatively). Tremor severity and ataxia were assessed in four different stimulation conditions in a randomized order: DBS switched off (STIM OFF), omnidirectional stimulation with 60 µs (oDBS60), omnidirectional stimulation with 30 µs (oDBS30), directional stimulation at the best segment with 60 µs (dDBS60). In both patient groups, all three DBS stimulation modes reduced the total tremor score compared to STIM OFF, whereas stimulation-induced ataxia was reduced by oDBS30 and partially by dDBS60 compared to oDBS60. Tremor reduction was more pronounced in PD than in ET due to a limited DBS effect on intention and action-specific drawing tremor in ET. In PD and ET tremor, short pulse or directional VIM/PSA-DBS is an effective and well tolerated therapeutic option.

Trial registration: The study was registered in the DRKS (ID DRKS00025329, 18.05.2021, German Clinical Trials Register, DRKS—Deutsches Register Klinischer Studien).

Translational Pharmacology of PRAX-944, a Novel T-Type Calcium Channel Blocker in Development for the Treatment of Essential Tremor

Background

Essential tremor is the most common movement disorder with clear unmet need. Mounting evidence indicates tremor is caused by increased neuronal burst firing and oscillations in cerebello‐thalamo‐cortical circuitry and may be dependent on T‐type calcium channel activity. T‐type calcium channels regulate sigma band electroencephalogram (EEG) power during non‐rapid eye movement sleep, representing a potential biomarker of channel activity. PRAX‐944 is a novel T‐type calcium channel blocker in development for essential tremor.

Objectives

Using a rat tremor model and sigma‐band EEG power, we assessed pharmacodynamically‐active doses of PRAX‐944 and their translation into clinically tolerated doses in healthy participants, informing dose selection for future efficacy trials.

Methods

Harmaline‐induced tremor and spontaneous locomotor activity were used to assess PRAX‐944 efficacy and tolerability, respectively, in rats. Sigma‐power was used as a translational biomarker of T‐type calcium channel blockade in rats and, subsequently, in a phase 1 trial assessing pharmacologic activity and tolerability in healthy participants.

Results

In rats, PRAX‐944 dose‐dependently reduced tremor by 50% and 72% at 1 and 3 mg/kg doses, respectively, without locomotor side effects. These doses also reduced sigma‐power by ~30% to 50% in rats. In healthy participants, sigma‐power was similarly reduced by 34% to 50% at 10 to 100 mg, with no further reduction at 120 mg. All doses were well tolerated.

Conclusions

In rats, PRAX‐944 reduced sigma‐power at concentrations that reduced tremor without locomotor side effects. In healthy participants, comparable reductions in sigma‐power indicate that robust T‐type calcium channel blockade was achieved at well‐tolerated doses that may hold promise for reducing tremor in patients with essential tremor. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Neurodegenerative Disorders and the Current State, Pathophysiology, and Management of Parkinson's Disease

In the last few decades, major knowledge has been gained about pathophysiological aspects and molecular pathways behind Parkinson's Disease (PD). Based on neurotoxicological studies and postmortem investigations, there is a general concept of how environmental toxicants (neurotoxins, pesticides, insecticides) and genetic factors (genetic mutations in PD-associated proteins) cause depletion of dopamine from substantia nigra pars compacta region of the midbrain and modulate cellular processes leading to the pathogenesis of PD. α-Synuclein, a neuronal protein accumulation in oligomeric form, called protofibrils, is associated with cellular dysfunction and neuronal death, thus possibly contributing to PD propagation. With advances made in identifying loci that contribute to PD, molecular pathways involved in disease pathogenesis are now clear, and introducing therapeutic strategy at the right time may delay the progression. Biomarkers for PD have helped monitor PD progression; therefore, personalized therapeutic strategies can be facilitated. In order to further improve PD diagnostic and prognostic accuracy, independent validation of biomarkers is required.

Deep Brain Stimulation for Tremor: Update on Long-Term Outcomes, Target Considerations and Future Directions

Deep brain stimulation (DBS) of the thalamic ventral intermediate nucleus is one of the main advanced neurosurgical treatments for drug-resistant tremor. However, not every patient may be eligible for this procedure. Nowadays, various other functional neurosurgical procedures are available. In particular cases, radiofrequency thalamotomy, focused ultrasound and radiosurgery are proven alternatives to DBS. Besides, other DBS targets, such as the posterior subthalamic area (PSA) or the dentato-rubro-thalamic tract (DRT), may be appraised as well. In this review, the clinical characteristics and pathophysiology of tremor syndromes, as well as long-term outcomes of DBS in different targets, will be summarized. The effectiveness and safety of lesioning procedures will be discussed, and an evidence-based clinical treatment approach for patients with drug-resistant tremor will be presented. Lastly, the future directions in the treatment of severe tremor syndromes will be elaborated.

Tremor Syndromes: An Updated Review

Tremor is the most commonly encountered movement disorder in clinical practice. A wide range of pathologies may manifest with tremor either as a presenting or predominant symptom. Considering the marked etiological and phenomenological heterogeneity, it would be desirable to develop a classification of tremors that reflects their underlying pathophysiology. The tremor task force of the International Parkinson Disease and Movement Disorders Society has worked toward this goal and proposed a new classification system. This system has remained a prime topic of scientific communications on tremor in recent times. The new classification is based on two axes: 1. based on the clinical features, history, and tremor characteristics and 2. based on the etiology of tremor. In this article, we discuss the key aspects of the new classification, review various tremor syndromes, highlight some of the controversies in the field of tremor, and share the potential future perspectives.

A deep explainable artificial intelligent framework for neurological disorders discrimination

Pathological hand tremor (PHT) is a common symptom of Parkinson's disease (PD) and essential tremor (ET), which affects manual targeting, motor coordination, and movement kinetics. Effective treatment and management of the symptoms relies on the correct and in-time diagnosis of the affected individuals, where the characteristics of PHT serve as an imperative metric for this purpose. Due to the overlapping features of the corresponding symptoms, however, a high level of expertise and specialized diagnostic methodologies are required to correctly distinguish PD from ET. In this work, we propose the data-driven [Formula: see text] model, which processes the kinematics of the hand in the affected individuals and classifies the patients into PD or ET. [Formula: see text] is trained over 90 hours of hand motion signals consisting of 250 tremor assessments from 81 patients, recorded at the London Movement Disorders Centre, ON, Canada. The [Formula: see text] outperforms its state-of-the-art counterparts achieving exceptional differential diagnosis accuracy of [Formula: see text]. In addition, using the explainability and interpretability measures for machine learning models, clinically viable and statistically significant insights on how the data-driven model discriminates between the two groups of patients are achieved.

Visualisation of Parkinsonian, essential and physiological tremor planes in 3Dspace

Based on the fact that tremors display some distinct 3D spatial characteristics, we decided to visualise tremor planes in 3D space. We obtained 3-axial linear accelerometer signals of hand tremors from 58 patients with Parkinson´s disease (PD), 37 with isolated resting tremor (iRT), 75 with essential tremor (ET), and 44 healthy volunteers with physiological tremor (Ph). For each group analysis was done with subsequent spatial 3D regression of the input data i.e. along the x, y and z axes; the projected vector lengths in the individual (vertical transversal XY, vertical longitudinal XZ and horizontal YZ) reference frame planes and their angles. Most meaningful and statistically significant differences were found in the analyses of the 3D vector lengths. The tremor of the PD and the iRT group was oriented mainly in the horizontal YZ plane. The tremors of the patients with ET and Ph were oriented approximately in the midway between the all three referential planes with less tilt toward the vertical longitudinal XZ plane.

A-WEAR Bracelet for Detection of Hand Tremor and Bradykinesia in Parkinson's Patients

Parkinson's disease patients face numerous motor symptoms that eventually make their life different from those of normal healthy controls. Out of these motor symptoms, tremor and bradykinesia, are relatively prevalent in all stages of this disease. The assessment of these symptoms is usually performed by traditional methods where the accuracy of results is still an open question. This research proposed a solution for an objective assessment of tremor and bradykinesia in subjects with PD (10 older adults aged greater than 60 years with tremor and 10 older adults aged greater than 60 years with bradykinesia) and 20 healthy older adults aged greater than 60 years. Physical movements were recorded by means of an AWEAR bracelet developed using inertial sensors, i.e., 3D accelerometer and gyroscope. Participants performed upper extremities motor activities as adopted by neurologists during the clinical assessment based on Unified Parkinson's Disease Rating Scale (UPDRS). For discriminating the patients from healthy controls, temporal and spectral features were extracted, out of which non-linear temporal and spectral features show greater difference. Both supervised and unsupervised machine learning classifiers provide good results. Out of 40 individuals, neural net clustering discriminated 34 individuals in correct classes, while the KNN approach discriminated 91.7% accurately. In a clinical environment, the doctor can use the device to comprehend the tremor and bradykinesia of patients quickly and with higher accuracy.

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.

Deep Learning Identifies Digital Biomarkers for Self-Reported Parkinson's Disease

Large-scale population screening and in-home monitoring for patients with Parkinson's disease (PD) has so far been mainly carried out by traditional healthcare methods and systems. Development of mobile health may provide an independent, future method to detect PD. Current PD detection algorithms will benefit from better generalizability with data collected in real-world situations. In this paper, we report the top-performing smartphone-based method in the recent DREAM Parkinson's Disease Digital Biomarker Challenge for digital diagnosis of PD. Utilizing real-world accelerometer records, this approach differentiated PD from control subjects with an area under the receiver-operating characteristic curve of 0.87 by 3D augmentation of accelerometer records, a significant improvement over other state-of-the-art methods. This study paves the way for future at-home screening of PD and other neurodegenerative conditions affecting movement.

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.

PHTNet: Characterization and Deep Mining of Involuntary Pathological Hand Tremor using Recurrent Neural Network Models

The global aging phenomenon has increased the number of individuals with age-related neurological movement disorders including Parkinson's Disease (PD) and Essential Tremor (ET). Pathological Hand Tremor (PHT), which is considered among the most common motor symptoms of such disorders, can severely affect patients' independence and quality of life. To develop advanced rehabilitation and assistive technologies, accurate estimation/prediction of nonstationary PHT is critical, however, the required level of accuracy has not yet been achieved. The lack of sizable datasets and generalizable modeling techniques that can fully represent the spectrotemporal characteristics of PHT have been a critical bottleneck in attaining this goal. This paper addresses this unmet need through establishing a deep recurrent model to predict and eliminate the PHT component of hand motion. More specifically, we propose a machine learning-based, assumption-free, and real-time PHT elimination framework, the PHTNet, by incorporating deep bidirectional recurrent neural networks. The PHTNet is developed over a hand motion dataset of 81 ET and PD patients collected systematically in a movement disorders clinic over 3 years. The PHTNet is the first intelligent systems model developed on this scale for PHT elimination that maximizes the resolution of estimation and allows for prediction of future and upcoming sub-movements.

The Rehapiano-Detecting, Measuring, and Analyzing Action Tremor Using Strain Gauges

We have developed a device, the Rehapiano, for the fast and quantitative assessment of action tremor. It uses strain gauges to measure force exerted by individual fingers. This article verifies the device's capability to measure and monitor the development of upper limb tremor. The Rehapiano uses a precision, 24-bit, analog-to-digital converter and an Arduino microcomputer to transfer raw data via a USB interface to a computer for processing, database storage, and evaluation. First, our experiments validated the device by measuring simulated tremors with known frequencies. Second, we created a measurement protocol, which we used to measure and compare healthy patients and patients with Parkinson's disease. Finally, we evaluated the repeatability of a quantitative assessment. We verified our hypothesis that the Rehapiano is able to detect force changes, and our experimental results confirmed that our system is capable of measuring action tremor. The Rehapiano is also sensitive enough to enable the quantification of Parkinsonian tremors.

Artifact Mimicking Ictal Epileptiform Activity in EEG

Although the EEG is designed to record cerebral activity, it also frequently records activity from extracerebral sources, leading to artifact. Differentiating rhythmical artifact from true electrographic ictal activity remains a substantial challenge to even experienced electroencephalographers because the sources of artifact able to mimic ictal activity on EEG have continued to increase with the advent of technology. Knowledge of the characteristics of the polarity and physiologic electrical fields of the brain, as opposed to those generated by the eyes, heart, and muscles, allows the electroencephalographer to intuitively recognize noncerebrally generated waveforms. In this review, we provide practical guidelines for the EEG interpreter to correctly identify physiologic and nonphysiologic artifacts capable of mimicking electrographic seizures. In addition, we further elucidate the common pitfalls in artifact interpretation and the costly impact of epilepsy misdiagnosis due to artifact.

Nigral iron deposition in common tremor disorders

OBJECTIVE

We investigated R2* relaxation rates as a marker of iron content in the substantia nigra in patients with common tremor disorders and explored their diagnostic properties.

METHODS

Mean nigral R2* rates were measured in 40 patients with tremor-dominant Parkinson's disease (PD), 15 with tremor in dystonia, 25 with essential tremor, and 25 healthy controls.

RESULTS

Tremor-dominant PD patients had significantly higher nigral R2* values (34.1 ± 5.7) than those with tremor in dystonia (30.0 ± 3.9), essential tremor (30.6 ± 4.8), and controls (30.0 ± 2.8). An R2* threshold of 31.15 separated tremor-dominant PD from controls with a sensitivity and specificity of 67.5% and 72%. The sensitivity and specificity for discrimination between PD and non-PD tremor patients was 67.5% and 60%.

CONCLUSION

Iron content in the substantia nigra is significantly higher in tremor-dominant PD than in tremor in dystonia, essential tremor, and controls. Because of the considerable overlap, nigral R2* cannot be suggested as a useful diagnostic tool. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Are Clinical Certainty Ratings Helpful in the Diagnosis of Parkinson's Disease?

Background

Clinical diagnostic criteria for PD rely on rest tremor, bradykinesia, and rigidity. These features are non-specific and neuropathological confirmation remains the gold standard for diagnosis. This study presents data on clinical certainty ratings in autopsy-proven PD.

Methods

Subjects were assessed annually by a movement disorders specialist and assigned to a clinical certainty group for PD based on multiple clinical features before autopsy. The three groups considered for analysis are as follows: Group I 0-49% certainty, Group II 50-89% certainty, and Group III 90-100% certainty. All subjects were autopsied and had a standardized neuropathological assessment.

Results

275 subjects were assigned a PD certainty at their last visit before death. Group I had 80 subjects, Group II 56 subjects, and Group III 139 subjects. The clinical features recorded in Group I, II, and III, were as follows: rest tremor, bradykinesia, rigidity, postural instability, asymmetric onset, persistent asymmetry, current response to dopaminergic treatment, motor fluctuations, and dyskinesia. Rigidity, postural instability, asymmetric onset, current response to dopaminergic treatment, motor fluctuation, and dyskinesia were more likely to be present in the group which was rated with higher certainty. The final diagnosis of PD was confirmed by neuropathological assessment in 85% of the patients in Group III as compared to 30% in Group II and 5% in Group I.

Conclusions

High certainty (90-100%) had strong positive predictive value (85%) for autopsy-proven PD as compared to either lower certainty groups (0-49% and 50-89%) which had lower predictive value (5% and 30% respectively).

Combined accelerometer and genetic analysis to differentiate essential tremor from Parkinson's disease

Essential tremor (ET) and Parkinson's disease (PD) are among the most common adult-onset tremor disorders. Clinical and pathological studies suggest that misdiagnosis of PD for ET, and vice versa, occur in anywhere from 15% to 35% of cases. Complex diagnostic procedures, such as dopamine transporter imaging, can be powerful diagnostic aids but are lengthy and expensive procedures that are not widely available. Preliminary studies suggest that monitoring of tremor characteristics with consumer grade accelerometer devices could be a more accessible approach to the discrimination of PD from ET, but these studies have been performed in well-controlled clinical settings requiring multiple maneuvers and oversight from clinical or research staff, and thus may not be representative of at-home monitoring in the community setting. Therefore, we set out to determine whether discrimination of PD vs. ET diagnosis could be achieved by monitoring research subject movements at home using consumer grade devices, and whether discrimination could be improved with the addition of genetic profiling of the type that is readily available through direct-to-consumer genetic testing services. Forty subjects with PD and 27 patients with ET were genetically profiled and had their movements characterized three-times a day for two weeks through a simple procedure meant to induce rest tremors. We found that tremor characteristics could be used to predict diagnosis status (sensitivity = 76%, specificity = 65%, area under the curve (AUC) = 0.75), but that the addition of genetic risk information, via a PD polygenic risk score, did not improve discriminatory power (sensitivity = 80%, specificity = 65%, AUC = 0.73).

Tremor severity in Parkinson's disease and cortical changes of areas controlling movement sequencing: A preliminary study

There remains much to learn about the changes in cortical anatomy that are associated with tremor severity in Parkinson's disease (PD). For this reason, we used a combination of structural neuroimaging to measure cortical thickness and neurophysiological studies to analyze whether PD tremor was associated with cortex integrity. Magnetic resonance imaging and neurophysiological assessment were performed in 13 nondemented PD patients (9 women, 69.2%) with a clearly tremor-dominant phenotype. Cortical reconstruction and volumetric segmentation were performed with the Freesurfer image analysis software. Assessment of tremor was performed by means of high-density surface electromyography (hdEMG) and inertial measurement units (IMUs). Individual motor unit discharge patterns were identified from surface hdEMG and tremor metrics quantifying motor unit synchronization from IMUs. Increased motor unit synchronization (i.e., more severe tremor) was associated with cortical changes (i.e., atrophy) in wide-spread cortical areas, including caudal middle frontal regions bilaterally (dorsal premotor cortices), left inferior parietal lobe (posterior parietal cortex), left lateral orbitofrontal cortex, cingulate cortex bilaterally, left posterior and transverse temporal cortex, and left occipital lobe, as well as reduced left middle temporal volume. Given that the majority of these areas are involved in controlling movement sequencing, our results support Albert's classic hypothesis that PD tremor may be the result of an involuntary activation of a program of motor behavior used in the genesis of rapid voluntary alternating movements.