Detection of evoked resonant neural activity in Parkinson's disease.

Objective. This study investigated a machine-learning approach to detect the presence of evoked resonant neural activity (ERNA) recorded during deep brain stimulation (DBS) of the subthalamic nucleus (STN) in people with Parkinson's disease.Approach. Seven binary classifiers were trained to distinguish ERNA from the background neural activity using eight different time-domain signal features.Main results. Nested cross-validation revealed a strong classification performance of 99.1% accuracy, with 99.6% specificity and 98.7% sensitivity to detect ERNA. Using a semi-simulated ERNA dataset, the results show that a signal-to-noise ratio of 15 dB is required to maintain a 90% classifier sensitivity. ERNA detection is feasible with an appropriate combination of signal processing, feature extraction and classifier. Future work should consider reducing the computational complexity for use in real-time applications.Significance. The presence of ERNA can be used to indicate the location of a DBS electrode array during implantation surgery. The confidence score of the detector could be useful for assisting clinicians to adjust the position of the DBS electrode array inside/outside the STN.

Clinical outcomes of deep brain stimulation for obsessive-compulsive disorder: Insight as a predictor of symptom changes.

AIM: Deep brain stimulation (DBS) is a safe and effective treatment option for people with refractory obsessive-compulsive disorder (OCD). Yet our understanding of predictors of response and prognostic factors remains rudimentary, and long-term comprehensive follow-ups are lacking. We aim to investigate the efficacy of DBS therapy for OCD patients, and predictors of clinical response. METHODS: Eight OCD participants underwent DBS stimulation of the nucleus accumbens (NAc) in an open-label longitudinal trial, duration of follow-up varied between 9 months and 7 years. Post-operative care involved comprehensive fine tuning of stimulation parameters and adjunct multidisciplinary therapy. RESULTS: Six participants achieved clinical response (35% improvement in obsessions and compulsions on the Yale Brown Obsessive Compulsive Scale (YBOCS)) within 6-9 weeks, response was maintained at last follow up. On average, the YBOCS improved by 45% at last follow up. Mixed linear modeling elucidated directionality of symptom changes: insight into symptoms strongly predicted (P = 0.008) changes in symptom severity during DBS therapy, likely driven by initial changes in depression and anxiety. Precise localization of DBS leads demonstrated that responders most often had their leads (and active contacts) placed dorsal compared to non-responders, relative to the Nac. CONCLUSION: The clinical efficacy of DBS for OCD is demonstrated, and mediators of changes in symptoms are proposed. The symptom improvements within this cohort should be seen within the context of the adjunct psychological and biopsychosocial care that implemented a shared decision-making approach, with flexible iterative DBS programming. Further research should explore the utility of insight as a clinical correlate of response. The trial was prospectively registered with the ANZCTR (ACTRN12612001142820).

Evaluation of the PaCER Algorithm for Postoperative Subthalamic Nucleus Deep Brain Stimulation Electrode Localization.

Deep Brain Stimulation (DBS) is an established therapy for many movement disorders. DBS entails electrical stimulation of precise brain structures using permanently implanted electrodes. Following implantation, locating the electrodes relative to the target brain structure assists patient outcome optimization. Here we evaluated an open-source automatic algorithm (PaCER) to localize individual electrodes on Computed Tomography imaging (co-registered to Magnetic Resonance Imaging). In a dataset of 111 participants, we found a modified version of the algorithm matched manual-markups with median error less than 0.191 mm (interquartile range 0.698 mm). Given the error is less than the voxel resolution (1 mm3) of the images, we conclude that the automatic algorithm is suitable for DBS electrode localizations.Clinical Relevance- Automated DBS electrode localization identifies the closest electrode to the target brain structure; allowing the neurologist to direct electrical stimulation to maximize patient outcomes. Further, if none of the electrodes are deemed suitable, localization will guide re-implantation.

Plug-and-play microphones for recording speech and voice with smart devices.

INTRODUCTION Smart devices are widely available and capable of quickly recording and uploading speech segments for health-related analysis. The switch from laboratory recordings with professional-grade microphone set ups to remote, smart device-based recordings offers immense potential for the scalability of voice assessment. Yet, a growing body of literature points to a wide heterogeneity among acoustic metrics for their robustness to variation in recording devices. The addition of consumer-grade plug-and-play microphones has been proposed as a possible solution. Our aim was to assess if the addition of consumer-grade plug-and-play microphones increase the acoustic measurement agreement between ultra-portable devices and a reference microphone. METHODS Speech was simultaneously recorded by a reference high-quality microphone commonly used in research, and by two configurations with plug-and-play microphones. Twelve speech-acoustic features were calculated using recordings from each microphone to determine the agreement intervals in measurements between microphones. Agreement intervals were then compared to expected deviations in speech in various neurological conditions. Each microphone's response to speech and to silence were characterized through acoustic analysis to explore possible reasons for differences in acoustic measurements between microphones. The statistical differentiation of two groups, neurotypical and people with Multiple Sclerosis, using metrics from each tested microphone was compared to that of the reference microphone. RESULTS The two consumer-grade plug-and-play microphones favoured high frequencies (mean centre of gravity difference ≥ +175.3Hz) and recorded more noise (mean difference in signal-to-noise ≤ -4.2dB) when compared to the reference microphone. Between consumer-grade microphones, differences in relative noise were closely related to distance between the microphone and the speaker's mouth. Agreement intervals between the reference and consumer-grade microphones remained under disease-expected deviations only for fundamental frequency (f0, agreement interval ≤0.06Hz), f0 instability (f0 CoV, agreement interval ≤0.05%) and for tracking of second formant movement (agreement interval ≤1.4Hz/millisecond). Agreement between microphones was poor for other metrics, particularly for fine timing metrics (mean pause length and pause length variability for various tasks). The statistical difference between the two groups of speakers was smaller with the plug-and-play than with the reference microphone. CONCLUSION Measurement of f0 and F2 slope were robust to variation in recording equipment while other acoustic metrics were not. Thus, the tested plug-and-play microphones should not be used interchangeably with professional-grade microphones for speech analysis. Plug-and-play microphones may assist in equipment standardization within speech studies, including remote or self-recording, possibly with small loss in accuracy and statistical power as observed in this study.

Anatomical targeting for electrode localization in subthalamic nucleus deep brain stimulation: A comparative study.

BACKGROUND AND PURPOSE: In deep brain stimulation (DBS), accurate electrode placement is essential for optimizing patient outcomes. Localizing electrodes enables insight into therapeutic outcomes and development of metrics for use in clinical trials. Methods of defining anatomical targets have been described with varying accuracy and objectivity. To assess variability in anatomical targeting, we compare four methods of defining an appropriate target for DBS of the subthalamic nucleus for Parkinson's disease. METHODS: The methods compared are direct visualization, red nucleus-based indirect targeting, mid-commissural point-based indirect targeting, and automated template-based targeting. This study assessed 226 hemispheres in 113 DBS recipients (39 females, 73 males, 62.2 ± 7.7 years). We utilized the electrode placement error (the Euclidean distance between the defined target and closest DBS electrode) as a metric for comparative analysis. Pairwise differences in electrode placement error across the four methods were compared using the Kruskal-Wallis H-test and Wilcoxon signed-rank tests. RESULTS: Interquartile ranges of the differences in electrode placement error spanned 1.18-1.56 mm. A Kruskal-Wallis H-test reported a statistically significant difference in the median of at least two groups (H(5) = 41.052, p < .001). Wilcoxon signed-rank tests reported statistically significant difference in two comparisons: direct visualization versus red nucleus-based indirect, and direct visualization versus automated template-based methods (T < 9215, p < .001). CONCLUSIONS: All methods were similarly discordant in their relative accuracy, despite having significant technical differences in their application. The differing protocols and technical aspects of each method, however, have the implication that one may be more practical depending on the clinical or research application at hand.

Can brain signals and anatomy refine contact choice for deep brain stimulation in Parkinson's disease?

INTRODUCTION: Selecting the ideal contact to apply subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson's disease is time-consuming and reliant on clinical expertise. The aim of this cohort study was to assess whether neuronal signals (beta oscillations and evoked resonant neural activity (ERNA)), and the anatomical location of electrodes, can predict the contacts selected by long-term, expert-clinician programming of STN-DBS. METHODS: We evaluated 92 hemispheres of 47 patients with Parkinson's disease receiving chronic monopolar and bipolar STN-DBS. At each contact, beta oscillations and ERNA were recorded intraoperatively, and anatomical locations were assessed. How these factors, alone and in combination, predicted the contacts clinically selected for chronic deep brain stimulation at 6 months postoperatively was evaluated using a simple-ranking method and machine learning algorithms. RESULTS: The probability that each factor individually predicted the clinician-chosen contact was as follows: ERNA 80%, anatomy 67%, beta oscillations 50%. ERNA performed significantly better than anatomy and beta oscillations. Combining neuronal signal and anatomical data did not improve predictive performance. CONCLUSION: This work supports the development of probability-based algorithms using neuronal signals and anatomical data to assist programming of deep brain stimulation.

Towards guided and automated programming of subthalamic area stimulation in Parkinson's disease.

Selecting the ideal contact to apply subthalamic nucleus deep brain stimulation in Parkinson's disease can be an arduous process, with outcomes highly dependent on clinician expertise. This study aims to assess whether neuronal signals recorded intraoperatively in awake patients, and the anatomical location of contacts, can assist programming. In a cohort of 14 patients with Parkinson's disease, implanted with subthalamic nucleus deep brain stimulation, the four contacts on each lead in the 28 hemispheres were ranked according to proximity to a nominated ideal anatomical location and power of the following neuronal signals: evoked resonant neural activity, beta oscillations and high-frequency oscillations. We assessed how these rankings predicted, on each lead: (i) the motor benefit from deep brain stimulation applied through each contact and (ii) the 'ideal' contact to apply deep brain stimulation. The ranking of contacts according to each factor predicted motor benefit from subthalamic nucleus deep brain stimulation, as follows: evoked resonant neural activity; r 2 = 0.50, Akaike information criterion 1039.9, beta; r 2 = 0.50, Akaike information criterion 1041.6, high-frequency oscillations; r 2 = 0.44, Akaike information criterion 1057.2 and anatomy; r 2 = 0.49, Akaike information criterion 1048.0. Combining evoked resonant neural activity, beta and high-frequency oscillations ranking data yielded the strongest predictive model (r 2 = 0.61, Akaike information criterion 1021.5). The 'ideal' contact (yielding maximal benefit) was ranked first according to each factor in the following proportion of hemispheres; evoked resonant neural activity 18/28, beta 17/28, anatomy 16/28, high-frequency oscillations 7/28. Across hemispheres, the maximal available deep brain stimulation benefit did not differ from that yielded by contacts chosen by clinicians for chronic therapy or contacts ranked first according to evoked resonant neural activity. Evoked resonant neural activity, beta oscillations and anatomy similarly predicted how motor benefit from subthalamic nucleus deep brain stimulation varied across contacts on each lead. This could assist programming by providing a probability ranking of contacts akin to a 'monopolar survey'. However, these factors identified the 'ideal' contact in only a proportion of hemispheres. More advanced signal processing and anatomical techniques may be needed for the full automation of contact selection.

Electrically evoked and spontaneous neural activity in the subthalamic nucleus under general anesthesia.

OBJECTIVE: Deep brain stimulation (DBS) surgery is commonly performed with the patient awake to facilitate assessments of electrode positioning. However, awake neurosurgery can be a barrier to patients receiving DBS. Electrode implantation can be performed with the patient under general anesthesia (GA) using intraoperative imaging, although such techniques are not widely available. Electrophysiological features can also aid in the identification of target neural regions and provide functional evidence of electrode placement. Here we assess the presence and positional variation under GA of spontaneous beta and high-frequency oscillation (HFO) activity, and evoked resonant neural activity (ERNA), a novel evoked response localized to the subthalamic nucleus. METHODS: ERNA, beta, and HFO were intraoperatively recorded from DBS leads comprising four individual electrodes immediately after bilateral awake implantation into the subthalamic nucleus of 21 patients with Parkinson's disease (42 hemispheres) and after subsequent GA induction deep enough to perform pulse generator implantation. The main anesthetic agent was either propofol (10 patients) or sevoflurane (11 patients). RESULTS: GA reduced the amplitude of ERNA, beta, and HFO activity (p < 0.001); however, ERNA amplitudes remained large in comparison to spontaneous local field potentials. Notably, a moderately strong correlation between awake ERNA amplitude and electrode distance to an "ideal" therapeutic target within dorsal STN was preserved under GA (awake: ρ = -0.73, adjusted p value [padj] < 0.001; GA: ρ = -0.69, padj < 0.001). In contrast, correlations were diminished under GA for beta (awake: ρ = -0.45, padj < 0.001; GA: ρ = -0.13, padj = 0.12) and HFO (awake: ρ = -0.69, padj < 0.001; GA: ρ = -0.33, padj < 0.001). The largest ERNA occurred at the same electrode (awake vs GA) for 35/42 hemispheres (83.3%) and corresponded closely to the electrode selected by the clinician for chronic therapy at 12 months (awake ERNA 77.5%, GA ERNA 82.5%). The largest beta amplitude occurred at the same electrode (awake vs GA) for only 17/42 (40.5%) hemispheres and 21/42 (50%) for HFO. The electrode measuring the largest awake beta and HFO amplitudes corresponded to the electrode selected by the clinician for chronic therapy at 12 months in 60% and 70% of hemispheres, respectively. However, this correspondence diminished substantially under GA (beta 20%, HFO 35%). CONCLUSIONS: ERNA is a robust electrophysiological signal localized to the dorsal subthalamic nucleus subregion that is largely preserved under GA, indicating it could feasibly guide electrode implantation, either alone or in complementary use with existing methods.

Low-frequency STN-DBS provides acute gait improvements in Parkinson's disease: a double-blinded randomised cross-over feasibility trial.

BACKGROUND: Some people with Parkinson's disease (PD) report poorer dynamic postural stability following high-frequency deep brain stimulation of the subthalamic nucleus (STN-DBS), which may contribute to an increased falls risk. However, some studies have shown low-frequency (60 Hz) STN-DBS improves clinical measures of postural stability, potentially providing support for this treatment. This double-blind randomised crossover study aimed to investigate the effects of low-frequency STN-DBS compared to high-frequency stimulation on objective measures of gait rhythmicity in people with PD. METHODS: During high- and low-frequency STN-DBS and while off-medication, participants completed assessments of symptom severity and walking (e.g., Timed Up-and-Go). During comfortable walking, the harmonic ratio, an objective measures of gait rhythmicity, was derived from head- and trunk-mounted accelerometers to provide insight in dynamic postural stability. Lower harmonic ratios represent less rhythmic walking and have discriminated people with PD who experience falls. Linear mixed model analyses were performed on fourteen participants. RESULTS: Low-frequency STN-DBS significantly improved medial-lateral and vertical trunk rhythmicity compared to high-frequency. Improvements were independent of electrode location and total electrical energy delivered. No differences were noted between stimulation conditions for temporal gait measures, clinical mobility measures, motor symptom severity or the presence of gait retropulsion. CONCLUSIONS: This study provides evidence for the acute benefits of low-frequency stimulation for gait outcomes in STN-DBS PD patients, independent of electrode location. However, the perceived benefits of this therapy may be diminished for people who experienced significant tremor pre-operatively, as lower frequencies may cause these symptoms to re-emerge. TRIAL REGISTRATION: This study was prospectively registered with the Australian and New Zealand Clinical Trials Registry on 5 June 2018 (ACTRN12618000944235).

How accurately are subthalamic nucleus electrodes implanted relative to the ideal stimulation location for Parkinson's disease?

INTRODUCTION: The efficacy of subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) depends on how closely electrodes are implanted relative to an individual's ideal stimulation location. Yet, previous studies have assessed how closely electrodes are implanted relative to the planned location, after homogenizing data to a reference. Thus here, we measured how accurately electrodes are implanted relative to an ideal, dorsal STN stimulation location, assessed on each individual's native imaging. This measure captures not only the technical error of stereotactic implantation but also constraints imposed by planning a suitable trajectory. METHODS: This cross-sectional study assessed 226 electrodes in 113 consecutive PD patients implanted with bilateral STN-DBS by experienced clinicians utilizing awake, microelectrode guided, surgery. The error (Euclidean distance) between the actual electrode trajectory versus a nominated ideal, dorsal STN stimulation location was determined in each hemisphere on native imaging and predictive factors sought. RESULTS: The median electrode location error was 1.62 mm (IQR = 1.23 mm). This error exceeded 3 mm in 28/226 electrodes (12.4%). Location error did not differ between hemispheres implanted first or second, suggesting brain shift was minimised. Location error did not differ between electrodes positioned with (48/226), or without, a preceding microelectrode trajectory shift (suggesting such shifts were beneficial). There was no relationship between location error and case order, arguing against a learning effect. DISCUSSION/CONCLUSION: The proximity of STN-DBS electrodes to a nominated ideal, dorsal STN, stimulation location is highly variable, even when implanted by experienced clinicians with brain shift minimized, and without evidence of a learning effect. Using this measure, we found that assessments on awake patients (microelectrode recordings and clinical examination) likely yielded beneficial intraoperative decisions to improve positioning. In many patients the error is likely to have reduced therapeutic efficacy. More accurate methods to implant STN-DBS electrodes relative to the ideal stimulation location are needed.

Acoustic Speech Analytics Are Predictive of Cerebellar Dysfunction in Multiple Sclerosis.

Speech production relies on motor control and cognitive processing and is linked to cerebellar function. In diseases where the cerebellum is impaired, such as multiple sclerosis (MS), speech abnormalities are common and can be detected by instrumental assessments. However, the potential of speech assessments to be used to monitor cerebellar impairment in MS remains unexplored. The aim of this study is to build an objectively measured speech score that reflects cerebellar function, pathology and quality of life in MS. Eighty-five people with MS and 21 controls participated in the study. Speech was independently assessed through objective acoustic analysis and blind expert listener ratings. Cerebellar function and overall disease disability were measured through validated clinical scores; cerebellar pathology was assessed via magnetic resonance imaging, and validated questionnaires informed quality of life. Selected speech variables were entered in a regression model to predict cerebellar function. The resulting model was condensed into one composite speech score and tested for prediction of abnormal 9-hole peg test (9HPT), and for correlations with the remaining cerebellar scores, imaging measurements and self-assessed quality of life. Slow rate of syllable repetition and increased free speech pause percentage were the strongest predictors of cerebellar impairment, complemented by phonatory instability. Those variables formed the acoustic composite score that accounted for 54% of variation in cerebellar function, correlated with cerebellar white matter volume (r = 0.3, p = 0.017), quality of life (r = 0.5, p < 0.001) and predicted an abnormal 9HPT with 85% accuracy. An objective multi-feature speech metric was highly representative of motor cerebellar impairment in MS.

OnabotulinumtoxinA treatment for MS-tremor modifies fMRI tremor response in central sensory-motor integration areas.

BACKGROUND: Treatment of tremor in MS is an unmet need. OnabotulinumtoxinA (BoNT-A) has shown promising results; however, little is known regarding its effects on the brain. The clinical presentation of tremor MS is shown to depend on subcortical neural damage and cortical neural plasticity. This study aimed to identify effects of onabotulinumtoxinA (BoNT-A) on brain activation in MS and upper-limb tremor using functional MRI. METHODS: Forty-three MS participants with tremor were randomized to receive intramuscular injections of placebo (n = 22) or BoNT-A (n = 21). Tremor was quantified using the Bain score (0-10) for severity, handwriting and Archimedes drawing at baseline, 6 weeks and 12 weeks. Functional MRI activation within two previously identified clusters, ipsilateral inferior parietal cortex (IPL) and premotor/supplementary motor cortex (SMC) of compensatory activity, was measured at baseline and 6 weeks. RESULTS: Treatment with BoNT-A resulted in improved handwriting tremor at 6 weeks (p = 0.049) and 12 weeks (p = 0.014), and tremor severity -0.79 (p = 0.007) at 12 weeks. Furthermore, the patients that received BoNT-A showed a reduction in activation within the IPL (p = 0.034), but not in the SMC. The change in IPL activation correlated with the reduction in tremor severity from baseline to 12 weeks (ß = 0.608; p = 0.015) in the BoNT-A group. No tremor and fMRI changes were seen in the placebo treated group. CONCLUSION: We have shown that reduction in MS-tremor severity after intramuscular injection with BoNT-A is associated with changes in brain activity in sensorimotor integration regions.

Functional neuroplasticity in response to cerebello-thalamic injury underpins the clinical presentation of tremor in multiple sclerosis.

BACKGROUND: Tremor is present in almost half of multiple sclerosis (MS) patients. The lack of understanding of its pathophysiology is hampering progress in development of treatments. OBJECTIVES: To clarify the structural and functional brain changes associated with the clinical phenotype of upper limb tremor in people with MS. METHODS: Fifteen healthy controls (46.1 ± 15.4 years), 27 MS participants without tremor (46.7 ± 11.6 years) and 42 with tremor (46.6 ± 11.5 years) were included. Tremor was quantified using the Bain score (0-10) for overall severity, handwriting and Archimedes spiral drawing. Functional magnetic resonance imaging activations were compared between participants groups during performance of a joystick task designed to isolate tremulous movement. Inflammation and atrophy of cerebello-thalamo-cortical brain structures were quantified. RESULTS: Tremor participants were found to have atrophy of the cerebellum and thalamus, and higher ipsilateral cerebellar lesion load compared to participants without tremor (p < 0.020). We found higher ipsilateral activation in the inferior parietal lobule, the premotor cortex and supplementary motor area in MS tremor participants compared to MS participants without tremor during the joystick task. Finally, stronger activation in those areas was associated with lower tremor severity. CONCLUSION: Subcortical neurodegeneration and inflammation along the cerebello-thalamo-cortical and cortical functional neuroplasticity contribute to the severity of tremor in MS.

Deep brain stimulation for Parkinson's disease modulates high-frequency evoked and spontaneous neural activity.

Deep brain stimulation is an established therapy for Parkinson's disease; however, its effectiveness is hindered by limited understanding of therapeutic mechanisms and the lack of a robust feedback signal for tailoring stimulation. We recently reported that subthalamic nucleus deep brain stimulation evokes a neural response resembling a decaying high-frequency (200-500 Hz) oscillation that typically has a duration of at least 10 ms and is localizable to the dorsal sub-region. As the morphology of this response suggests a propensity for the underlying neural circuitry to oscillate at a particular frequency, we have named it evoked resonant neural activity. Here, we determine whether this evoked activity is modulated by therapeutic stimulation - a critical attribute of a feedback signal. Furthermore, we investigated whether any related changes occurred in spontaneous local field potentials. Evoked and spontaneous neural activity was intraoperatively recorded from 19 subthalamic nuclei in patients with Parkinson's disease. Recordings were obtained before therapeutic stimulation and during 130 Hz stimulation at increasing amplitudes (0.67-3.38 mA), 'washout' of therapeutic effects, and non-therapeutic 20 Hz stimulation. Therapeutic efficacy was assessed using clinical bradykinesia and rigidity scores. The frequency and amplitude of evoked resonant neural activity varied with the level of 130 Hz stimulation (p < .001). This modulation coincided with improvement in bradykinesia and rigidity (p < .001), and correlated with spontaneous beta band suppression (p < .001). Evoked neural activity occupied a similar frequency band to spontaneous high-frequency oscillations (200-400 Hz), both of which decreased to around twice the 130 Hz stimulation rate. Non-therapeutic stimulation at 20 Hz evoked, but did not modulate, resonant activity. These results indicate that therapeutic deep brain stimulation alters the frequency of evoked and spontaneous oscillations recorded in the subthalamic nucleus that are likely generated by loops within the cortico-basal ganglia-thalamo-cortical network. Evoked resonant neural activity therefore has potential as a tool for providing insight into brain network function and has key attributes of a dynamic feedback signal for optimizing therapy.

An Instrumented Pull Test to Characterize Postural Responses.

Impairment of postural reflexes, termed postural instability, is a common and disabling deficit in Parkinson's disease. To assess postural reflexes, clinicians typically employ the pull test to grade corrective responses to a backward perturbation at the shoulders. However, the pull test is prone to issues with reliability and scaling (score/4). Here, we present an instrumented version of the pull test to more precisely quantify postural responses. Akin to the clinical test, pulls are manually administered except pull force is also recorded. Displacements of the trunk and feet are captured by a semi-portable motion tracking system. Raw data represent distance traveled (in millimeter units), making subsequent interpretation and analysis intuitive. The instrumented pull test also detects variabilities influencing pull test administration, such as pull force, thereby identifying and quantifying potential confounds that can be accounted for by statistical techniques. The instrumented pull test could have application in studies seeking to capture early abnormalities in postural responses, track postural instability over time, and detect responses to therapy.

A palm-worn device to quantify rigidity in Parkinson's disease.

BACKGROUND: Parkinsonian rigidity is identified on clinical examination as resistance to passive movement. Measurement of rigidity commonly relies on ordinal rating scales (MDS-UPDRS), however instrumented objective measures may provide greater mechanistic insight. NEW METHOD: We present a palm-worn instrument to objectively quantify rigidity on a continuous scale. The device employs a miniature motor to flex the third digit of the hand about the metacarpophalangeal joint whilst transducers record flexion/extension forces. We aim to determine congruence with the MDS-UPDRS, investigate sensitivity to the impact of deep brain stimulation (DBS) and contralateral movement, and make comparisons with healthy individuals. Eight participants with Parkinson's disease underwent evaluation during conditions: on and off DBS, and with and without contralateral limb movement to activate rigidity. During each DBS condition, wash-in/out effects were tracked using both our instrument and two blinded clinical raters. Sixteen healthy volunteers (age-matched/young) served as controls. RESULTS: Rigidity measured using our instrument had moderate agreement with the MDS-UPDRS and showed differences between therapeutic state, activation conditions, and disease/healthy cohorts. Rigidity gradually worsened over a one-hour period after DBS cessation, but improved more rapidly with DBS resumption. COMPARISON WITH EXISTING METHODS: Previous attempts to quantify rigidity include manual approaches where a clinician is required to manipulate limbs while sensors passively gather information, or large automated instruments to move the wrist or elbow. CONCLUSION: Given its ability to track changes in rigidity due to therapeutic intervention, our technique could have applications where continuous measurement is required or where a suitably qualified rater is absent.

Objective evaluation of bradykinesia in Parkinson's disease using an inexpensive marker-less motion tracking system.

OBJECTIVE: Quantification of bradykinesia (slowness of movement) is crucial for the treatment and monitoring of Parkinson's disease. Subjective observational techniques are the de-facto 'gold standard', but such clinical rating scales suffer from poor sensitivity and inter-rater variability. Although various technologies have been developed for assessing bradykinesia in recent years, most still require considerable expertise and effort to operate. Here we present a novel method to utilize an inexpensive off-the-shelf hand-tracker (Leap Motion) to quantify bradykinesia. APPROACH: Eight participants with Parkinson's disease receiving benefit from deep brain stimulation were recruited for the study. Participants were assessed 'on' and 'off' stimulation, with the 'on' condition repeated to evaluate reliability. Participants performed wrist pronation/supination, hand open/close, and finger-tapping tasks during each condition. Tasks were simultaneously captured by our software and rated by three clinicians. A linear regression model was developed to predict clinical scores and its performance was assessed with leave-one-subject-out cross validation. MAIN RESULTS: Aggregate bradykinesia scores predicted by our method were in strong agreement (R = 0.86) with clinical scores. The model was able to differentiate therapeutic states and comparison between the test-retest conditions yielded no significant difference (p  = 0.50). SIGNIFICANCE: These findings demonstrate that our method can objectively quantify bradykinesia in agreement with clinical observation and provide reliable measurements over time. The hardware is readily accessible, requiring only a modest computer and our software to perform assessments, thus making it suitable for both clinic- and home-based symptom tracking.

Validation of a precision tremor measurement system for multiple sclerosis.

BACKGROUND: Tremor is a debilitating symptom of Multiple Sclerosis (MS). Little is known about its pathophysiology and treatments are limited. Clinical trials investigating new interventions often rely on subjective clinical rating scales to provide supporting evidence of efficacy. NEW METHOD: We present a novel instrument (TREMBAL) which uses electromagnetic motion capture technology to quantify MS tremor. We aim to validate TREMBAL by comparison to clinical ratings using regression modelling with 310 samples of tremor captured from 13 MS participants who performed five different hand exercises during several follow-up visits. Minimum detectable change (MDC) and test-retest reliability were calculated and comparisons were made between MS tremor and data from 12 healthy volunteers. RESULTS: Velocity of the index finger was most congruent with clinical observation. Regression modelling combining different features, sensor configurations, and labelling exercises did not improve results. TREMBAL MDC was 84% of its initial measurement compared to 91% for the clinical rating. Intra-class correlations for test-retest reliability were 0.781 for TREMBAL and 0.703 for clinical ratings. Tremor was lower (p = 0.002) in healthy subjects. COMPARISON WITH EXISTING METHODS: Subjective scales have low sensitivity, suffer from ceiling effects, and mitigation against inter-rater variability is challenging. Inertial sensors are ubiquitous, however, their output is nonlinearly related to tremor frequency, compensation is required for gravitational artefacts, and their raw data cannot be intuitively comprehended. CONCLUSIONS: TREMBAL, compared with clinical ratings, gave measures in agreement with clinical observation, had marginally lower MDC, and similar test-retest reliability.

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging.

Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the preprocessing method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

What speech can tell us: A systematic review of dysarthria characteristics in Multiple Sclerosis.

IMPORTANCE: Multiple sclerosis produces neurological impairments that are variable in duration, severity and quality. Speech is frequently impaired, resulting in decreased communication skills and quality of life. Advancements in technology now makes it possible to use quantitative acoustic assessment of speech as biomarkers of disease progression. OBSERVATIONS: Four domains of speech have been identified: articulation (slow articulation and imprecise consonants), voice (pitch and loudness instability), respiration (decreased phonatory time and expiratory pressure) and prosody (longer and frequent pauses, deficient loudness control). Studies also explored I) predictive models for diagnosis of MS and of ataxia using speech variables, II) the relationship of dysarthria with cognition and III) very few studies correlated neuroimaging with dysarthria. We could not identify longitudinal studies of speech or dysarthria in Multiple Sclerosis. CONCLUSION AND RELEVANCE: Refinement of objective measures of speech has enhanced our understanding of Multiple Sclerosis-related deficits in cross-sectional analysis while both integrative and longitudinal studies are identified as major gaps. This review highlights the potential for using quantitative acoustic assessments as clinical endpoints for diagnosing, monitoring progression and treatment in disease modifying trials.