Adaptive, personalized closed-loop therapy for Parkinson's disease: biochemical, neurophysiological, and wearable sensing systems

Kinematic Effects of Combined Subthalamic and Dorsolateral Nigral Deep Brain Stimulation in Parkinson's Disease

Background

Additional stimulation of the substantia nigra (SNr) has been proposed to target axial symptoms and gait impairment in patients with Parkinson's disease (PD).

Objective

This study aimed to characterize effects of combined deep brain stimulation (DBS) of the subthalamic nucleus (STN) and SNr on gait performance in PD and to map stimulation sites within the SNr.

Methods

In a double-blinded crossover design, 10 patients with PD and gait impairment underwent clinical examination and kinematic assessment with STN DBS, combined STN+SNr DBS and OFF DBS 30 minutes after reprogramming. To confirm stimulation within the SNr, electrodes, active contacts, and stimulation volumes were modeled in a common space and overlap with atlases of SNr was computed.

Results

Overlap of stimulation volumes with dorsolateral SNr was confirmed for all patients. UPDRS III, scoring of freezing during turning and transitioning, stride length, stride velocity, and range of motion of shank, knee, arm, and trunk as well as peak velocities during turning and transitions and turn duration were improved with STN DBS compared to OFF. On cohort level, no further improvement was observed with combined STN+SNr DBS but additive improvement of spatiotemporal gait parameters was observed in individual subjects.

Conclusions

Combined high frequency DBS of the STN and dorsolateral SNr did not consistently result in additional short-term kinematic or clinical benefit compared to STN DBS. Stimulation intervals, frequency, and patient selection for target symptoms as well as target region within the SNr need further refinement in future trials.

Clinical Management of Movement Disorders

Movement disorders include a wide and heterogeneous variety of signs and syndromes, which are classified as hyperkinetic [...].

Intraoperative Local Field Potential Beta Power and Three-Dimensional Neuroimaging Mapping Predict Long-Term Clinical Response to Deep Brain Stimulation in Parkinson Disease: A Retrospective Study

BACKGROUND

Directional deep brain stimulation (DBS) leads allow a fine-tuning control of the stimulation field, however, this new technology could increase the DBS programming time because of the higher number of the possible combinations used in directional DBS than in standard nondirectional electrodes. Neuroimaging leads localization techniques and local field potentials (LFPs) recorded from DBS electrodes implanted in basal ganglia are among the most studied biomarkers for DBS programing.

OBJECTIVE

This study aimed to evaluate whether intraoperative LFPs beta power and neuroimaging reconstructions correlate with contact selection in clinical programming of DBS in patients with Parkinson disease (PD).

MATERIALS AND METHODS

In this retrospective study, routine intraoperative LFPs recorded from all contacts in the subthalamic nucleus (STN) of 14 patients with PD were analyzed to calculate the beta band power for each contact. Neuroimaging reconstruction obtained through Brainlab Elements Planning software detected contacts localized within the STN. Clinical DBS programming contact scheme data were collected after one year from the implant. Statistical analysis evaluated the diagnostic performance of LFPs beta band power and neuroimaging data for identification of the contacts selected with clinical programming. We evaluated whether the most effective contacts identified based on the clinical response after one year from implant were also those with the highest level of beta activity and localized within the STN in neuroimaging reconstruction.

RESULTS

LFPs beta power showed a sensitivity of 67%, a negative predictive value (NPV) of 84%, a diagnostic odds ratio (DOR) of 2.7 in predicting the most effective contacts as evaluated through the clinical response. Neuroimaging reconstructions showed a sensitivity of 62%, a NPV of 77%, a DOR of 1.20 for contact effectivity prediction. The combined use of the two methods showed a sensitivity of 87%, a NPV of 87%, a DOR of 2.7 for predicting the clinically more effective contacts.

CONCLUSIONS

The combined use of LFPs beta power and neuroimaging localization and segmentations predict which are the most effective contacts as selected on the basis of clinical programming after one year from implant of DBS. The use of predictors in contact selection could guide clinical programming and reduce time needed for it.

Clinical neurophysiological interrogation of motor slowing: A critical step towards tuning adaptive deep brain stimulation

OBJECTIVE

Subthalamic nucleus (STN) beta activity (13-30 Hz) is the most accepted biomarker for adaptive deep brain stimulation (aDBS) for Parkinson's disease (PD). We hypothesize that different frequencies within the beta range may exhibit distinct temporal dynamics and, as a consequence, different relationships to motor slowing and adaptive stimulation patterns. We aim to highlight the need for an objective method to determine the aDBS feedback signal.

METHODS

STN LFPs were recorded in 15 PD patients at rest and while performing a cued motor task. The impact of beta bursts on motor performance was assessed for different beta candidate frequencies: the individual frequency strongest associated with motor slowing, the individual beta peak frequency, the frequency most modulated by movement execution, as well as the entire-, low- and high beta band. How these candidate frequencies differed in their bursting dynamics and theoretical aDBS stimulation patterns was further investigated.

RESULTS

The individual motor slowing frequency often differs from the individual beta peak or beta-related movement-modulation frequency. Minimal deviations from a selected target frequency as feedback signal for aDBS leads to a substantial drop in the burst overlapping and in the alignment of the theoretical onset of stimulation triggers (to ∼ 75% for 1 Hz, to ∼ 40% for 3 Hz deviation).

CONCLUSIONS

Clinical-temporal dynamics within the beta frequency range are highly diverse and deviating from a reference biomarker frequency can result in altered adaptive stimulation patterns.

SIGNIFICANCE

A clinical-neurophysiological interrogation could be helpful to determine the patient-specific feedback signal for aDBS.

Levodopa-Induced Dyskinesias in Parkinson's Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions

Since its first introduction, levodopa has become the cornerstone for the treatment of Parkinson's disease and remains the leading therapeutic choice for motor control therapy so far. Unfortunately, the subsequent appearance of abnormal involuntary movements, known as dyskinesias, is a frequent drawback. Despite the deep knowledge of this complication, in terms of clinical phenomenology and the temporal relationship during a levodopa regimen, less is clear about the pathophysiological mechanisms underpinning it. As the disease progresses, specific oscillatory activities of both motor cortical and basal ganglia neurons and variation in levodopa metabolism, in terms of the dopamine receptor stimulation pattern and turnover rate, underlie dyskinesia onset. This review aims to provide a global overview on levodopa-induced dyskinesias, focusing on pathophysiology, clinical manifestations, therapy management strategies and future directions.

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Closed-loop adaptive deep brain stimulation (aDBS) can deliver individualized therapy at an unprecedented temporal precision for neurological disorders. This has the potential to lead to a breakthrough in neurotechnology, but the translation to clinical practice remains a significant challenge. Via bidirectional implantable brain-computer-interfaces that have become commercially available, aDBS can now sense and selectively modulate pathophysiological brain circuit activity. Pilot studies investigating different aDBS control strategies showed promising results, but the short experimental study designs have not yet supported individualized analyses of patient-specific factors in biomarker and therapeutic response dynamics. Notwithstanding the clear theoretical advantages of a patient-tailored approach, these new stimulation possibilities open a vast and mostly unexplored parameter space, leading to practical hurdles in the implementation and development of clinical trials. Therefore, a thorough understanding of the neurophysiological and neurotechnological aspects related to aDBS is crucial to develop evidence-based treatment regimens for clinical practice. Therapeutic success of aDBS will depend on the integrated development of strategies for feedback signal identification, artifact mitigation, signal processing, and control policy adjustment, for precise stimulation delivery tailored to individual patients. The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years. Finally, it highlights the importance of interdisciplinary clinical neurotechnological research within and across DBS centers, toward an individualized patient-centered approach to invasive brain stimulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Closed-Loop Adaptive Deep Brain Stimulation in Parkinson's Disease: Procedures to Achieve It and Future Perspectives

Parkinson's disease (PD) is a neurodegenerative disease with a heavy burden on patients, families, and society. Deep brain stimulation (DBS) can improve the symptoms of PD patients for whom medication is insufficient. However, current open-loop uninterrupted conventional DBS (cDBS) has inherent limitations, such as adverse effects, rapid battery consumption, and a need for frequent parameter adjustment. To overcome these shortcomings, adaptive DBS (aDBS) was proposed to provide responsive optimized stimulation for PD. This topic has attracted scientific interest, and a growing body of preclinical and clinical evidence has shown its benefits. However, both achievements and challenges have emerged in this novel field. To date, only limited reviews comprehensively analyzed the full framework and procedures for aDBS implementation. Herein, we review current preclinical and clinical data on aDBS for PD to discuss the full procedures for its achievement and to provide future perspectives on this treatment.

Spectral Topography of the Subthalamic Nucleus to Inform Next-Generation Deep Brain Stimulation

BACKGROUND

The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing-based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN).

OBJECTIVES

The aims were to systematically investigate the spectral topography, including a wide range of sub-bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS.

METHODS

STN-LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub-bands (delta, theta, alpha, low-beta, high-beta, low-gamma, high-gamma, and fast-gamma (FG) as well as low- and fast high-frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS.

RESULTS

The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior-superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub-bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher-frequency hot spots were predictive for the best rigidity response to DBS.

CONCLUSIONS

The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next-generation sensing-based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Deep brain stimulation - New programming algorithms and teleprogramming

INTRODUCTION

Thanks to a variety of factors, the field of neuromodulation has evolved significantly over the past decade. Developments include new indications and innovations of hardware, software, and stimulation techniques leading to an expansion in scope and role of these techniques as powerful therapies. They also imply the realization that practical application involves new nuances that make patient selection, surgical technique and the programming process even more complex, requiring continuous education and an organized structured approach.

AREAS COVERED

In this review, the authors explore the developments in deep brain stimulation technology, including electrodes, implantable pulse generators, contact configurations (i.e, directional leads and independent current control), remote programming and sensing using local field potentials.

EXPERT OPINION

The innovations in the field of deep brain stimulation discussed in this review potentially provide increased effectiveness and flexibility not only to improve therapeutic response but also to address troubleshooting challenges seen in clinical practice. Directional leads and shorter pulse widths may broaden the therapeutic window of stimulation, avoiding current spread to structures that might trigger stimulation-related side effects. Similarly, independent control of current to individual contacts allows for the shaping of the electric field. Finally, sensing and remote programming represent important developments for more effective and individualized patient care.

Quantitative High Density EEG Brain Connectivity Evaluation in Parkinson's Disease: The Phase Locking Value (PLV)

INTRODUCTION

The present study explores brain connectivity in Parkinson's disease (PD) and in age matched healthy controls (HC), using quantitative EEG analysis, at rest and during a motor tasks. We also evaluated the diagnostic performance of the phase locking value (PLV), a measure of functional connectivity, in differentiating PD patients from HCs.

METHODS

High-density, 64-channels, EEG data from 26 PD patients and 13 HC were analyzed. EEG signals were recorded at rest and during a motor task. Phase locking value (PLV), as a measure of functional connectivity, was evaluated for each group in a resting state and during a motor task for the following frequency bands: (i) delta: 2-4 Hz; (ii) theta: 5-7 Hz; (iii) alpha: 8-12 Hz; beta: 13-29 Hz; and gamma: 30-60 Hz. The diagnostic performance in PD vs. HC discrimination was evaluated.

RESULTS

Results showed no significant differences in PLV connectivity between the two groups during the resting state, but a higher PLV connectivity in the delta band during the motor task, in HC compared to PD. Comparing the resting state versus the motor task for each group, only HCs showed a higher PLV connectivity in the delta band during motor task. A ROC curve analysis for HC vs. PD discrimination, showed an area under the ROC curve (AUC) of 0.75, a sensitivity of 100%, and a negative predictive value (NPV) of 100%.

CONCLUSIONS

The present study evaluated the brain connectivity through quantitative EEG analysis in Parkinson's disease versus healthy controls, showing a higher PLV connectivity in the delta band during the motor task, in HC compared to PD. This neurophysiology biomarkers showed the potentiality to be explored in future studies as a potential screening biomarker for PD patients.

Neurophysiology tools to lower the stroke onset to treatment time during the golden hour: microwaves, bioelectrical impedance and near infrared spectroscopy

Reperfusion therapy administration timing in acute ischaemic stroke is the main determinant of patients' mortality and long-term disability. Indeed, the first hour from the stroke onset is defined the "golden hour", in which the treatment has the highest efficacy and lowest side effects. Delayed ambulance transport, inappropriate triage and difficulty in accessing CT scans lead to delayed onset to treatment time (OTT) in clinical practice. To date brain CT scan is needed to rule out intracranial haemorrhage, which is a major contraindication to thrombolytic therapy. The availability, dimension and portability make CT suitable mainly for intrahospital use, determining further delays in the therapies administration. This review aims at evaluating portable neurophysiology technologies developed with the scope of speeding up the diagnostic phase of acute stroke and, therefore, the initiation of intravenous thrombolysis. Medline databases were explored for studies concerning near infrared spectroscopy (NIRS), bioelectrical impedance spectroscopy (BIS) and Microwave imaging (MWI) as methods for stroke diagnosis. A total of 1368 articles were found, and 12 of these fit with our criteria and were included in the review. For each technology, the following parameters were evaluated: diagnostic accuracy, ability to differentiate ischaemic and haemorrhagic stroke, diagnosis time from stroke onset, portability and technology readiness level (TRL). All the described methods seem to be able to identify acute stroke even though the number of studies is very limited. Low cost and portability make them potentially usable during ambulance transport, possibly leading to a reduction of stroke OTT along with the related huge benefits in terms of patients outcome and health care costs. In addition, unlike standard imaging techniques, neurophysiological techniques could allow continuous monitoring of patients for timely intrahospital stroke diagnosis.KEY MESSAGESFirst hour from the stroke onset is defined the "golden hour", in which the treatment has the highest efficacy and lowest side effects.The delay for stroke onset to brain imaging time is one of the major reasons why only a minority of patients with acute ischaemic stroke are eligible to reperfusion therapies.Neurophysiology techniques (NIRS, BIS and MWI) could have a potential high impact in reducing the time to treatment in stroke patients.

Parkinson's Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis

Introduction: Gait features differ between Parkinson's disease (PD) and healthy subjects (HS). Kinematic alterations of gait include reduced gait speed, swing time, and stride length between PD patients and HS. Stride time and swing time variability are increased in PD patients with respect to HS. Additionally, dynamic parameters of asymmetry of gait are significantly different among the two groups. The aim of the present study is to evaluate which kind of gait analysis (dynamic or kinematic) is more informative to discriminate PD and HS gait features. Methods: In the present study, we analyzed gait dynamic and kinematic features of 108 PD patients and 88 HS from four cohorts of two datasets. Results: Kinematic features showed statistically significant differences among PD patients and HS for gait speed and time Up and Go test and for selected kinematic dispersion indices (standard deviation and interquartile range of swing, stance, and double support time). Dynamic features did not show any statistically significant difference between PD patients and HS. Discussion: Despite kinematics features like acceleration being directly proportional to dynamic features like ground reaction force, the results of this study showed the so-called force/rhythm dichotomy since kinematic features were more informative than dynamic ones.

Markerless Radio Frequency Indoor Monitoring for Telemedicine: Gait Analysis, Indoor Positioning, Fall Detection, Tremor Analysis, Vital Signs and Sleep Monitoring

Quantitative indoor monitoring, in a low-invasive and accurate way, is still an unmet need in clinical practice. Indoor environments are more challenging than outdoor environments, and are where patients experience difficulty in performing activities of daily living (ADLs). In line with the recent trends of telemedicine, there is an ongoing positive impulse in moving medical assistance and management from hospitals to home settings. Different technologies have been proposed for indoor monitoring over the past decades, with different degrees of invasiveness, complexity, and capabilities in full-body monitoring. The major classes of devices proposed are inertial-based sensors (IMU), vision-based devices, and geomagnetic and radiofrequency (RF) based sensors. In recent years, among all available technologies, there has been an increasing interest in using RF-based technology because it can provide a more accurate and reliable method of tracking patients' movements compared to other methods, such as camera-based systems or wearable sensors. Indeed, RF technology compared to the other two techniques has higher compliance, low energy consumption, does not need to be worn, is less susceptible to noise, is not affected by lighting or other physical obstacles, has a high temporal resolution without a limited angle of view, and fewer privacy issues. The aim of the present narrative review was to describe the potential applications of RF-based indoor monitoring techniques and highlight their differences compared to other monitoring technologies.

Dystonia Diagnosis: Clinical Neurophysiology and Genetics

Dystonia diagnosis is based on clinical examination performed by a neurologist with expertise in movement disorders. Clues that indicate the diagnosis of a movement disorder such as dystonia are dystonic movements, dystonic postures, and three additional physical signs (mirror dystonia, overflow dystonia, and geste antagonists/sensory tricks). Despite advances in research, there is no diagnostic test with a high level of accuracy for the dystonia diagnosis. Clinical neurophysiology and genetics might support the clinician in the diagnostic process. Neurophysiology played a role in untangling dystonia pathophysiology, demonstrating characteristic reduction in inhibition of central motor circuits and alterations in the somatosensory system. The neurophysiologic measure with the greatest evidence in identifying patients affected by dystonia is the somatosensory temporal discrimination threshold (STDT). Other parameters need further confirmations and more solid evidence to be considered as support for the dystonia diagnosis. Genetic testing should be guided by characteristics such as age at onset, body distribution, associated features, and coexistence of other movement disorders (parkinsonism, myoclonus, and other hyperkinesia). The aim of the present review is to summarize the state of the art regarding dystonia diagnosis focusing on the role of neurophysiology and genetic testing.

Examining Neurosteroid-Analogue Therapy in the Preterm Neonate For Promoting Hippocampal Neurodevelopment

Background: Preterm birth can lead to brain injury and currently there are no targeted therapies to promote postnatal brain development and protect these vulnerable neonates. We have previously shown that the neurosteroid-analogue ganaxolone promotes white matter development and improves behavioural outcomes in male juvenile guinea pigs born preterm. Adverse side effects in this previous study necessitated this current follow-up dosing study, where a focus was placed upon physical wellbeing during the treatment administration and markers of neurodevelopment at the completion of the treatment period. Methods: Time-mated guinea pigs delivered preterm (d62) by induction of labour or spontaneously at term (d69). Preterm pups were randomized to receive no treatment (Prem-CON) or ganaxolone at one of three doses [0.5 mg/kg ganaxolone (low dose; LOW-GNX), 1.0 mg/kg ganaxolone (mid dose; MID-GNX), or 2.5 mg/kg ganaxolone (high dose; HIGH-GNX) in vehicle (45% β-cyclodextrin)] daily until term equivalence age. Physical parameters including weight gain, ponderal index, supplemental feeding, and wellbeing (a score based on respiration, activity, and posture) were recorded throughout the preterm period. At term equivalence, brain tissue was collected, and analysis of hippocampal neurodevelopment was undertaken by immunohistochemistry and RT-PCR. Results: Low and mid dose ganaxolone had some impacts on early weight gain, supplemental feeding, and wellbeing, whereas high dose ganaxolone significantly affected all physical parameters for multiple days during the postnatal period when compared to the preterm control neonates. Deficits in the preterm hippocampus were identified using neurodevelopmental markers including mRNA expression of oligodendrocyte lineage cells (CSPG4, MBP), neuronal growth (INA, VEGFA), and the GABAergic/glutamatergic system (SLC32A1, SLC1A2, GRIN1, GRIN2C, DLG4). These deficits were not affected by ganaxolone at the doses used at the equivalent of normal term. Conclusion: This is the first study to investigate the effects of a range of doses of ganaxolone to improve preterm brain development. We found that of the three doses, only the highest dose of ganaxolone (2.5 mg/kg) impaired key indicators of physical health and wellbeing over extended periods of time. Whilst it may be too early to see improvements in markers of neurodevelopment, further long-term study utilising the lower doses are warranted to assess functional outcomes at ages when preterm birth associated behavioural disorders are observed.