Levodopa and subthalamic deep brain stimulation responses are not congruent

Individual Structural Covariance Network Predicts Long-Term Motor Improvement in Parkinson Disease with Subthalamic Nucleus Deep Brain Stimulation

BACKGROUND AND PURPOSE

The efficacy of long-term chronic subthalamic nucleus deep brain stimulation (STN-DBS) in treating Parkinson disease (PD) exhibits substantial variability among individuals. The preoperative identification of suitable deep brain stimulation (DBS) candidates through predictive means becomes crucial. Our study aims to investigate the predictive value of characterizing individualized structural covariance networks for long-term efficacy of DBS, offering patients a precise and cost-effective preoperative screening tool.

MATERIALS AND METHODS

We included 138 patients with PD and 40 healthy controls. We developed individualized structural covariance networks from T1-weighted images utilizing network template perturbation, and computed the networks' topological characteristics. Patients were categorized according to their long-term motor improvement following STN-DBS. Intergroup analyses were conducted on individual network edges and topological indices, alongside correlation analyses with long-term outcomes for the entire patient cohort. Finally, machine learning algorithms were employed for regression and classification to predict post-DBS motor improvement.

RESULTS

Among the patients with PD, 6 edges (left middle frontal and left caudate nucleus, right olfactory and right insula, left superior medial frontal gyrus and right insula, right middle frontal and left paracentral lobule, right middle frontal and cerebellum, left lobule VIIb of the cerebellum and the vermis of the cerebellum) exhibited significant results in intergroup comparisons and correlation analyses. Increased degree centrality and local efficiency of the cerebellum, parahippocampal gyrus, and postcentral gyrus were associated with DBS improvement. A regression model constructed from these 6 edges revealed a significant correlation between predicted and observed changes in the unified PD rating scale (R = 0.671, P < .001) and receiver operating characteristic analysis demonstrated an area under the curve of 0.802, effectively distinguishing between patients with good and moderate improvement post-DBS.

CONCLUSIONS

Our findings reveal the link between individual structural covariance network fingerprints in patients with PD and long-term motor outcome following STN-DBS. Additionally, binary and continuous cerebellum-basal ganglia-frontal structural covariance network edges have emerged as potential predictive biomarkers for DBS motor outcome.

Subthalamic nucleus input-output dynamics are correlated with Parkinson's burden and treatment efficacy

The subthalamic nucleus (STN) is pivotal in basal ganglia function in health and disease. Micro-electrode recordings of >25,000 recording sites from 146 Parkinson's patients undergoing deep brain stimulation (DBS) allowed differentiation between subthalamic input, represented by local field potential (LFP), and output, reflected in spike discharge rate (SPK). As with many natural systems, STN neuronal activity exhibits power-law dynamics characterized by the exponent α. We, therefore, dissected STN data into aperiodic and periodic components using the Fitting Oscillations & One Over F (FOOOF) tool. STN LFP showed significantly higher aperiodic exponents than SPK. Additionally, SPK beta oscillations demonstrated a downward frequency shift compared to LFP. Finally, the STN aperiodic and spiking parameters explained a significant fraction of the variance of the burden and treatment efficacy of Parkinson's disease. The unique STN input-output dynamics may clarify its role in Parkinson's physiology and can be utilized in closed-loop DBS therapy.

The connection of motor improvement after deep brain stimulation in Parkinson's disease and microstructural integrity of the substantia nigra and subthalamic nucleus

BACKGROUND

Nigrostriatal microstructural integrity has been suggested as a biomarker for levodopa response in Parkinson's disease (PD), which is a strong predictor for motor response to deep brain stimulation (DBS) of the subthalamic nucleus (STN). This study aimed to explore the impact of microstructural integrity of the substantia nigra (SN), STN, and putamen on motor response to STN-DBS using diffusion microstructure imaging.

METHODS

Data was collected from 23 PD patients (mean age 63 ± 7, 6 females) who underwent STN-DBS, had preoperative 3 T diffusion magnetic resonance imaging including multishell diffusion-weighted MRI with b-values of 1000 and 2000 s/mm2 and records of motor improvement available.

RESULTS

The association between a poorer DBS-response and increased free interstitial fluid showed notable effect sizes (rho > |0.4|) in SN and STN, but not in putamen. However, this did not reach significance after Bonferroni correction and controlling for sex and age.

CONCLUSION

Microstructural integrity of SN and STN are potential biomarkers for the prediction of therapy efficacy following STN-DBS, but further studies are required to confirm these associations.

Parkinson's Disease Tremor Differentially Responds to Levodopa and Subthalamic Stimulation

Background

Tremor in Parkinson's disease (PD) has an inconsistent response to levodopa and subthalamic deep brain stimulation (STN-DBS).

Objectives

To identify predictive factors of PD tremor responsiveness to levodopa and STN-DBS.

Material and Methods

PD patients with upper limb tremor who underwent STN-DBS were included. The levodopa responsiveness of tremor (overall, postural, and rest sub-components), was assessed using the relevant Unified Parkinson's Disease Rating Scale-III items performed during the preoperative assessment. Post-surgical outcomes were similarly assessed ON and OFF stimulation. A score for the rest/postural tremor ratio was used to determine the influence of rest and postural tremor severity on STN-DBS outcome. Factors predictive of tremor responsiveness were determined using multiple linear regression modeling. Volume of tissue activated measurement coupled to voxel-based analysis was performed to identify anatomical clusters associated with motor symptoms improvement.

Results

One hundred and sixty five patients were included in this study. Male gender was negatively correlated with tremor responsiveness to levodopa, whereas the ratio of rest/postural tremor was positively correlated with both levodopa responsiveness and STN-DBS tremor outcome. Clusters corresponding to improvement of tremor were in the subthalamic nucleus, the zona incerta and the thalamus, whereas clusters corresponding to improvement for akinesia and rigidity were located within the subthalamic nucleus.

Conclusion

More severe postural tremor and less severe rest tremor were associated with both poorer levodopa and STN-DBS response. The different locations of clusters associated with best correction of tremor and other parkinsonian features suggest that STN-DBS effect on PD symptoms is underpinned by the modulation of different networks.

The Role of Levodopa Challenge in Predicting the Outcome of Subthalamic Deep Brain Stimulation

Background

Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective and evidence-based treatment for idiopathic Parkinson's disease (iPD). A minority of patients does not sufficiently benefit from STN-DBS.

Objective

The predictive validity of the levodopa challenge for individual patients is analyzed.

Methods

Data from patients assessed with a preoperative Levodopa-test and a follow-up examination (mean ± standard deviation: 9.15 months ±3.39) from Kiel (n = 253), Berlin (n = 78) and Toronto (n = 98) were studied. Insufficient DBS outcome was defined as an overall UPDRS-III reduction <33% compared to UPDRS-III in med-off at baseline or alternatively if the minimal clinically important improvement of 5 points was not reached. Single UPDRS-items and sub-scores were dichotomized. Following exploratory analysis, we trained supervised regression- and classification models for outcome prediction.

Results

Data analysis confirmed significant correlation between the absolute UPDRS-III reduction during Levodopa challenge and after stimulation. But individual improvement was inaccurately predicted with a large range of up to 30 UPDRS III points. Further analysis identified preoperative UPDRS-III/med-off-scores and preoperative Levodopa-improvement as most influential factors. The models for UPDRS-III and sub-scores improvement achieved comparably low accuracy.

Conclusions

With large prediction intervals, the Levodopa challenge use for patient counseling is limited, though remains important for excluding non-responders to Levodopa. Despite these deficiencies, the current practice of patient selection is highly successful and builds not only on the Levodopa challenge. However, more specific motor tasks and further paraclinical tools for prediction need to be developed.

Relationship Between Iron Distribution in Deep Gray Matter Nuclei Measured by Quantitative Susceptibility Mapping and Motor Outcome After Deep Brain Stimulation in Patients With Parkinson's Disease

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor deficits in advanced Parkinson's disease (PD) patients, but the degree of motor improvement varies across individuals. PD pathology involves the changes of iron spatial distribution in the deep gray matter nuclei.

PURPOSE

To explore the relationship between the iron spatial distribution and motor improvement among PD patients who underwent STN-DBS surgery in three regions: substantia nigra (SN), STN, and dentate nucleus (DN).

STUDY TYPE

Prospective.

SUBJECTS

Forty PD patients (49.7 ± 8.8 years, 22 males/18 females) who underwent bilateral STN-DBS.

FIELD STRENGTH/SEQUENCE

A 3 T preoperative three-dimensional spoiled bipolar-readout multi-echo gradient recalled echo and two-dimensional fast spin echo sequences.

ASSESSMENT

Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) scores were assessed 2-3 days before and 6 months after STN-DBS. The first- and second-order texture features in regions of interest were measured on susceptibility maps.

STATISTICAL TESTS

Intraclass correlation coefficient was used to determine the consistency of the region of interest volumes delineated by the two raters. Pearson or Spearman's correlation coefficients were used to assess the relationship between motor improvement after DBS and texture features. A P-value <0.05 was considered statistically significant.

RESULTS

MDS-UPDRS III scores were reduced by 59.9% after STN-DBS in 40 PD patients. Motor improvement correlated with second-order texture parameters in the SN including angular second moment (r = -0.449), correlation (rho = 0.326), sum of squares (r = 0.402), sum of entropy (rho = 0.421), and entropy (r = 0.410). Additionally, DBS outcome negatively correlated with mean susceptibility values in the DN (r = -0.400).

DATA CONCLUSION

PD patients with a more homogeneous iron distribution throughout the SN or a higher iron concentration in the DN responded worse to STN-DBS.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Levodopa Challenge Test Predicts STN-DBS Outcomes in Various Parkinson's Disease Motor Subtypes: A More Accurate Judgment

Background

The relationship between the levodopa challenge test (LDCT) and postoperative subthalamic nucleus-deep brain stimulation (STN-DBS) benefits is controversial in patients with Parkinson's disease (PD). We aim to evaluate the value of total levodopa response (TLR) and symptom levodopa response (SLR) in predicting postoperative improvement in different PD motor subtypes.

Methods

Studies were split into a training set (147 patients) and a validation set (304 patients). We retrospectively collected data from 147 patients who received the Unified Parkinson's Disease Rating Scale- (UPDRS-) III and the Parkinson's Disease Questionnaire- (PDQ-) 39 evaluation. Patients were classified into tremor-dominant (TD), akinetic-rigid-dominant (AR), and mixed (MX) groups. Clinically important difference (CID) was employed to dichotomize DBS effects. For patients in each subtype group from the training set, we used the correlation and receiver operator characteristic (ROC) curve analyses to explore the strength of their relations. Areas under the curve (AUCs) were calculated and compared through the DeLong test. Results developed from the training set were applied into the validation set to predict postoperative improvement in different PD motor subtypes.

Results

In the validation cohort, TLR significantly correlated with postoperative motor (p < 0.001) and quality of life (QOL) (p < 0.001) improvement in the MX group. The AUC between TLR and UPDRS-III (TU) is 0.800. The AUC between TLR and PDQ-39 (TP) is 0.770. An associated criterion in both TU and TP is around 50%. In the AR group, strong correlation was only found in SLR and PDQ-39 (SP) (p < 0.001). And the AUC of SP is significantly larger than that in TLR and PDQ-39 (TP) (p = 0.034). An associated criterion in SP is around 37%. No significant correlation was found in the TD group.

Conclusions

We provide a more accurate judgment for LDCT. TLR strongly correlated with postoperative UPDRS-III and PDQ-39 improvement in MX patients. A TLR > 50% may indicate a higher possibility of clinically meaningful benefits from STN-DBS comparing to medication only. SLR can well predict QOL improvement in AR patients. Similarly, a SLR > 37% may indicate a higher possibility of clinically significant benefits from STN-DBS. LDCT provides limited information for TD patients.

Predicting Motor Outcome of Subthalamic Nucleus Deep Brain Stimulation for Parkinson's Disease Using Quantitative Susceptibility Mapping and Radiomics: A Pilot Study

Background

Emerging evidence indicates that iron distribution is heterogeneous within the substantia nigra (SN) and it may reflect patient-specific trait of Parkinson’s Disease (PD). We assume it could account for variability in motor outcome of subthalamic nucleus deep brain stimulation (STN-DBS) in PD.

Objective

To investigate whether SN susceptibility features derived from radiomics with machine learning (RA-ML) can predict motor outcome of STN-DBS in PD.

Methods

Thirty-three PD patients underwent bilateral STN-DBS were recruited. The bilateral SN were segmented based on preoperative quantitative susceptibility mapping to extract susceptibility features using RA-ML. MDS-UPDRS III scores were recorded 1–3 days before and 6 months after STN-DBS surgery. Finally, we constructed three predictive models using logistic regression analyses: (1) the RA-ML model based on radiomics features, (2) the RA-ML+LCT (levodopa challenge test) response model which combined radiomics features with preoperative LCT response, (3) the LCT response model alone.

Results

For the predictive performances of global motor outcome, the RA-ML model had 82% accuracy (AUC = 0.85), while the RA-ML+LCT response model had 74% accuracy (AUC = 0.83), and the LCT response model alone had 58% accuracy (AUC = 0.55). For the predictive performance of rigidity outcome, the accuracy of the RA-ML model was 80% (AUC = 0.85), superior to those of the RA-ML+LCT response model (76% accuracy, AUC = 0.82), and the LCT response model alone (58% accuracy, AUC = 0.42).

Conclusion

Our findings demonstrated that SN susceptibility features from radiomics could predict global motor and rigidity outcomes of STN-DBS in PD. This RA-ML predictive model might provide a novel approach to counsel candidates for STN-DBS.

Balance response to levodopa predicts balance improvement after bilateral subthalamic nucleus deep brain stimulation in Parkinson's disease

The effect of subthalamic nucleus deep brain stimulation (STN-DBS) on balance function in patients with Parkinson’s disease (PD) and the potential outcome predictive factors remains unclear. We retrospectively included 261 PD patients who underwent STN-DBS and finished the 1-month follow-up (M1) assessment in the explorative set for identifying postoperative balance change predictors, and 111 patients who finished both the M1 and 12-month follow-up (M12) assessment in the validation set for verifying the identified factors. Motor and balance improvement were evaluated through the UPDRS-III and the Berg balance scale (BBS) and pull test (PT), respectively. Candidate predictors of balance improvement included age, disease duration, motor subtypes, baseline severity of PD, cognitive status, motor and balance response to levodopa, and stimulation parameters. In the off-medication condition, STN-DBS significantly improved BBS and PT performance in both the M1 and M12, in both datasets. While in the on-medication condition, no significant balance improvement was observed. Higher preoperative BBS response to levodopa was significantly associated with larger postoperative off-medication, but not on-medication, BBS (p < 0.001) and PT (p < 0.001) improvement in both the M1 and M12. BBS subitems 8, 9, 11, 13, and 14 were the major contributors to the prediction of balance improvement after STN-DBS. STN-DBS improves short-term off-medication, but not on-medication, balance function assessed through BBS and PT. Preoperative BBS response to levodopa best predicts postoperative off-medication balance improvement. For patients who manifested severe balance problems, a levodopa challenge test on BBS or the short version of BBS is recommended.

Revisiting the L-Dopa Response as a Predictor of Motor Outcomes After Deep Brain Stimulation in Parkinson's Disease

Objective: To investigate the correlation between preoperative response to the L-dopa challenge test and efficacy of deep brain stimulation (DBS) on motor function in Parkinson's disease (PD). Methods: We retrospectively reviewed the data of 38 patients with idiopathic PD who underwent DBS surgery with a median follow-up duration of 7 months. Twenty underwent bilateral globus pallidus interna (GPi) DBS, and 18 underwent bilateral subthalamic nucleus (STN) DBS. The Movement Disorder Society Unified Parkinson Disease Rating Scale-Motor Part (MDS UPDRS-III) was assessed before surgery and at the last follow-up in different medication and stimulation conditions, respectively. Results: Pearson's correlation analysis revealed a positive correlation between preoperative L-dopa challenge responsiveness and GPi-DBS responsiveness on the total score (R 2 = 0.283, p = 0.016) but not on the non-tremor total score (R 2 = 0.158, p = 0.083) of MDS UPDRS-III. Such correlation remained significant (R 2' = 0.332, p = 0.010) after controlling for age at the time of surgery as confounding factor by partial correlation analysis. The preoperative L-dopa challenge responsiveness was significantly correlated with the tremor-controlling outcome of GPi-DBS (R 2 = 0.390, p = 0.003). In contrast, we found a positive correlation between preoperative L-dopa challenge responsiveness and STN-DBS responsiveness on the non-tremor total score (R 2 = 0.290, p = 0.021), but not on the total score (R 2 = 0.130, p = 0.141) of MDS UPDRS-III. The partial correlation analysis further demonstrated that the predictive value of preoperative L-dopa challenge responsiveness on the non-tremor motor outcome of STN-DBS was eliminated (R 2' = 0.120, p = 0.174) after controlling for age at the time of surgery as confounding factor. Interpretation: The short-term predictive value of preoperative response to the L-dopa challenge test for the motor outcome of GPi-DBS in PD was systematically described. Our findings suggest: (1) a solid therapeutic effect of GPi-DBS in treating L-dopa-responsive tremors; (2) a negative effect of age at the time of surgery on motor outcomes of STN-DBS, (3) a possible preference of STN- to GPi-DBS in L-dopa-resistant tremor control, and (4) a possible preference of GPi- to STN-DBS in elderly PD patients who have a satisfactory dopamine response.

The rostro-caudal gradient in the prefrontal cortex and its modulation by subthalamic deep brain stimulation in Parkinson's disease

Deep brain stimulation of the subthalamic nucleus (STN-DBS) alleviates motor symptoms in Parkinson’s disease (PD) but also affects the prefrontal cortex (PFC), potentially leading to cognitive side effects. The present study tested alterations within the rostro-caudal hierarchy of neural processing in the PFC induced by STN-DBS in PD. Granger-causality analyses of fast functional near-infrared spectroscopy (fNIRS) measurements were used to infer directed functional connectivity from intrinsic PFC activity in 24 PD patients treated with STN-DBS. Functional connectivity was assessed ON stimulation, in steady-state OFF stimulation and immediately after the stimulator was switched ON again. Results revealed that STN-DBS significantly enhanced the rostro-caudal hierarchical organization of the PFC in patients who had undergone implantation early in the course of the disease, whereas it attenuated the rostro-caudal hierarchy in late-implanted patients. Most crucially, this systematic network effect of STN-DBS was reproducible in the second ON stimulation measurement. Supplemental analyses demonstrated the significance of prefrontal networks for cognitive functions in patients and matched healthy controls. These findings show that the modulation of prefrontal functional networks by STN-DBS is dependent on the disease duration before DBS implantation and suggest a neurophysiological mechanism underlying the side effects on prefrontally-guided cognitive functions observed under STN-DBS.

Pallidal stimulation as treatment for camptocormia in Parkinson's disease

Camptocormia is a common and often debilitating postural deformity in Parkinson’s disease (PD). Few treatments are currently effective. Deep brain stimulation (DBS) of the globus pallidus internus (GPi) shows potential in treating camptocormia, but evidence remains limited to case reports. We herein investigate the effect of GPi-DBS for treating camptocormia in a retrospective PD cohort. Thirty-six consecutive PD patients who underwent GPi-DBS were reviewed. The total and upper camptocormia angles (TCC and UCC angles) derived from video recordings of patients who received GPi-DBS were used to compare camptocormia alterations. Correlation analysis was performed to identify factors associated with the postoperative improvements. DBS lead placement and the impact of stimulation were analyzed using Lead-DBS software. Eleven patients manifested pre-surgical camptocormia: seven had lower camptocormia (TCC angles ≥ 30°; TCC-camptocormia), three had upper camptocormia (UCC angles ≥ 45°; UCC-camptocormia), and one had both. Mean follow-up time was 7.3 ± 3.3 months. GPi-DBS improved TCC-camptocormia by 40.4% (angles from 39.1° ± 10.1° to 23.3° ± 8.1°, p = 0.017) and UCC-camptocormia by 22.8% (angles from 50.5° ± 2.6° to 39.0° ± 6.7°, p = 0.012). Improvement in TCC angle was positively associated with pre-surgical TCC angles, levodopa responsiveness of the TCC angle, and structural connectivity from volume of tissue activated to somatosensory cortex. Greater improvement in UCC angles was seen in patients with larger pre-surgical UCC angles. Our study demonstrates potential effectiveness of GPi-DBS for treating camptocormia in PD patients. Future controlled studies with larger numbers of patients with PD-related camptocormia should extend our findings.

Machine learning prediction of motor response after deep brain stimulation in Parkinson's disease-proof of principle in a retrospective cohort

INTRODUCTION

Despite careful patient selection for subthalamic nucleus deep brain stimulation (STN DBS), some Parkinson's disease patients show limited improvement of motor disability. Innovative predictive analysing methods hold potential to develop a tool for clinicians that reliably predicts individual postoperative motor response, by only regarding clinical preoperative variables. The main aim of preoperative prediction would be to improve preoperative patient counselling, expectation management, and postoperative patient satisfaction.

METHODS

We developed a machine learning logistic regression prediction model which generates probabilities for experiencing weak motor response one year after surgery. The model analyses preoperative variables and is trained on 89 patients using a five-fold cross-validation. Imaging and neurophysiology data are left out intentionally to ensure usability in the preoperative clinical practice. Weak responders (n = 30) were defined as patients who fail to show clinically relevant improvement on Unified Parkinson Disease Rating Scale II, III or IV.

RESULTS

The model predicts weak responders with an average area under the curve of the receiver operating characteristic of 0.79 (standard deviation: 0.08), a true positive rate of 0.80 and a false positive rate of 0.24, and a diagnostic accuracy of 78%. The reported influences of individual preoperative variables are useful for clinical interpretation of the model, but cannot been interpreted separately regardless of the other variables in the model.

CONCLUSION

The model's diagnostic accuracy confirms the utility of machine learning based motor response prediction based on clinical preoperative variables. After reproduction and validation in a larger and prospective cohort, this prediction model holds potential to support clinicians during preoperative patient counseling.

Microelectrode Recordings Validate the Clinical Visualization of Subthalamic-Nucleus Based on 7T Magnetic Resonance Imaging and Machine Learning for Deep Brain Stimulation Surgery

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a proven and effective therapy for the management of the motor symptoms of Parkinson's disease (PD). While accurate positioning of the stimulating electrode is critical for success of this therapy, precise identification of the STN based on imaging can be challenging. We developed a method to accurately visualize the STN on a standard clinical magnetic resonance imaging (MRI). The method incorporates a database of 7-Tesla (T) MRIs of PD patients together with machine-learning methods (hereafter 7 T-ML).

OBJECTIVE

To validate the clinical application accuracy of the 7 T-ML method by comparing it with identification of the STN based on intraoperative microelectrode recordings.

METHODS

Sixteen PD patients who underwent microelectrode-recordings guided STN DBS were included in this study (30 implanted leads and electrode trajectories). The length of the STN along the electrode trajectory and the position of its contacts to dorsal, inside, or ventral to the STN were compared using microelectrode-recordings and the 7 T-ML method computed based on the patient's clinical 3T MRI.

RESULTS

All 30 electrode trajectories that intersected the STN based on microelectrode-recordings, also intersected it when visualized with the 7 T-ML method. STN trajectory average length was 6.2 ± 0.7 mm based on microelectrode recordings and 5.8 ± 0.9 mm for the 7 T-ML method. We observed a 93% agreement regarding contact location between the microelectrode-recordings and the 7 T-ML method.

CONCLUSION

The 7 T-ML method is highly consistent with microelectrode-recordings data. This method provides a reliable and accurate patient-specific prediction for targeting the STN.

Understanding Parkinson's disease and deep brain stimulation: Role of monkey models

Parkinson's disease (PD) is a progressive neurodegenerative movement disorder affecting over 10 million people worldwide. In the 1930s and 1940s there was little understanding regarding what caused PD or how to treat it. In a desperate attempt to improve patients' lives different regions of the neuraxis were ablated. Morbidity and mortality were common, but some patients' motor signs improved with lesions involving the basal ganglia or thalamus. With the discovery of l-dopa the advent of medical therapy began and surgical approaches became less frequent. It soon became apparent, however, that medical therapy was associated with side effects in the form of drug-induced dyskinesia and motor fluctuations and surgical therapies reemerged. Fortunately, during this time studies in monkeys had begun to lay the groundwork to understand the functional organization of the basal ganglia, and with the discovery of the neurotoxin MPTP a monkey model of PD had been developed. Using this model scientists were characterizing the physiological changes that occurred in the basal ganglia in PD and models of basal ganglia function and dysfunction were proposed. This work provided the rationale for the return of pallidotomy, and subsequently deep brain stimulation procedures. In this paper we describe the evolution of these monkey studies, how they provided a greater understanding of the pathophysiology underlying the development of PD and provided the rationale for surgical procedures, the search to understand mechanisms of DBS, and how these studies have been instrumental in understanding PD and advancing the development of surgical therapies for its treatment.

Connectivity Predicts deep brain stimulation outcome in Parkinson disease

OBJECTIVE

The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort.

METHODS

A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center.

RESULTS

In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p < 0.001). This same connectivity profile predicted response in an independent patient cohort (p < 0.01). Structural and functional connectivity were independent predictors of clinical improvement (p < 0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients.

INTERPRETATION

Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. Ann Neurol 2017;82:67-78.

Subthalamic deep brain stimulation sweet spots and hyperdirect cortical connectivity in Parkinson's disease

OBJECTIVES

Firstly, to identify subthalamic region stimulation clusters that predict maximum improvement in rigidity, bradykinesia and tremor, or emergence of side-effects; and secondly, to map-out the cortical fingerprint, mediated by the hyperdirect pathways which predict maximum efficacy.

METHODS

High angular resolution diffusion imaging in twenty patients with advanced Parkinson's disease was acquired prior to bilateral subthalamic nucleus deep brain stimulation. All contacts were screened one-year from surgery for efficacy and side-effects at different amplitudes. Voxel-based statistical analysis of volumes of tissue activated models was used to identify significant treatment clusters. Probabilistic tractography was employed to identify cortical connectivity patterns associated with treatment efficacy.

RESULTS

All patients responded well to treatment (46% mean improvement off medication UPDRS-III [p < 0.0001]) without significant adverse events. Cluster corresponding to maximum improvement in tremor was in the posterior, superior and lateral portion of the nucleus. Clusters corresponding to improvement in bradykinesia and rigidity were nearer the superior border in a further medial and posterior location. The rigidity cluster extended beyond the superior border to the area of the zona incerta and Forel-H₂ field. When the clusters where averaged, the coordinates of the area with maximum overall efficacy was X = -10(-9.5), Y = -13(-1) and Z = -7(-3) in MNI(AC-PC) space. Cortical connectivity to primary motor area was predictive of higher improvement in tremor; whilst that to supplementary motor area was predictive of improvement in bradykinesia and rigidity; and connectivity to prefrontal cortex was predictive of improvement in rigidity.

INTERPRETATION

These findings support the presence of overlapping stimulation sites within the subthalamic nucleus and its superior border, with different cortical connectivity patterns, associated with maximum improvement in tremor, rigidity and bradykinesia.

Subthalamic nucleus deep brain stimulation on motor-symptoms of Parkinson's disease: Focus on neurochemistry

Deep brain stimulation (DBS) has become a standard therapy for Parkinson's disease (PD) and it is also currently under investigation for other neurological and psychiatric disorders. Although many scientific, clinical and ethical issues are still unresolved, DBS delivered into the subthalamic nucleus (STN) has improved the quality of life of several thousands of patients. The mechanisms underlying STN-DBS have been debated extensively in several reviews; less investigated are the biochemical consequences, which are still under scrutiny. Crucial and only partially understood, for instance, are the complex interplays occurring between STN-DBS and levodopa (LD)-centred therapy in the post-surgery follow-up. The main goal of this review is to address the question of whether an improved motor control, based on STN-DBS therapy, is also achieved through the additional modulation of other neurotransmitters, such as noradrenaline (NA) and serotonin (5-HT). A critical issue is to understand not only acute DBS-mediated effects, but also chronic changes, such as those involving cyclic nucleotides, capable of modulating circuit plasticity. The present article will discuss the neurochemical changes promoted by STN-DBS and will document the main results obtained in microdialysis studies. Furthermore, we will also examine the preliminary achievements of voltammetry applied to humans, and discuss new hypothetical investigational routes, taking into account novel players such as glia, or subcortical regions such as the pedunculopontine (PPN) area. Our further understanding of specific changes in brain chemistry promoted by STN-DBS would further disseminate its utilisation, at any stage of disease, avoiding an irreversible lesioning approach.

Deep brain stimulation for Parkinson's disease: current status and future outlook

Parkinson's disease is a neurodegenerative condition secondary to loss of dopaminergic neurons in the substantia nigra pars compacta. Surgical therapy serves as an adjunct when unwanted medication side effects become apparent or additional therapy is needed. Deep brain stimulation emerged into the forefront in the 1990s. Studies have demonstrated improvement in all of the cardinal parkinsonian signs with stimulation. Frameless and ‘mini-frame’ stereotactic systems, improved MRI for anatomic visualization, and intraoperative MRI-guided placement are a few of the surgical advances in deep brain stimulation. Other advances include rechargeable pulse generators, voltage- or current-based stimulation, and enhanced abilities to ‘steer’ stimulation. Work is ongoing investigating closed-loop ‘smart’ stimulation in which stimulation is predicated on neuronal feedback.

Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization.

OBJECTIVE

Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication.

METHODS

Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions: (1) information retrieval; (2) visualization of treatment, and; (3) recommendation on expected effective stimulation and drug dosages, based on three machine learning methods that included support vector machines, Naïve Bayes, and random forest.

RESULTS

Measures of medication dosages, time factors, and symptom-specific pre-operative response to levodopa were significantly correlated with post-operative outcomes (P < 0.05) and their effect on outcomes was of similar magnitude to that of DBS. Using those results, the combined machine learning algorithms were able to accurately predict 86% (12/14) of the motor improvement scores at one year after surgery.

CONCLUSIONS

Using patient-specific details, an appropriately parameterized CDSS could help select theoretically optimal DBS parameter settings and medication dosages that have potential to improve the clinical management of PD patients.

Dopaminergic therapy in Parkinson's disease decreases cortical beta band coherence in the resting state and increases cortical beta band power during executive control

It is not yet well understood how dopaminergic therapy improves cognitive and motor function in Parkinson's disease (PD). One possibility is that it reduces the pathological synchronization within and between the cortex and basal ganglia, thus improving neural communication. We tested this hypothesis by recording scalp electroencephalography (EEG) in PD patients when On and Off medication, during a brief resting state epoch (no task), and during performance of a stop signal task that is thought to engage two partially overlapping (or different) frontal-basal-ganglia circuits. For resting state EEG, we measured pair-wise coherence between scalp electrodes in several frequency bands. Consistent with previous studies, in the Off medication state, those patients with the greatest clinical impairment had the strongest coherence, especially in the beta band, indicating pathological over-synchronization. Dopaminergic medication reduced this coherence. For the stop signal task, On vs. Off medication increased beta band power over right frontal cortex for successful stopping and over bilateral sensorimotor cortex for going, especially for those patients who showed greater clinical improvement. Thus, medication reduced pathological coherence in beta band at rest and increased task related beta power for two potentially dissociable cortico-basal ganglia circuits. These results support the hypothesis that dopaminergic medication in PD improves neural communication both at rest and for executive and motor function.

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EEG measured in PD while On/Off medication during rest and an executive control task.

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Dopaminergic therapy reduces pathological locking jointly with clinical improvement.

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Medication increases beta power during successful stopping over right frontal cortex.

Reaching to proprioceptively defined targets in Parkinson's disease: effects of deep brain stimulation therapy

Deep brain stimulation of the subthalamic nucleus (STN DBS) provides a unique window into human brain function since it can reversibly alter the functioning of specific brain circuits. Basal ganglia-cortical circuits are thought to be excessively noisy in patients with Parkinson's disease (PD), based in part on the lack of specificity of proprioceptive signals in basal ganglia-thalamic-cortical circuits in monkey models of the disease. PD patients are known to have deficits in proprioception, but the effects are often subtle, with paradigms typically restricted to one or two joint movements in a plane. Moreover, the effects of STN DBS on proprioception are virtually unexplored. We tested the following hypotheses: first, that PD patients will show substantial deficits in unconstrained, multi-joint proprioception, and, second, that STN DBS will improve multi-joint proprioception. Twelve PD patients with bilaterally implanted electrodes in the subthalamic nucleus and 12 age-matched healthy subjects were asked to position the left hand at a location that was proprioceptively defined in 3D space with the right hand. In a second condition, subjects were provided visual feedback during the task so that they were not forced to rely on proprioception. Overall, with STN DBS switched off, PD patients showed significantly larger proprioceptive localization errors, and greater variability in endpoint localizations than the control subjects. Visual feedback partially normalized PD performance, and demonstrated that the errors in proprioceptive localization were not simply due to a difficulty in executing the movements or in remembering target locations. Switching STN DBS on significantly reduced localization errors from those of control subjects when patients moved without visual feedback relative to when they moved with visual feedback (when proprioception was not required). However, this reduction in localization errors without vision came at the cost of increased localization variability.

Deep brain stimulation for Parkinson's disease - patient selection

Proper selection of patients who will reliably benefit from deep brain stimulation (DBS) is critical to its success. This requires careful evaluation that should be delivered by an expert multidisciplinary team involving a movement disorder neurologist, a neurosurgeon, a neuropsychologist, and a psychiatrist. The most suitable candidates for DBS suffer from Parkinson's disease with motor fluctuations and/or dyskinesias that are not adequately controlled with optimized medical therapy, or with medication-refractory tremor. During the best on-motor periods, gait difficulties, instability, and speech problems should be minimal, reflecting an excellent response to levodopa in the ideal candidate. The cognitive, psychiatric, and behavioral status must be normal or minimally affected, with the exception of dopamine agonist drug-induced impulse control disorders, which are usually improved after successful surgery and drug withdrawal. Moreover, the patients have no serious comorbidities. Most patients corresponding to this profile suffer from a relatively young onset of Parkinson's disease, and are aged less than 70 years at the time of surgery. Indeed, most patients fall outside this ideal description, and the medical art is to appreciate for each patient the extent to which the alterations of these features can be accepted. Eventually, patients make their own decision from detailed information of their individualized risks and benefits of DBS. Patient expectations, cooperation, and familial support are also important considerations.

Deep brain stimulation induces rapidly reversible transcript changes in Parkinson's leucocytes

Subthalamic deep brain stimulation (DBS) reversibly modulates Parkinson's disease (PD) motor symptoms, providing an unusual opportunity to compare leucocyte transcripts in the same individuals before and after neurosurgery and 1 hr after stimulus cessation (ON- and OFF-stimulus). Here, we report DBS-induced reversibility and OFF-stimulus restoration in 12 of 16 molecular functions and 3 of 4 biological processes shown in exon microarrays to be differentially expressed between PD patients and controls, post-DBS from pre-DBS and OFF from ON states. Intriguingly, 6 of 18 inflammation and immune-related functions exhibited reversibility, and the extent of stimulus-induced changes correlated with the neurological DBS efficacy, suggesting mechanistic implications. A minimal list of 29 transcripts that changed in all three comparisons between states discriminated pre-surgery and OFF states from post-surgery and controls. Six of these transcripts were found to be able to distinguish between PD patients and both healthy controls and patients with other neurological diseases in a previously published whole blood 3’ array data study of early PD patients. Our findings support the future use of this approach for identifying targets for therapeutic intervention and assessing the efficacy of current and new treatments in this and other neurological diseases.

Whole-brain mapping of direct inputs to midbrain dopamine neurons

Recent studies indicate that dopamine neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) convey distinct signals. To explore this difference, we comprehensively identified each area's monosynaptic inputs using the rabies virus. We show that dopamine neurons in both areas integrate inputs from a more diverse collection of areas than previously thought, including autonomic, motor, and somatosensory areas. SNc and VTA dopamine neurons receive contrasting excitatory inputs: the former from the somatosensory/motor cortex and subthalamic nucleus, which may explain their short-latency responses to salient events; and the latter from the lateral hypothalamus, which may explain their involvement in value coding. We demonstrate that neurons in the striatum that project directly to dopamine neurons form patches in both the dorsal and ventral striatum, whereas those projecting to GABAergic neurons are distributed in the matrix compartment. Neuron-type-specific connectivity lays a foundation for studying how dopamine neurons compute outputs.

Preservation of function in Parkinson's disease: what's learning got to do with it?

Dopamine denervation gives rise to abnormal corticostriatal plasticity; however, its role in the symptoms and progression of Parkinson's disease (PD) has not been articulated or incorporated into current clinical models. The 'integrative selective gain' framework proposed here integrates dopaminergic mechanisms known to modulate basal ganglia throughput into a single conceptual framework: (1) synaptic weights, the neural instantiation of accumulated experience and skill modulated by dopamine-dependent plasticity and (2) system gain, the operating parameters of the basal ganglia, modulated by dopamine's on-line effects on cell excitability, glutamatergic transmission and the balance between facilitatory and inhibitory pathways. Within this framework and based on recent work, a hypothesis is presented that prior synaptic weights and established skills can facilitate motor performance and preserve function despite diminished dopamine; however, dopamine denervation induces aberrant corticostriatal plasticity that degrades established synaptic weights and replaces them with inappropriate, inhibitory learning that inverts the function of the basal ganglia resulting in 'anti-optimization' of motor performance. Consequently, mitigating aberrant corticostriatal plasticity represents an important therapeutic objective, as reflected in the long-duration response to levodopa, reinterpreted here as the correction of aberrant learning. It is proposed that viewing aberrant corticostriatal plasticity and learning as a provisional endophenotype of PD would facilitate investigation of this hypothesis.