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Personalized Real-Time DBS and PD Mechanisms

Primary Purpose

Parkinson Disease

Status
Recruiting
Phase
Phase 4
Locations
United States
Study Type
Interventional
Intervention
Neurostimulation
Carbidopa 25/Levodopa 100Mg Tab
Sponsored by
David Escobar
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional basic science trial for Parkinson Disease focused on measuring Deep Brain Stimulation

Eligibility Criteria

40 Years - 80 Years (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Key Inclusion Criteria: Ability to provide informed consent. Clinical diagnosis of idiopathic Parkinson's disease. Determined, as per standard of care, to be a candidate for deep brain stimulation (DBS) surgery targeting either the subthalamic nucleus or the internal segment of the globus pallidus. Ability to tolerate delays in taking daily standard Parkinson's disease medications. Key Exclusion Criteria: - Secondary Parkinsonism, stroke, or progressive central nervous system disease other than Parkinson's disease.

Sites / Locations

  • Cleveland ClinicRecruiting

Arms of the Study

Arm 1

Arm 2

Arm 3

Arm 4

Arm Type

Experimental

No Intervention

Experimental

Experimental

Arm Label

eiDBS suppression

Off DBS

eiDBS amplification

Levodopa medication

Arm Description

Closed-loop evoked interference DBS that suppresses beta oscillations.

Off-stimulation and off-medication

Closed-loop evoked interference DBS that amplifies beta oscillations.

On-medication, off-stimulation

Outcomes

Primary Outcome Measures

Effect of eiDBS suppression vs. off-stimulation on finger tapping speed
The finger tapping speed will be measured with an inertial measuring unit. The relationship (slope/effect) between this kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models. The LME models will include the stimulation conditions in this study (e.g., eiDBS-suppression) as fixed effects with the off-stimulation condition as a reference/control group, and random intercepts as random effects that account for the heterogeneity between subjects.
Effect of eiDBS amplification vs. off-stimulation on finger tapping speed
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS suppression vs. off-stimulation on forearm speed
The forearm speed will be measured with an inertial measuring unit. The relationship (slope/effect) between this kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS amplification vs. off-stimulation on forearm speed
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS suppression vs. off-stimulation on UPDRS-III rigidity subscore
The relationship (slope/effect) between this UPDRS-III rigidity subscore (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS amplification vs. off-stimulation on UPDRS-III rigidity subscore
The relationship (slope/effect) between this UPDRS-III rigidity subscore (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Correlation between levodopa-related changes in finger tapping speed and the amplitude of stimulation-evoked beta oscillations
The amplitude of beta oscillations evoked by stimulation will be characterized using the wavelet transform. The relationship (slope) between the kinematic measurements (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Correlation between levodopa-related changes in forearm speed and the amplitude of stimulation-evoked beta oscillations
The relationship (slope) between the kinematic measurements (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Correlation between levodopa-related changes in UPDRS-III rigidity subscore and the amplitude of stimulation-evoked beta oscillations.
The relationship (slope) between the UPDRS-III subscores (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.

Secondary Outcome Measures

Effect of eiDBS suppression vs. off-stimulation on finger tapping displacement
The finger tapping displacement will be derived based on data from an inertial measuring unit via a Kalman filter. The relationship (slope/effect) between this kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS amplification vs. off-stimulation on finger tapping displacement
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS suppression vs. off-stimulation on forearm displacement
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS amplification vs. off-stimulation on forearm displacement
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS suppression vs. off-stimulation on UPDRS-III bradykinesia subscore
The relationship (slope/effect) between this UPDRS-III subscore (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Effect of eiDBS amplification vs. off-stimulation on UPDRS-III bradykinesia subscore
The relationship (slope/effect) between this UPDRS-III subscore (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Correlation between levodopa-related changes in finger tapping displacement and the amplitude of stimulation-evoked beta oscillations
The relationship (slope) between the kinematic measurements (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Correlation between levodopa-related changes in forearm displacement and the amplitude of stimulation-evoked beta oscillations
The relationship (slope) between the kinematic measurements (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Correlation between levodopa-related changes in UPDRS-III bradykinesia subscore and the amplitude of stimulation-evoked beta oscillations
The relationship (slope) between the UPDRS-III subscores (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.

Full Information

First Posted
August 22, 2023
Last Updated
August 25, 2023
Sponsor
David Escobar
Collaborators
The Cleveland Clinic
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1. Study Identification

Unique Protocol Identification Number
NCT06013956
Brief Title
Personalized Real-Time DBS and PD Mechanisms
Official Title
Identifying Circuit Dynamics Underlying Motor Dysfunction in Parkinson's Disease Using Real-Time Neural Control
Study Type
Interventional

2. Study Status

Record Verification Date
August 2023
Overall Recruitment Status
Recruiting
Study Start Date
September 15, 2023 (Anticipated)
Primary Completion Date
June 30, 2028 (Anticipated)
Study Completion Date
June 30, 2028 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor-Investigator
Name of the Sponsor
David Escobar
Collaborators
The Cleveland Clinic

4. Oversight

Studies a U.S. FDA-regulated Drug Product
Yes
Studies a U.S. FDA-regulated Device Product
Yes
Device Product Not Approved or Cleared by U.S. FDA
Yes
Product Manufactured in and Exported from the U.S.
No
Data Monitoring Committee
No

5. Study Description

Brief Summary
A prospective cohort of patients scheduled to undergo deep brain stimulation (DBS) implantation surgery for the treatment of Parkinson's disease as per standard of care will be invited to participate in this study. This mechanistic study is aimed at better understanding the role of basal ganglia beta band (11-35 Hz) oscillations and resonance in the manifestation of Parkinson's disease (PD) motor signs using closed-loop electrical neurostimulation, levodopa medication, and computational modeling. The ultimate goal of this study is to inform the development of closed-loop neuromodulation technology that can be programmed and adjusted in real time based on patient-specific neural activity.
Detailed Description
While much research has been dedicated to understanding the pathophysiology of Parkinson's disease (PD), the neural dynamics underlying the manifestation of motor signs remain unclear. Studies over the past two decades have shown a correlation of the amplitude and incidence of beta band oscillations in the subthalamic nucleus (STN) and internal segment of the globus pallidus (GPi) with changes in bradykinesia and rigidity mediated by levodopa or deep brain stimulation (DBS) therapies. Yet, no study has conclusively or deductively demonstrated a causal link. A limitation to establishing causality is the lack of available neuromodulation tools capable of predictably and precisely controlling neural oscillatory activity in the human brain in real time without introducing confounding factors. Establishing these tools and clarifying whether the relationship of beta band oscillations with PD motor signs is causal or epiphenomenon are critical steps to better understand PD pathophysiology and advance personalized DBS technology in PD and other brain conditions. This study aims to address these technology and knowledge gaps by leveraging feedback control engineering and patient-specific computational modeling tools. In this study, the investigators will employ a neural control approach, referred to as evoked interference closed-loop DBS (eiDBS), to characterize the degree by which controlled suppression or amplification of beta oscillations in the STN and GPi influences bradykinesia and rigidity in PD (Specific Aim 1, SA1). The investigators will test the hypothesis that stimulation-induced suppression or amplification of beta oscillations in the STN or GPi will result in changes in bradykinesia and rigidity measures. In SA2, the investigators will employ levodopa medication to characterize how changes in bradykinesia and rigidity relate to variations in the amplitude of neural oscillations in the STN, GPi, and primary motor cortex (MC) evoked by STN and GPi stimulation. The investigators will test the hypothesis that levodopa administration will result in a decrease in the amplitude of stimulation-evoked beta oscillations that will correlate with changes in bradykinesia and rigidity. The results from SA2 will help to gain a greater understanding of intrinsic circuit dynamics associated with PD and identify strategies to optimize closed-loop DBS algorithms (e.g., eiDBS) in the face of concurrent levodopa therapy, a step to bring this technology to future clinical trials. Combining electrophysiological data with high-resolution (7T) magnetic resonance (MR) imaging and computational modeling, the investigators will examine which specific neuronal pathways connected with the STN and GPi need to be activated to evoke frequency-specific neural responses in the STN, GPi, and MC (SA3). The data from SA3 will shed light on which sub-circuits are involved in the generation of stimulation-evoked and spontaneous beta oscillations in PD, and inform how to use directional DBS leads to shape electric fields in the STN and GPi to selectively modulate the STN or GPi via eiDBS or other neurostimulation techniques. The investigators will address the three aims of this study with the participation of PD patients implanted with DBS leads in the STN or GPi, whose DBS lead extensions will be externalized and connected to our recording and closed-loop stimulation infrastructure.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Parkinson Disease
Keywords
Deep Brain Stimulation

7. Study Design

Primary Purpose
Basic Science
Study Phase
Phase 4
Interventional Study Model
Crossover Assignment
Model Description
Each participant is assigned to four different conditions. Kinematic, behavioral, and neurophysiological variables are compared across the conditions.
Masking
ParticipantCare ProviderOutcomes Assessor
Masking Description
The sequence order for the conditions will be randomized for each study participant.
Allocation
Randomized
Enrollment
30 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
eiDBS suppression
Arm Type
Experimental
Arm Description
Closed-loop evoked interference DBS that suppresses beta oscillations.
Arm Title
Off DBS
Arm Type
No Intervention
Arm Description
Off-stimulation and off-medication
Arm Title
eiDBS amplification
Arm Type
Experimental
Arm Description
Closed-loop evoked interference DBS that amplifies beta oscillations.
Arm Title
Levodopa medication
Arm Type
Experimental
Arm Description
On-medication, off-stimulation
Intervention Type
Device
Intervention Name(s)
Neurostimulation
Intervention Description
Electrical stimulation delivered via deep brain stimulation electrodes based on measurements of brain activity.
Intervention Type
Drug
Intervention Name(s)
Carbidopa 25/Levodopa 100Mg Tab
Intervention Description
Anti-parkinsonian medication.
Primary Outcome Measure Information:
Title
Effect of eiDBS suppression vs. off-stimulation on finger tapping speed
Description
The finger tapping speed will be measured with an inertial measuring unit. The relationship (slope/effect) between this kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models. The LME models will include the stimulation conditions in this study (e.g., eiDBS-suppression) as fixed effects with the off-stimulation condition as a reference/control group, and random intercepts as random effects that account for the heterogeneity between subjects.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS amplification vs. off-stimulation on finger tapping speed
Description
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS suppression vs. off-stimulation on forearm speed
Description
The forearm speed will be measured with an inertial measuring unit. The relationship (slope/effect) between this kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS amplification vs. off-stimulation on forearm speed
Description
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS suppression vs. off-stimulation on UPDRS-III rigidity subscore
Description
The relationship (slope/effect) between this UPDRS-III rigidity subscore (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS amplification vs. off-stimulation on UPDRS-III rigidity subscore
Description
The relationship (slope/effect) between this UPDRS-III rigidity subscore (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Correlation between levodopa-related changes in finger tapping speed and the amplitude of stimulation-evoked beta oscillations
Description
The amplitude of beta oscillations evoked by stimulation will be characterized using the wavelet transform. The relationship (slope) between the kinematic measurements (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Correlation between levodopa-related changes in forearm speed and the amplitude of stimulation-evoked beta oscillations
Description
The relationship (slope) between the kinematic measurements (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Correlation between levodopa-related changes in UPDRS-III rigidity subscore and the amplitude of stimulation-evoked beta oscillations.
Description
The relationship (slope) between the UPDRS-III subscores (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Secondary Outcome Measure Information:
Title
Effect of eiDBS suppression vs. off-stimulation on finger tapping displacement
Description
The finger tapping displacement will be derived based on data from an inertial measuring unit via a Kalman filter. The relationship (slope/effect) between this kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS amplification vs. off-stimulation on finger tapping displacement
Description
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS suppression vs. off-stimulation on forearm displacement
Description
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS amplification vs. off-stimulation on forearm displacement
Description
The relationship (slope/effect) between the kinematic variable (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS suppression vs. off-stimulation on UPDRS-III bradykinesia subscore
Description
The relationship (slope/effect) between this UPDRS-III subscore (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Effect of eiDBS amplification vs. off-stimulation on UPDRS-III bradykinesia subscore
Description
The relationship (slope/effect) between this UPDRS-III subscore (response variable) and the mean amplitude of beta (11-35 Hz) oscillations (predictor physiological variable) will be estimated via linear mixed-effects (LME) models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Correlation between levodopa-related changes in finger tapping displacement and the amplitude of stimulation-evoked beta oscillations
Description
The relationship (slope) between the kinematic measurements (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Correlation between levodopa-related changes in forearm displacement and the amplitude of stimulation-evoked beta oscillations
Description
The relationship (slope) between the kinematic measurements (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.
Title
Correlation between levodopa-related changes in UPDRS-III bradykinesia subscore and the amplitude of stimulation-evoked beta oscillations
Description
The relationship (slope) between the UPDRS-III subscores (response variable) and the beta oscillations amplitude (predictor variable) will be estimated via the linear mixed-effects models.
Time Frame
Data will be collected in assessment blocks multiple times throughout enrollment. Assessments will be performed for up to nine days, starting the day after the DBS surgery. Assessments may also be performed in one visit 3-12 months after DBS surgery.

10. Eligibility

Sex
All
Minimum Age & Unit of Time
40 Years
Maximum Age & Unit of Time
80 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Key Inclusion Criteria: Ability to provide informed consent. Clinical diagnosis of idiopathic Parkinson's disease. Determined, as per standard of care, to be a candidate for deep brain stimulation (DBS) surgery targeting either the subthalamic nucleus or the internal segment of the globus pallidus. Ability to tolerate delays in taking daily standard Parkinson's disease medications. Key Exclusion Criteria: - Secondary Parkinsonism, stroke, or progressive central nervous system disease other than Parkinson's disease.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
David Escobar, PhD
Phone
216-390-1907
Email
escobad2@ccf.org
First Name & Middle Initial & Last Name or Official Title & Degree
Jeffrey Negrey, MA
Phone
216-316-6896
Email
negreyj2@ccf.org
Facility Information:
Facility Name
Cleveland Clinic
City
Cleveland
State/Province
Ohio
ZIP/Postal Code
44195
Country
United States
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
David Escobar, PhD
Phone
216-390-1907
Email
escobad2@ccf.org
First Name & Middle Initial & Last Name & Degree
Jeffrey Negrey, MA
Phone
216-316-6896
Email
negreyj2@ccf.org

12. IPD Sharing Statement

Plan to Share IPD
Yes
IPD Sharing Plan Description
Individual participant data that underlie the results reported in the published articles (text, tables, figures, and appendices), after deidentification, will be shared.
IPD Sharing Time Frame
Data will be shared immediately following publication. There is no end date for this data sharing.
IPD Sharing Access Criteria
Data sharing requests should be directed to escobad2@ccf.org. To gain access, data requestors may need to sign a data access agreement.

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Personalized Real-Time DBS and PD Mechanisms

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