Dyskinesias, Parkinson Disease, Tremor
Conditions
Keywords
DBS, Parkinson's disease, Connectomic, Tremor, Dyskinesia, Wearable
Brief summary
The objective of this research is to use advanced connectomic imaging models to identify disease-relevant axonal pathway targets for better tremor control in Parkinson's disease patients while avoiding undesirable side effects, with the goal of increasing precision and facilitating the choice of optimal DBS parameters for certain disease phenotypes. The investigators hypothesize that patient centered subthalamic nucleus deep brain stimulation of cerebellothalamic axonal pathways and pallidothalamic tract activation can provide better tremor control while avoiding worsening dyskinesias in patients with Parkinson's disease with significant tremor.
Detailed description
Patients with Parkinson's disease (PD) can suffer from significant disability due to tremors, rigidity, bradykinesia, or motor fluctuations, in addition to non-motor symptoms of the disease. Deep brain stimulation (DBS) is the main surgical approach approved by the US Food and Drug Administration (FDA) for the treatment of medication-refractory PD. Despite recent advances, the selection of DBS parameters is based on trial-and-error experimentation by specialists over the course of months. Better understanding of the optimal network targets for symptomatic control would allow for therapy improvement and simplify the DBS programming process, increase efficiency, and possibly increase access to care. Most studies of structural connectivity in PD have focused on the analysis of the subthalamic nucleus (STN). Previous studies analyzing structural connectivity of STN DBS have shown that specific motor symptoms benefit from the activation of different networks. Several tracts such as the cerebellothalamic tract (CBT), pallidothalamic (PT) and corticospinal tract (CST) course through the STN and might be relevant for DBS targeting. For patients with essential tremor, stimulation of the CBT might provide better tremor control, but studies in PD are lacking. The investigators will use connectomic models to better understand the mechanistic qualities of axonal pathways in the STN in Parkinson's disease and address the need for phenotype driven stimulation in PD. Estimating targeted axonal pathways by using connectomic models may guide personalized decision-making and targeting of DBS. It has the potential to improve clinical outcomes and reduce the number of visits needed for DBS optimization. The study involves the extraction of data collected during routine clinical care, and data collected during the intervention study. Data collected during routine clinical care includes: * Demographic characteristics: age, gender, ethnicity, race. * Clinical characteristics: disease duration, Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) prior to DBS implementation, levodopa equivalent daily dose of medications. * Imaging data: DBS lead location, stimulation model activation pathway, recruitment curves, percent of each pathway activated with clinical DBS settings
Interventions
DEVICECerebellothalamic optimized deep brain stimulation
A deep brain stimulation plan will be created by maximizing the cerebellothalamic pathway on the patient-specific connectomic deep brain stimulation model
DEVICEPallidothalamic optimized deep brain stimulation
A deep brain stimulation plan will be created by maximizing the Pallidothalamic pathway on the patient-specific connectomic deep brain stimulation model
OTHERNo deep brain stimulation
Patients will also be tested without any deep brain stimulation
DEVICEUsual care deep brain stimulation
Patient will also be tested with the deep brain stimulation clinical settings that were previously established during usual care with their neurologist
Sponsors
Duke University
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT
Masking
DOUBLE (Subject, Outcomes Assessor)
Masking description
The order in which all four scenarios are tested will be randomized. The MDS-UPDRS III scale will be scored blindly by a second rater based on the de-identified video recorded exam. Participants will be blinded to which stimulation is being used during the recording of their exam.
Intervention model description
Two alternative deep brain stimulation (DBS) stimulation plans will be created by maximizing the stimulation to the cerebellothalamic tract (1) and to the pallidothalamic tract (2) based on the patient-specific connectomic DBS model previously created with recruitment curves. Participants will be asked to attend one single research encounter for DBS programming, MDS-UPDRS scoring and wearable data collection. During their research visit, MDS-UPDRS III (clinical scale) and wearable data will be collected in different scenarios (each setting will be recorded for 20 minutes): * "OFF" oral dopaminergic medication: during no DBS stimulation, usual care stimulation, cerebellothalamic optimized, and pallidothalamic optimized. This will be collected during the morning. * "ON" oral dopaminergic medication: during no DBS stimulation, usual care stimulation, cerebellothalamic optimized, and pallidothalamic optimized
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Age 18 or older * Diagnosed with Parkinson's disease and has previously been implanted with bilateral subthalamic nucleus deep brain stimulation (DBS) * Received DBS at least three months prior to the time of the study to allow for optimization of usual clinical care * With at least mild tremor on a pre-operatory MDS-UPDRS clinical scale as defined by at least 2 out of 4 resting tremor grading on MDS-UPDRS on at least one extremity
Exclusion criteria
* Not having a post-operative head CT with 1mm or smaller axial slices at least 1 week after initial lead implantation. * Patients who received DBS less than three months prior to the start of the study
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Tremor duration as measured by wearables | Approximately eight hours | An Apple iPhone will be used to collect about two hours of data of each participant using accelerometer to estimate tremor duration. This technology has been integrated into the StrivePD application (Rune Labs, San Francisco, CA) and has been used in other studies at Duke University. |
| Tremor severity as measured by wearables | Approximately eight hours | An Apple iPhone will be used to collect about two hours of data of each participant using accelerometer to estimate tremor severity. This technology has been integrated into the StrivePD application (Rune Labs, San Francisco, CA) and has been used in other studies at Duke University. |
| Dyskinesia duration as measured by wearables | Approximately eight hours | An Apple iPhone will be used to collect about two hours of data of each participant using accelerometer to estimate dyskinesia severity duration). This technology has been integrated into the StrivePD application (Rune Labs, San Francisco, CA) and has been used in other studies at Duke University. |
| Dyskinesia severity as measured by wearables | Approximately eight hours | An Apple iPhone will be used to collect about two hours of data of each participant using accelerometer to estimate dyskinesia severity. This technology has been integrated into the StrivePD application (Rune Labs, San Francisco, CA) and has been used in other studies at Duke University. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Tremor severity as measured by the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) | Approximately eight hours | The Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) tremor severity score ranges from 0 to 4, with higher scores indicating greater severity of tremors. |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORKyle Mitchell, MD
Duke University
Outcome results
None listed