Evaluation of Predictors of Treatment Response in Subthalamic Nucleus Deep Brain Stimulation for Parkinson’s Disease Using Connectomics and Wearable Sensors
Tanziyah Muqeem1, Angela Noecker2, Alaa Norain3, Tiffany Tran3, Cameron McIntyre2, Kyle Mitchell3
1Duke University Hospital, 2Duke Pratt School of Engineering, 3Duke University Movement Disorders Center
Objective:
To evaluate a method to provide comprehensive symptom monitoring and models of tract-specific modulation before and after Subthalamic Nucleus (STN) Deep Brain Stimulation (DBS) for Parkinson’s Disease.
Background:
Parkinson’s Disease is a prevalent neurodegenerative disorder that affects over 8.5 million people worldwide. DBS helps treat motor fluctuations and/or dyskinesia in advancing disease. DBS programming occurs in a time intensive trial/error fashion without insight into how activation of specific tracts may create a personalized treatment paradigm for each patient. Programming settings are also performed based on static exam findings, unable to consider fluctuations of symptoms over time.
Design/Methods:
We established a framework for collecting a comprehensive dataset that considers granular exam findings at clinic visits (Movement Disorders Society Unified Parkinson Disease Rating Scale [MDS-UPDRS] for bradykinesia, tremor, rigidity, and gait/posture), longitudinal symptom tracking with wearable devices (tremor/dyskinesia probability), and modeling of tract activation based on lead placement. We analyzed this data pre- and post-DBS implantation in six patients who underwent bilateral STN placement.
Results:
We observed changes in MDS-UPDRS scores and wearable symptom tracking pre- and post-DBS that allow for dynamic measurements in a patient-specific manner. The results demonstrate the use of wearable data as a continuous stream of information to evaluate the interplay between medications and stimulation paradigm and how this differentially affects each individual patient in a disease that can fluctuate hour to hour. We also show how tract activation models and imaging can allow for a granular analysis of symptom control. Preliminarily, we found a possible trend towards rigidity control and cerebellothalamic tract activation and bradykinesia control and hyperdirect tract activation. The model showed there was minimal activation of the internal capsule tract in these subjects (n=6).
Conclusions:
We demonstrate a multi-modal approach to assessing treatment response after DBS in patients with Parkinson’s Disease.