Session Information
Date: Saturday, October 6, 2018
Session Title: Parkinson’s Disease: Clinical Trials, Pharmacology And Treatment
Session Time: 1:45pm-3:15pm
Location: Hall 3FG
Objective: To assess the feasibility and efficacy of a novel closed-loop programming algorithm (CLPA) for deep brain stimulation (DBS) based on objective feedback using a motion sensor.
Background: The advancement of devices has enabled additional combinations of DBS programming settings to achieve better outcomes, although the programming has become more complicated. Development of a computer-guided CLPA based on objective feedback may make DBS programming easier for clinicians.
Methods: A pilot study to compare the computer-based programming methods utilizing CLPA and the standard of care programming by a DBS expert (SOC) was performed. Twelve patients with Parkinson’s disease who had been implanted bilaterally with eight‐contact DBS leads (VerciseTM DBS system, Boston Scientific) in the Subthalamic nucleus (STN) for at least 6 months with unchanged programming settings over 4 weeks were enrolled. The CLPA would suggest iterative stimulation settings based on the motor outcome at previous settings, as measured by an accelerometer (Kinesia®, Great Lakes NeuroTechnologies). The number of steps to achieve the final setting expected as the “best” were tracked. Additionally, motor outcomes were measured by accelerometer as well as by the Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) by a blinded neurologist, at baseline and after each programming method, in a random order.
Results: The number of steps was significantly lower in the CLPA (22.5±7.2) than the SOC (53.8±10.5). The scores of accelerometer and UPDRS-III were significantly improved, compared with baseline (27.0±5.9 and 38.6±9.5), by both CLPA (18.2±7.6 and 20.2±7.0) and SOC (17.6±6.1 and 17.4±5.7points) (p <.05). There was no significant difference between CLPA and SOC in the degree of improvement of motor symptoms evaluated by accelerometer and UPDRS-III.
Conclusions: These results indicate that CLPA is a feasible and useful algorithm to determine adequate stimulation parameters for STN-DBS.
To cite this abstract in AMA style:
F. Sasaki, G. Oyama, S. Sekimoto, R. Nakamura, T. Jo, H. Iwamuro, A. Umemura, Y. Shimo, N. Hattori. Closed Loop Programming Evaluation Using External Responses for Deep Brain Stimulation (CLOVER-DBS) [abstract]. Mov Disord. 2018; 33 (suppl 2). https://www.mdsabstracts.org/abstract/closed-loop-programming-evaluation-using-external-responses-for-deep-brain-stimulation-clover-dbs/. Accessed May 13, 2025.« Back to 2018 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/closed-loop-programming-evaluation-using-external-responses-for-deep-brain-stimulation-clover-dbs/