Selection of deep brain stimulation contacts using volume of tissue activated software following subthalamic nucleus stimulation
High-frequency deep brain stimulation (DBS) of the subthalamic nucleus (STN) is effective in the treatment of motor symptoms of Parkinson's disease. Using a patient-specific lead and volume of tissue activated (VTA) software, it is possible to visualize contact positions in the context of the p...
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Published in | Journal of neurosurgery Vol. 135; no. 2; p. 611 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
01.08.2021
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Subjects | |
Online Access | Get more information |
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Summary: | High-frequency deep brain stimulation (DBS) of the subthalamic nucleus (STN) is effective in the treatment of motor symptoms of Parkinson's disease. Using a patient-specific lead and volume of tissue activated (VTA) software, it is possible to visualize contact positions in the context of the patient's own anatomy. In this study, the authors' aim was to demonstrate that VTA software can be used in clinical practice to help determine the clinical effectiveness of stimulation in patients with Parkinson's disease undergoing DBS of the STN.
Brain images of 26 patients undergoing STN DBS were analyzed using VTA software. Preoperative clinical and neuropsychological data were collected. Contacts were chosen by two experts in DBS blinded to the clinical data. A therapeutic window of amplitude was determined. These results were compared with the parameter settings for each patient. Data were obtained at 3 months and 1 year postsurgery.
In 90.4% (95% CI 82%-98%) of the patients, the contacts identified by the VTA software were concordant with the clinically effective contacts or with an effective contact in contact-by-contact testing. The therapeutic window of amplitude selected virtually included 81.3% of the clinical amplitudes.
VTA software appears to present significant concordance with clinical data for selecting contacts and stimulation parameters that could help in postoperative follow-up and programming. |
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ISSN: | 1933-0693 |
DOI: | 10.3171/2020.6.JNS192157 |