Background: Directional deep brain stimulation (DBS) allows for steering of the stimulation field, but extensive and time-consuming testing of all segmented contacts is necessary to identify the possible benefit of steering. It is therefore important to determine under which circumstances directional current steering is advantageous.
Methods: Fifty two Parkinson's disease patients implanted in the STN with a directional DBS system underwent a standardized monopolar programming session 5 to 9 months after implantation.
Background: Deep brain stimulation (DBS) programming of multicontact DBS leads relies on a very time-consuming manual screening procedure, and strategies to speed up this process are needed. Beta activity in subthalamic nucleus (STN) local field potentials (LFP) has been suggested as a promising marker to index optimal stimulation contacts in patients with Parkinson disease.
Objective: In this study, we investigate the advantage of algorithmic selection and combination of multiple resting and movement state features from STN LFPs and imaging markers to predict three relevant clinical DBS parameters (clinical efficacy, therapeutic window, side-effect threshold).
Objectives: Subthalamic nucleus (STN) deep brain stimulation (DBS) programming in patients with Parkinson disease (PD) may be challenging, especially when using segmented leads. In this study, we integrated a previously validated probabilistic STN sweet spot into a commercially available software to evaluate its predictive value for clinically effective DBS programming.
Materials And Methods: A total of 14 patients with PD undergoing bilateral STN DBS with segmented leads were included.
Objective: Deep brain stimulation (DBS) is a treatment option for refractory chronic cluster headache (CCH). Despite several recent prospective case series reporting a good outcome, the effectiveness and the optimal stimulation target of DBS for CCH remain unclear. We aimed to obtain precise estimates and predictors of long-term pain relief in an individual patient data meta-analysis.
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