Commonly used for Parkinson’s disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.
Deep brain stimulation (DBS) is a neuromodulatory treatment used in patients with drug-resistant epilepsy (DRE). The primary goal of this systematic review and metaanalysis is to describe recent advancements in the field of DBS for epilepsy, to compare the results of published trials, and to clarify the clinical utility of DBS in DRE. A systematic literature search was performed by two independent authors. Forty-four articles were included in the meta-analysis (23 for anterior thalamic nucleus [ANT], 8 for centromedian thalamic nucleus [CMT], and 13 for hippocampus) with a total of 527 patients. The mean seizure reduction after stimulation of the ANT, CMT, and hippocampus in our meta-analysis was 60.8%, 73.4%, and 67.8%, respectively. DBS is an effective and safe therapy in patients with DRE. Based on the results of randomized controlled trials and larger clinical series, the best evidence exists for DBS of the anterior thalamic nucleus. Further randomized trials are required to clarify the role of CMT and hippocampal stimulation. Our analysis suggests more efficient deep brain stimulation of ANT for focal seizures, wider use of CMT for generalized seizures, and hippocampal DBS for temporal lobe seizures. Factors associated with clinical outcome after DBS for epilepsy are electrode location, stimulation parameters, type of epilepsy, and longer time of stimulation. Recent advancements in anatomical targeting, functional neuroimaging, responsive neurostimulation, and sensing of local field potentials could potentially lead to improved outcomes after DBS for epilepsy and reduced sudden, unexpected death of patients with epilepsy. Biomarkers are needed for successful patient selection, targeting of electrodes and optimization of stimulation parameters.
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