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.
Deep brain stimulation (DBS) is becoming increasingly central in the treatment of patients with Parkinson’s disease and other movement disorders. Recent developments in DBS lead and implantable pulse generator design provide increased flexibility for programming, potentially improving the therapeutic benefit of stimulation. Directional DBS leads may increase the therapeutic window of stimulation by providing a means of avoiding current spread to structures that might give rise to stimulation-related side effects. Similarly, control of current to individual contacts on a DBS lead allows for shaping of the electric field produced between multiple active contacts. The following review aims to describe the recent developments in DBS system technology and the features of each commercially available DBS system. The advantages of each system are reviewed, and general considerations for choosing the most appropriate system are discussed.
A BS TRACT: Background: In patients with medically refractory essential tremor, unilateral magnetic resonanceguided focused ultrasound thalamotomy can improve contralateral tremor. However, this procedure does not address ipsilateral symptoms. Objective: The objective of the current study was to determine whether bilateral thalamotomies can be performed with an acceptable safety profile where benefits outweigh adverse effects. Methods: We conducted a prospective, single-arm, single-blinded phase 2 trial of second-side magnetic resonance-guided focused ultrasound thalamotomy in patients with essential tremor. Patients were followed for 3 months. The primary outcome was the change in quality of life relative to baseline, as well as the answer to the question "Given what you know now, would you treat the second side again?". Secondary outcomes included tremor, gait, speech, and adverse effects. Results: Ten patients were analyzed. The study met both primary outcomes, with the intervention resulting in clinically significant improvement in quality of life at 3 months (mean Quality of Life in Essential Tremor score difference, 19.7; 95%CI,; P = 0.004) and all patients reporting that they would elect to receive the secondside treatment again. Tremor significantly improved in all patients. Seven experienced mild adverse effects, including 2 with transient gait impairment and a fall, 1 with dysarthria and dysphagia, and 1 with mild dysphagia persisting at 3 months.
Self-supervised pretraining followed by supervised finetuning has seen success in image recognition, especially when labeled examples are scarce, but has received limited attention in medical image analysis. This paper studies the effectiveness of self-supervised learning as a pretraining strategy for medical image classification. We conduct experiments on two distinct tasks: dermatology skin condition classification from digital camera images and multilabel chest X-ray classification, and demonstrate that selfsupervised learning on ImageNet, followed by additional self-supervised learning on unlabeled domain-specific medical images significantly improves the accuracy of medical image classifiers. We introduce a novel Multi-Instance Contrastive Learning (MICLe) method that uses multiple images of the underlying pathology per patient case, when available, to construct more informative positive pairs for self-supervised learning. Combining our contributions, we achieve an improvement of 6.7% in top-1 accuracy and an improvement of 1.1% in mean AUC on dermatology and chest X-ray classification respectively, outperforming strong supervised baselines pretrained on ImageNet. In addition, we show that big self-supervised models are robust to distribution shift and can learn efficiently with a small number of labeled medical images.
Background: Electrical stimulation in the kilohertz-frequency range has gained interest in the field of neuroscience. The mechanisms underlying stimulation in this frequency range, however, are poorly characterized to date. Objective/hypothesis: To summarize the manifold biological effects elicited by kilohertz-frequency stimulation in the context of the currently existing literature and provide a mechanistic framework for the neural responses observed in this frequency range. Methods: A comprehensive search of the peer-reviewed literature was conducted across electronic databases. Relevant computational, clinical, and mechanistic studies were selected for review. Results: The effects of kilohertz-frequency stimulation on neural tissue are diverse and yield effects that are distinct from conventional stimulation. Broadly, these can be divided into 1) subthreshold, 2) suprathreshold, 3) synaptic and 4) thermal effects. While facilitation is the dominating mechanism at the subthreshold level, desynchronization, spike-rate adaptation, conduction block, and non-monotonic activation can be observed during suprathreshold kilohertz-frequency stimulation. At the synaptic level, kilohertz-frequency stimulation has been associated with the transient depletion of the available neurotransmitter pool e also known as synaptic fatigue. Finally, thermal effects associated with extrinsic (environmental) and intrinsic (associated with kilohertz-frequency stimulation) temperature changes have been suggested to alter the neural response to stimulation paradigms. Conclusion:The diverse spectrum of neural responses to stimulation in the kilohertz-frequency range is distinct from that associated with conventional stimulation. This offers the potential for new therapeutic avenues across stimulation modalities. However, stimulation in the kilohertz-frequency range is associated with distinct challenges and caveats that need to be considered in experimental paradigms.
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