Psychiatric neurosurgery teams in the United States and Europe have studied deep brain stimulation (DBS) of the ventral anterior limb of the internal capsule and adjacent ventral striatum (VC/VS) for severe and highly treatment-resistant obsessive-compulsive disorder. Four groups have collaborated most closely, in small-scale studies, over the past 8 years. First to begin was Leuven/Antwerp, followed by Butler Hospital/Brown Medical School, the Cleveland Clinic and most recently the University of Florida. These centers used comparable patient selection criteria and surgical targeting. Targeting, but not selection, evolved during this period. Here, we present combined long-term results of those studies, which reveal clinically significant symptom reductions and functional improvement in about two-thirds of patients. DBS was well tolerated overall and adverse effects were overwhelmingly transient. Results generally improved for patients implanted more recently, suggesting a 'learning curve' both within and across centers. This is well known from the development of DBS for movement disorders. The main factor accounting for these gains appears to be the refinement of the implantation site. Initially, an anterior-posterior location based on anterior capsulotomy lesions was used. In an attempt to improve results, more posterior sites were investigated resulting in the current target, at the junction of the anterior capsule, anterior commissure and posterior ventral striatum. Clinical results suggest that neural networks relevant to therapeutic improvement might be modulated more effectively at a more posterior target. Taken together, these data show that the procedure can be successfully implemented by dedicated interdisciplinary teams, and support its therapeutic promise.

Background We investigated the use of deep brain stimulation (DBS) of the ventral capsule/ventral striatum (VC/VS) for treatment refractory depression. Methods Fifteen patients with chronic, severe, highly refractory depression received open-label DBS at three collaborating clinical sites. Electrodes were implanted bilaterally in the VC/VS region. Stimulation was titrated to therapeutic benefit and the absence of adverse effects. All patients received continuous stimulation and were followed for a minimum of 6 months to longer than 4 years. Outcome measures included the Hamilton Depression Rating Scale—24 item (HDRS), the Montgomery-Asberg Depression Rating Scale (MADRS), and the Global Assessment of Function Scale (GAF). Results Significant improvements in depressive symptoms were observed during DBS treatment. Mean HDRS scores declined from 33.1 at baseline to 17.5 at 6 months and 14.3 at last follow-up. Similar improvements were seen with the MADRS (34.8, 17.9, and 15.7, respectively) and the GAF (43.4, 55.5, and 61.8, respectively). Responder rates with the HDRS were 40% at 6 months and 53.3% at last follow-up (MADRS: 46.7% and 53.3%, respectively). Remission rates were 20% at 6 months and 40% at last follow-up with the HDRS (MADRS: 26.6% and 33.3%, respectively). The DBS was well-tolerated in this group. Conclusions Deep brain stimulation of the VC/VS offers promise for the treatment of refractory major depression.

Purpose: To assess magnetic resonance imaging (MRI)-related heating for a neurostimulation system (Activa Tremor Control System, Medtronic, Minneapolis, MN) used for chronic deep brain stimulation (DBS). Materials and Methods:Different configurations were evaluated for bilateral neurostimulators (Soletra® Model 7426), extensions, and leads to assess worst-case and clinically relevant positioning scenarios. In vitro testing was performed using a 1.5-T/64-MHz MR system and a gelfilled phantom designed to approximate the head and upper torso of a human subject. MRI was conducted using the transmit/receive body and transmit/receive head radio frequency (RF) coils. Various levels of RF energy were applied with the transmit/receive body (whole-body averaged specific absorption rate (SAR); range, 0.98 -3.90 W/kg) and transmit/receive head (whole-body averaged SAR; range, 0.07-0.24 W/kg) coils. A fluoroptic thermometry system was used to record temperatures at multiple locations before (1 minute) and during (15 minutes) MRI.Results: Using the body RF coil, the highest temperature changes ranged from 2.5°-25.3°C. Using the head RF coil, the highest temperature changes ranged from 2.3°-7.1°C.Thus, these findings indicated that substantial heating occurs under certain conditions, while others produce relatively minor, physiologically inconsequential temperature increases. Conclusion:The temperature increases were dependent on the type of RF coil, level of SAR used, and how the lead wires were positioned. Notably, the use of clinically relevant positioning techniques for the neurostimulation system and low SARs commonly used for imaging the brain generated little heating. Based on this information, MR safety guidelines are provided. These observations are restricted to the tested neurostimulation system.

Chronically implantable, closed-loop neuromodulation devices with concurrent sensing and stimulation hold promise for better understanding the nervous system and improving therapies for neurological disease. Concurrent sensing and stimulation are needed to maximize usable neural data, minimize time delays for closed-loop actuation, and investigate the instantaneous response to stimulation. Current systems lack concurrent sensing and stimulation primarily because of stimulation interference to neural signals of interest. While careful design of high performance amplifiers has proved useful to reduce disturbances in the system, stimulation continues to contaminate neural sensing due to biological effects like tissue-electrode impedance mismatch and constraints on stimulation parameters needed to deliver therapy. In this work we describe systematic methods to mitigate the effect of stimulation through a combination of sensing hardware, stimulation parameter selection, and classification algorithms that counter residual stimulation disturbances. To validate these methods we implemented and tested a completely implantable system for over one year in a large animal model of epilepsy. The system proved capable of measuring and detecting seizure activity in the hippocampus both during and after stimulation. Furthermore, we demonstrate an embedded algorithm that actuates neural modulation in response to seizure detection during stimulation, validating the capability to detect bioelectrical markers in the presence of therapy and titrate it appropriately. The capability to detect neural states in the presence of stimulation and optimally titrate therapy is a key innovation required for generalizing closed-loop neural systems for multiple disease states.

Acute DBS at the VC/VS target is associated with activation of the circuitry implicated in OCD. Further studies will be necessary to replicate these findings and to determine the neural effects associated with chronic VC/VS DBS. Moreover, additional data are needed to investigate whether pretreatment imaging profiles can be used to predict a patient's subsequent clinical response to chronic DBS.

While modulating neural activity through stimulation is an effective treatment for neurological diseases such as Parkinson's disease and essential tremor, an opportunity for improving neuromodulation therapy remains in automatically adjusting therapy to continuously optimize patient outcomes. Practical issues associated with achieving this include the paucity of human data related to disease states, poorly validated estimators of patient state, and unknown dynamic mappings of optimal stimulation parameters based on estimated states. To overcome these challenges, we present an investigational platform including: an implanted sensing and stimulation device to collect data and run automated closed-loop algorithms; an external tool to prototype classifier and control-policy algorithms; and real-time telemetry to update the implanted device firmware and monitor its state. The prototyping system was demonstrated in a chronic large animal model studying hippocampal dynamics. We used the platform to find biomarkers of the observed states and transfer functions of different stimulation amplitudes. Data showed that moderate levels of stimulation suppress hippocampal beta activity, while high levels of stimulation produce seizure-like after-discharge activity. The biomarker and transfer function observations were mapped into classifier and control-policy algorithms, which were downloaded to the implanted device to continuously titrate stimulation amplitude for the desired network effect. The platform is designed to be a flexible prototyping tool and could be used to develop improved mechanistic models and automated closed-loop systems for a variety of neurological disorders.

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