Prediction of STN-DBS Electrode Implantation Track in Parkinson’s Disease by Using Local Field Potentials

Optimal electrophysiological placement of the DBS electrode may lead to better long term clinical outcomes. Inter-subject anatomical variability and limitations in stereotaxic neuroimaging increase the complexity of physiological mapping performed in the operating room. Microelectrode single unit neuronal recording remains the most common intraoperative mapping technique, but requires significant expertise and is fraught by potential technical difficulties including robust measurement of the signal. In contrast, local field potentials (LFPs), owing to their oscillatory and robust nature and being more correlated with the disease symptoms, can overcome these technical issues. Therefore, we hypothesized that multiple spectral features extracted from microelectrode-recorded LFPs could be used to automate the identification of the optimal track and the STN localization. In this regard, we recorded LFPs from microelectrodes in three tracks from 22 patients during DBS electrode implantation surgery at different depths and aimed to predict the track selected by the neurosurgeon based on the interpretation of single unit recordings. A least mean square (LMS) algorithm was used to de-correlate LFPs in each track, in order to remove common activity between channels and increase their spatial specificity. Subband power in the beta band (11-32Hz) and high frequency range (200-450Hz) were extracted from the de-correlated LFP data and used as features. A linear discriminant analysis (LDA) method was applied both for the localization of the dorsal border of STN and the prediction of the optimal track. By fusing the information from these low and high frequency bands, the dorsal border of STN was localized with a root mean square error of 1.22 mm. The prediction accuracy for the optimal track was 80%. Individual beta band (11-32Hz) and the range of high frequency oscillations (200-450Hz) provided prediction accuracies of 72% and 68% respectively. The best prediction result obtained with monopolar LFP data was 68%. These results establish the initial evidence that LFPs can be strategically fused with computational intelligence in the operating room for STN localization and the selection of the track for chronic DBS electrode implantation

The International Deep Brain Stimulation Registry and Database for Gilles de la Tourette Syndrome: How Does It Work?

Tourette Syndrome (TS) is a neuropsychiatric disease characterized by a combination of motor and vocal tics. Deep brain stimulation (DBS), already widely utilized for Parkinson's disease and other movement disorders, is an emerging therapy for select and severe cases of TS that are resistant to medication and behavioral therapy. Over the last two decades, DBS has been used experimentally to manage severe TS cases. The results of case reports and small case series have been variable but in general positive. The reported interventions have, however, been variable, and there remain non-standardized selection criteria, various brain targets, differences in hardware, as well as variability in the programming parameters utilized. DBS centers perform only a handful of TS DBS cases each year, making large-scale outcomes difficult to study and to interpret. These limitations, coupled with the variable effect of surgery, and the overall small numbers of TS patients with DBS worldwide, have delayed regulatory agency approval (e.g., FDA and equivalent agencies around the world). The Tourette Association of America, in response to the worldwide need for a more organized and collaborative effort, launched an international TS DBS registry and database. The main goal of the project has been to share data, uncover best practices, improve outcomes, and to provide critical information to regulatory agencies. The international registry and database has improved the communication and collaboration among TS DBS centers worldwide. In this paper we will review some of the key operation details for the international TS DBS database and registry