Feasibility of magnetomyography with optically pumped magnetometers in a mobile magnetic shield.

While magnetomyography (MMG) using optically pumped magnetometers (OPMs) is a promising method for non-invasive investigation of the neuromuscular system, it has almost exclusively been performed in magnetically shielded rooms (MSRs) to date. MSRs provide extraordinary conditions for biomagnetic measurements but limit the widespread adoption of measurement methods due to high costs and extensive infrastructure. In this work, we address this issue by exploring the feasibility of mobile OPM-MMG in a setup of commercially available components. From field mapping and simulations, we find that the employed zero-field OPM can operate within a large region of the mobile shield, beyond which residual magnetic fields and perturbations become increasingly intolerable. Moreover, with digital filtering and moderate averaging a signal quality comparable to that in a heavily shielded MSR is attained. These findings facilitate practical and cost-effective implementations of OPM-MMG systems in clinical practice and research.

Programming of subthalamic nucleus deep brain stimulation for Parkinson's disease with sweet spot-guided parameter suggestions.

Deep Brain Stimulation (DBS) is an effective treatment for advanced Parkinson's disease. However, identifying stimulation parameters, such as contact and current amplitudes, is time-consuming based on trial and error. Directional leads add more stimulation options and render this process more challenging with a higher workload for neurologists and more discomfort for patients. In this study, a sweet spot-guided algorithm was developed that automatically suggested stimulation parameters. These suggestions were retrospectively compared to clinical monopolar reviews. A cohort of 24 Parkinson's disease patients underwent bilateral DBS implantation in the subthalamic nucleus at our center. First, the DBS' leads were reconstructed with the open-source toolbox Lead-DBS. Second, a sweet spot for rigidity reduction was set as the desired stimulation target for programming. This sweet spot and estimations of the volume of tissue activated were used to suggest (i) the best lead level, (ii) the best contact, and (iii) the effect thresholds for full therapeutic effect for each contact. To assess these sweet spot-guided suggestions, the clinical monopolar reviews were considered as ground truth. In addition, the sweet spot-guided suggestions for best lead level and best contact were compared against reconstruction-guided suggestions, which considered the lead location with respect to the subthalamic nucleus. Finally, a graphical user interface was developed as an add-on to Lead-DBS and is publicly available. With the interface, suggestions for all contacts of a lead can be generated in a few seconds. The accuracy for suggesting the best out of four lead levels was 56%. These sweet spot-guided suggestions were not significantly better than reconstruction-guided suggestions (p = 0.3). The accuracy for suggesting the best out of eight contacts was 41%. These sweet spot-guided suggestions were significantly better than reconstruction-guided suggestions (p < 0.001). The sweet spot-guided suggestions of each contact's effect threshold had a mean error of 1.2 mA. On an individual lead level, the suggestions can vary more with mean errors ranging from 0.3 to 4.8 mA. Further analysis is warranted to improve the sweet spot-guided suggestions and to account for more symptoms and stimulation-induced side effects.