Deep brain stimulation surgery time reduction based on the automatic detection of the subthalamic nucleus: method and preliminary results

Deep brain stimulation (DBS) surgery of the subthalamic nucleus (STN) is an effective therapy in the management of the motor symptoms of advanced Parkinson's disease (PD). The accurate localization of the STN is essential to achieve an optimal outcome of the DBS treatment. Therefore, microelectrode recording (MER) is often utilized for target validation and refinement, although it often extends the surgery time and its costs. The extra time required by MER is likely related to the number of recorded points along the trajectory and to the duration of recording at each of these points. However, reducing the number of recording locations and/or recording duration may result in a lower STN detection accuracy. To quantify this tradeoff, we have developed a method to retrospectively estimate the accuracy of STN detection on data from 100 microelectrode trajectories. In our study, dense and long MER data was acquired and down-sampled in the spatial and temporal domains. Then, the STN borders were detected automatically on both the down-sampled and the original data and compared to each other. Our results show that sampling duration of STN activity can be minimized to one second per recording without compromising accuracy. We conclude that bilateral DBS surgery time may be shortened by more than one hour while maintaining good targeting accuracy.