Sweetspot Mapping in Deep Brain Stimulation: Strengths and Limitations of Current Approaches
Till A. Dembek, Juan Carlos Baldermann, Jan Niklas Petry‐Schmelzer, Hannah Jergas, Harald Treuer, Veerle Visser‐Vandewalle, Haidar S. Dafsari, Michael T. Barbe
Abstract
OBJECTIVES: Open questions remain regarding the optimal target, or sweetspot, for deep brain stimulation (DBS) in, for example, Parkinson's disease. Previous studies introduced different methods of mapping DBS effects to determine sweetspots. While having a direct impact on surgical targeting and postoperative programming in DBS, these methods so far have not been compared. MATERIALS AND METHODS: . RESULTS: The five investigated methods resulted in highly variable sweetspots. Methods based on voxel-wise statistics against average outcomes showed the best performance overall. While predictive capabilities were high, even in the best of cases Dice coefficients remained limited to values around 0.5, highlighting the overall limitations of sweetspot identification. CONCLUSIONS: This study highlights the strengths and limitations of current approaches to DBS sweetspot mapping. Those limitations need to be taken into account when considering the clinical implications. All future approaches should be investigated in silico before being applied to clinical data.