RESUMO
BACKGROUND: Deep brain stimulation (DBS) is an established method of treatment for Parkinson's disease (PD). A stimulation sweet spot at the interface between the motor and associative clusters of the subthalamic nucleus (STN) has recently been postulated. The aim of this study was to analyze the available clustering methods for the STN and their correlation to outcome. METHODS: This is a retrospective analysis of a group of 20 patients implanted with a DBS device for PD. Atlas-based and diffusion tractography-based parcellation of the STN was performed. The distances of the electrode to the obtained clusters were compared to each other and to outcome parameters, which included levodopa equivalent dose (LED) reduction, Unified Parkinson's Disease Rating Scale (UPDRS)-III scores, and reduction in scores for items 32 and 36 of the UPDRS-IV. RESULTS: The implanted electrodes were located nearest to the motor clusters of the STN. The following significant associations with postoperative LED reduction were found: (1) distance of the electrode to the motor cluster in the Accolla and DISTAL atlases (p < 0.01) and (2) distance of the electrode to the supplementary motor area cluster (p = 0.02). There was no association with either the UPDRS-III or the UPDRS-IV score. CONCLUSIONS: The results of this study suggest the possibility that atlas-based clustering, as well as diffusion tractography-based parcellation, can be useful in estimating the stimulation target ("sweet spot") for STN-DBS in PD patients. Atlas-based as well as diffusion-based clustering might become a useful tool in DBS trajectory planning.