Second, we relate DBS outcome to the impact of each electrode on local structures by measuring overlap of stimulation volumes with the STN. We do so by using active coordinates and volumes of tissue activated, showing converging evidence of an optimal DBS target in the dorsolateral STN. Specifically, we demonstrate various ways to visualize placement of all electrodes in the group and map clinical improvement values to subcortical space. In the present article, we showcase the various processing streams of Lead Group in a retrospective cohort of 51 patients suffering from Parkinson’s disease, who were implanted with DBS electrodes to the subthalamic nucleus (STN). Here, we introduce Lead Group, implemented within the Lead-DBS environment and specifically designed to meet aforementioned demands. With the publication of Lead-DBS software in 2014, an open-source tool was introduced that allowed for precise electrode reconstructions based on pre- and postoperative neuroimaging data. Moreover, to allow for comparability across different centers, these need to be performed within an algorithmically and anatomically standardized and openly available group space. Such tools should have the goal to make electrode placement comparable across patients and DBS centers, and include statistical analysis options to validate and define optimal targets. To measure clinical improvement as a function of electrode placement, neuroscientific methodology and specialized software tools are needed. It has been shown that exact electrode placement crucially affects the efficacy of DBS and this should be considered when investigating novel indications or DBS targets. Deep Brain Stimulation (DBS) is an established treatment option for movement disorders and is under investigation for treatment of a growing number of other brain diseases.
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