Abstract

Deep brain stimulation (DBS) promises to treat an increasing number of neurological and psychiatric disorders. DBS outcome is directly a factor of optimal targeting of the relevant brain structures. Computational models can help to interpret a patient's outcome by predicting the volume of tissue activated (VTA) around DBS electrode contacts. Here we report results of a preliminary study of DBS in two patients with obsessive-compulsive disorder and show that VTA predictions, which are based on patient-specific volume conductor models, correlate with clinical outcome. Our results suggest that patient specific VTA calculation can help inform device programing to maximize therapeutic effects and minimize side effects.Clinical Relevance- Patient-specific modeling of the volume of activated tissue can predict clinical outcomes and thus, can help to optimize DBS device programing to maximize therapeutic effects.

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