Deep Brain Stimulation (DBS) of the subthalamic nucleus (STN) is a common treatment
of Parkinson's disease (PD), but its optimal therapeutic outcomes and long-term success
depend on accurate targeting. STN-DBS targeting is conventionally initiated using
consensus coordinates relative to the mid-commissural point (MCP) with refinement
using direct imaging. In this study, we develop a machine learning (ML) model that
utilizes previously validated and salient x, y, and z coordinates, known as anatomical
fiducials (AFIDs), that can be placed within millimeters of accuracy on structural
T1w MRI scans to predict STN center location.
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© 2022 Published by Elsevier Inc.
