Defining the Border of the Subthalamic Nucleus for Deep Brain Stimulation: A Proposed Model using the Symmetrical Sigmoid Curve Function

BACKGROUND: The subthalamic nucleus (STN) is an important target in deep brain stimulation (DBS). Accurate lead placement is integral for achieving satisfactory clinical outcomes, however the STN remains a structure whose visualization is highly variable with borders often difficult to define. We aimed to develop an objective method of evaluating the visibility of the STN on preoperative MRI, to standardize future comparative assessments between imaging protocols and patient-specific parameters.

METHODS: An imaging study of 64 prospectively collected patients undergoing bilateral DBS of the STN for various movement disorders was performed with institutional approval. Images were acquired using a uniform protocol involving general anaesthesia, cranial fixation in a Leksell stereotactic frame, and long acquisition times in a 3T MRI scanner. Images were analysed on the iPlan Stereotaxy workstation (Brainlab, v2.6). High resolution T2 axial sections were evaluated and voxel values in the region of the presumed posterior border of the STN (as defined by the operating neurosurgeon) were obtained. A four-parameter logistic symmetrical sigmoid curve was employed to map the voxel values as they progressed from within to outside the region of the STN border. The inflection point and Hill coefficient of this symmetrical curve was calculated to provide objective information on the location and clarity of the STN border, respectively. This was compared with the surgeon's judgement of the STN border. To demonstrate the employment of the sigmoid curve, patient head volumes were also calculated and evaluated to assess if larger head volumes adversely affected STN visibility.

RESULTS: The symmetrical sigmoid curve model provided objective information on the visibility of the STN on T2 MRI, and could be generated in 86% of patients. Fourteen percent of patients had MRIs which generated linear graphs, indicating the poorest scoring of STN image quality. No correlation between head volume and visibility of the STN was identified.

CONCLUSION: Our proposed statistical model allows for standardized examination of the visibility of the STN border for DBS, and has potential for both clinical and academic application.