Thalamic Segmentation and Neural Activation Modeling Based on Individual Tissue Microstructure in Deep Brain Stimulation for Essential Tremor.

OBJECTIVE: Thalamic deep brain stimulation (DBS) is the primary surgical therapy for essential tremor (ET). Thalamic DBS traditionally uses an atlas-based targeting approach, which, although nominally accurate, may obscure individual anatomic differences from population norms. The objective of this study was to compare this traditional atlas-based approach with a novel quantitative modeling methodology grounded in individual tissue microstructure (N-of-1 approach). MATERIALS AND METHODS: The N-of-1 approach uses individual patient diffusion tensor imaging (DTI) data to perform thalamic segmentation and volume of tissue activation (VTA) modeling. For each patient, the thalamus was individually segmented into 13 nuclei using DTI-based k-means clustering. DBS-induced VTAs associated with tremor suppression and side effects were then computed for each patient with finite-element electric-field models incorporating DTI microstructural data. Results from N-of-1 and traditional atlas-based modeling were compared for a large cohort of patients with ET treated with thalamic DBS. RESULTS: The size and shape of individual N-of-1 thalamic nuclei and VTAs varied considerably across patients (N = 22). For both methods, tremor-improving therapeutic VTAs showed similar overlap with motor thalamic nuclei and greater motor than sensory nucleus overlap. For VTAs producing undesirable sustained paresthesia, 94% of VTAs overlapped with N-of-1 sensory thalamus estimates, whereas 74% of atlas-based segmentations overlapped. For VTAs producing dysarthria/motor contraction, the N-of-1 approach predicted greater spread beyond the thalamus into the internal capsule and adjacent structures than the atlas-based method. CONCLUSIONS: Thalamic segmentation and VTA modeling based on individual tissue microstructure explain therapeutic stimulation equally well and side effects better than a traditional atlas-based method in DBS for ET. The N-of-1 approach may be useful in DBS targeting and programming, particularly when patient neuroanatomy deviates from population norms.

Evaluating indirect subthalamic nucleus targeting with validated 3-tesla magnetic resonance imaging.

BACKGROUND/OBJECTIVES: Indirect targeting of the subthalamic nucleus (STN) is commonly utilized at deep brain stimulation (DBS) centers around the world. The superiority of either midcommissural point (MCP)-based or red nucleus (RN)-based indirect targeting remains to be established. METHODS: The location of the STN was determined and statistically compared to MCP- and RN-based predictions in 58 STN DBS patients, using a validated 3-tesla MRI protocol. The influence of additional neuroanatomical parameters on STN midpoint location was evaluated. Linear regression analysis was utilized to produce an optimized MCP/RN targeting model. Targeting coordinates at 1.5 T were compared to results at 3 T. RESULTS: Accuracy and precision for RN-based targeting was superior to MCP-based targeting to predict STN midpoint location for each coordinate dimension (p < 0.01 and p < 0.05, respectively). RN-based targeting was statistically equivalent to an optimized regression-based targeting strategy incorporating multiple neuroanatomical parameters, including third-ventricle width and overall brain size. RN-based targeting at 1.5 T yielded equivalent coordinates to targeting at 3 T. CONCLUSIONS: RN-based targeting is statistically superior to MCP-based STN targeting and accommodates broad variations in neuroanatomical parameters. Neurosurgeons utilizing indirect targeting of the STN may consider favoring RN-based over MCP-based indirect targeting methods.