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.