Precise neurosurgical targeting of electrode arrays within the brain is essential to the successful treatment of a range of brain disorders with deep brain stimulation (DBS) therapy. Here, we describe a set of computational tools to generate in vivo, subject-specific atlases of individual thalamic nuclei thus improving the ability to visualize thalamic targets for preclinical DBS applications on a subject-specific basis. A sequential nonlinear atlas warping technique and a Bayesian estimation technique for probabilistic crossing fiber tractography were applied to high field (7T) susceptibility-weighted and diffusion-weighted imaging, respectively, in seven rhesus macaques. Image contrast, including contrast within thalamus from the susceptibility-weighted images, informed the atlas warping process and guided the seed point placement for fiber tractography. The susceptibility-weighted imaging resulted in relative hyperintensity of the intralaminar nuclei and relative hypointensity in the medial dorsal nucleus, pulvinar, and the medial/ventral border of the ventral posterior nuclei, providing context to demarcate borders of the ventral nuclei of thalamus, which are often targeted for DBS applications. Additionally, ascending fiber tractography of the medial lemniscus, superior cerebellar peduncle, and pallidofugal pathways into thalamus provided structural demarcation of the ventral nuclei of thalamus. The thalamic substructure boundaries were validated through in vivo electrophysiological recordings and post-mortem blockface tissue sectioning. Together, these imaging tools for visualizing and segmenting thalamus have the potential to improve the neurosurgical targeting of DBS implants and enhance the selection of stimulation settings through more accurate computational models of DBS.
Bibliographical noteFunding Information:
This work was supported by grants from the National Institutes of Health (R01-NS081118, R01-NS085188, P41-EB015894, P30-076408, and the Human Connectome Project U54-MH091657) and the National Science Foundation (IGERT DGE-1069104 to LZ and GFRP 00006595 to BT). We would like to thank Drs. Vitek, Baker, and Ghose for support for the NHP imaging.
© 2016 Xiao, Zitella, Duchin, Teplitzky, Kastl, Adriany, Yacoub, Harel and Johnson.
- Diffusion weighted imaging
- Fiber tractography
- High-field imaging
- Susceptibility weighted imaging