Compares probabilistic and deterministic tractography methods for targeting brain areas in essential tremor, highlighting accuracy implications.
Introduction The ventral intermediate nucleus (VIM) is a key target for deep brain stimulation (DBS) in treating essential tremor (ET). However, conventional indirect targeting often overlooks individual anatomic variability. Diffusion tractography (DT) offers a patient‐specific approach, but its effectiveness depends on the chosen method. Objective To compare the performance of nine DT methods for presurgical targeting of the VIM and Ventralis Caudalis (VC) in the thalamus. Methods We applied five probabilistic and four deterministic tractography methods to pre‐operative diffusion images from 15 ET patients. The dentato‐rubro‐thalamic (DRT) and spinothalamic (ST) tracts were reconstructed to localize the VIM and VC. Patient‐specific targets were defined as the centers‐of‐gravity (CoG) of thalamic tract‐density indices. Accuracy was evaluated by comparing CoGs with post‐implantation electrode locations, given the lack of direct anatomical validation. Additional metrics included the lateral distance from the third ventricle and the VIM–VC distance. Statistical analysis used Kruskal–Wallis and Dunn's tests. Results Tractography methods showed substantial inter‐ and intra‐method variability. Probabilistic approaches specifically constrained spherical deconvolution (CSD)‐based tractography exhibited lower variability and closer correspondence to planned and implanted lead locations. CSD‐based tractography also demonstrated greater anatomical separation between the VIM from the VC compared with several deterministic approaches. Conclusions Probabilistic methods, especially CSD‐based approaches, showed promising accuracy and reliability, results should be interpreted with caution given the retrospective design and indirect accuracy estimates. These findings highlight the need for prospective studies with anatomical validation but also suggest how optimized tractography methods may help refine targeting strategies.
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Alizadeh et al. (2026) studied this question.
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