Abstract

Purpose: To depict the specific brain networks that are modulated by deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson’s disease (PD), using diffusion tensor imaging-based fibre tractography (DTI-FT).Materials and methods: Nine patients who received bilateral STN-DBS for PD were included. Electrodes were localized by co-registering preoperative magnetic resonance imaging and postoperative computed tomography. The volume of tissue activated (VTA) was estimated as an isotropic, spherical electric field distribution centred at each effective electrode contact’s centroid coordinates, taking into account individual stimulation parameters (i.e. voltage, impedance). Brain connectivity analysis was undertaken using a deterministic DTI-FT method, seeded from a single region of interest corresponding to the VTA. The labelling of the reconstructed white matter fibre tracts relied on their path and (sub)cortical termination territories.Results: Six months after surgery, we observed a statistically significant reduction in both the Unified Parkinson Disease Rating Scale part III and L-dopa equivalent daily dose. Areas consistently connected to the VTA included the brainstem (100%), cerebellum (94%), dorsal (i.e. supplementary motor area) and lateral premotor cortex (94%), and primary motor cortex (72%). An involvement of the hyperdirect pathway (HDP) connecting the STN and the (pre)motor cortex was demonstrated.Conclusions: The connectivity patterns observed in this study suggest that the therapeutic effects of STN-DBS are mediated through the modulation of distributed, large-scale motor networks. Specifically, the depiction of projection neurons connecting the stimulated area/STN to the (pre)motor cortex, reinforce the growing evidence that the HDP might be a potential therapeutic target in PD. If further replicated, these findings could raise the possibility that DTI-FT reconstruction of the HDP may critically improve DBS targeting and stimulation parameters selection, through the development of programming tools that incorporate VTA modelling and patient-specific DTI-FT data.

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