Probabilistic versus deterministic tractography for delineation of the cortico-subthalamic hyperdirect pathway in patients with Parkinson disease selected for deep brain stimulation

OBJECTIVE Diffusion-weighted MRI (DWI) and tractography allows noninvasive mapping of the structural connections of the brain, and may provide important information for neurosurgical planning. The hyperdirect pathway, connecting the subthalamic nucleus (STN) with the motor cortex, is assumed to play a key role in mediating the effects of deep brain stimulation (DBS), which is an effective but poorly understood treatment for Parkinson disease. This study aimed to apply recent methodological advances in DWI acquisition and analysis to the delineation of the hyperdirect pathitay in patients with Parkinson disease selected for surgery. METHODS High spatial and angular resolution DWI data were acquired preoperatively from 5 patients with Parkinson disease undergoing DBS. The authors compared the delineated hyperdirect pathways and associated STN target maps generated by 2 different tractography methods: a tensor-based deterministic method, typically available in clinical settings, and an advanced probabilistic method based on constrained spherical deconvolution. In addition, 10 high resolution data sets with the same scanning parameters were acquired from a healthy control participant to assess the robustness of the tractography results. RESULTS Both tractography approaches identified connections between the ipsilateral motor cortex and the STN. However, the 2 methods provided substantially different target regions in the STN, with the target center of gravity differing by > 1.4 mm on average. The probabilistic method (based on constrained spherical deconvolution) plausibly reconstructed a continuous set of connections from the motor cortex, terminating in the dorsolateral region of the STN. In contrast, the tensor-based method reconstructed a comparatively sparser and more variable subset of connections. Furthermore, across the control scans, the probabilistic method identified considerably more consistent targeting regions within the STN compared with the deterministic tensor-based method, which demonstrated a 1.9-2.4 times higher variation. CONCLUSIONS These data provide a strong impetus for the use of a robust probabilistic tractography framework based on constrained spherical deconvolution, or similar advanced DWI models, in clinical settings. The inherent limitations and demonstrated inaccuracy of the tensor-based method leave it questionable for use in high-precision stereotactic DBS surgery. The authors have also described a straightforward method for importing tractography-derived information into any clinical neuronavigation system, based on the generation of track-density images.