Tractography patterns of subthalamic nucleus deep brain stimulation

Abstract

Deep brain stimulation therapy is an effective symptomatic treatment for Parkinson's disease, yet the precise mechanisms responsible for its therapeutic effects remain unclear. Although the targets of deep brain stimulation are grey matter structures, axonal modulation is known to play an important role in deep brain stimulation's therapeutic mechanism. Several white matter structures in proximity to the subthalamic nucleus have been implicated in the clinical benefits of deep brain stimulation for Parkinson's disease. We assessed the connectivity patterns that characterize clinically beneficial electrodes in Parkinson's disease patients, after deep brain stimulation of the subthalamic nucleus. We evaluated 22 patients with Parkinson's disease (11 females, age 57 ± 9.1 years, disease duration 13.3 ± 6.3 years) who received bilateral deep brain stimulation of the subthalamic nucleus at the National Institutes of Health. During an initial electrode screening session, one month after deep brain stimulation implantation, the clinical benefits of each contact were determined. The electrode was localized by coregistering preoperative magnetic resonance imaging and postoperative computer tomography images and the volume of tissue activated was estimated from stimulation voltage and impedance. Brain connectivity for the volume of tissue activated of deep brain stimulation contacts was assessed using probabilistic tractography with diffusion-tensor data. Areas most frequently connected to clinically effective contacts included the thalamus, substantia nigra, brainstem and superior frontal gyrus. A series of discriminant analyses demonstrated that the strength of connectivity to the superior frontal gyrus and the thalamus were positively associated with clinical effectiveness. The connectivity patterns observed in our study suggest that the modulation of white matter tracts directed to the superior frontal gyrus and the thalamus is associated with favourable clinical outcomes and may contribute to the therapeutic effects of deep brain stimulation. Our method can be further developed to reliably identify effective deep brain stimulation contacts and aid in the programming process.

Connectivity Predicts deep brain stimulation outcome in Parkinson disease

“…Anatomical connectivity (based on diffusion MRI) has higher spatial resolution than functional connectivity (based on fMRI) and is thus more likely to identify differences between adjacent electrode contacts in the same patient. 8,16 However, when predicting outcome across different patients with variability in electrode location, our data suggest that functional connectivity adds predictive value above and beyond anatomical connectivity. This is consistent with other work.…”

“…It is worth noting that our results are broadly consistent with a prior study of STN DBS based on patient-specific connectivity. 16 Future work is needed to determine how to best combine the strengths of normative connectomes, patient-based connectomes, and connectivity data from individual patients.…”

Quantifying axonal responses in patient-specific models of subthalamic deep brain stimulation

“…VTA-Madler and VTA-Astrom were chosen because they are being utilized by a broader community of researchers studying DBS [e.g. Vanegas-Arroyave et al, 2016; Horn et al, 2017]. And, we chose DF-Peterson because it is the most accurate and generalizable DF-based method currently available [Peterson et al, 2011].…”

“…In particular, subthalamic DBS has already been the focus of numerous PAM studies [e.g. Coenen et al, 2011; Chaturvedi et al, 2012; Groppa et al, 2014; Sweet et al, 2014; Accolla et al, 2016; Vanegas-Arroyave et al, 2016; Gunalan et al, 2017; Horn et al, 2017; Akram et al, 2017]. However, the various PAM analyses have employed a wide range of different methods without much in the way of documentation or validation of their accuracy.…”

In vivo Exploration of the Connectivity between the Subthalamic Nucleus and the Globus Pallidus in the Human Brain Using Multi-Fiber Tractography

“…The analysis and interpretation of dMRI data using tractography tools have the potential to bring clinically relevant information for the planning and execution of DBS intervention (Henderson, 2012; Torres et al, 2014; Calabrese, 2016). In recent years, exploratory studies on the use of diffusion tensor imaging based on the single tensor model of diffusion for investigating white matter fibers connecting DBS targets have demonstrated promising findings (Barkhoudarian et al, 2010; Lemaire et al, 2011; Coenen et al, 2014; Rozanski et al, 2014; Sweet et al, 2014; Avecillas-Chasin et al, 2016; Vanegas-Arroyave et al, 2016). However, the tensor model can only identify a single fiber population within a voxel (Alexander et al, 2007).…”