Commonly used for Parkinson’s disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.

Background: The ventral intermediate nucleus of the thalamus is not readily visible on structural magnetic resonance imaging. Therefore, a method for its visualization for stereotactic targeting is desirable.Objective: The objective of this study was to define a tractography‐based methodology for the stereotactic targeting of the ventral intermediate nucleus.Methods: The lateral and posterior borders of the ventral intermediate nucleus were defined by tracking the pyramidal tract and medial lemniscus, respectively. A thalamic seed was then created 3 mm medial and anterior to these borders, and its structural connections were analyzed. The application of this method was assessed in an imaging cohort of 14 tremor patients and 15 healthy controls, in which we compared the tractography‐based targeting to conventional targeting. In a separate surgical cohort (3 tremor and 3 tremor‐dominant Parkinson's disease patients), we analyzed the accuracy of this method by correlating it with intraoperative neurophysiology.Results: Tractography of the thalamic seed revealed the tracts corresponding to cerebellar input and motor cortical output fibers. The tractography‐based target was more lateral (12.5 [1.2] mm vs 11.5 mm for conventional targeting) and anterior (8.5 [1.1] mm vs 6.7 [0.3] mm, anterior to the posterior commissure). In the surgical cohort, the Euclidian distance between the ventral intermediate nucleus identified by tractography and the surgical target was 1.6 [1.1] mm. The locations of the sensory thalamus, lemniscus, and pyramidal tracts were concordant within <1 mm between tractography and neurophysiology.Interpretation: The tractography‐based methodology for identification of the ventral intermediate nucleus is accurate and useful. This method may be used to improve stereotactic targeting in functional neurosurgery procedures. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society

Trigeminal neuralgia (TN) is a chronic neuropathic facial pain disorder that commonly responds to surgery. A proportion of patients, however, do not benefit and suffer ongoing pain. There are currently no imaging tools that permit the prediction of treatment response. To address this paucity, we used diffusion tensor imaging (DTI) to determine whether pre-surgical trigeminal nerve microstructural diffusivities can prognosticate response to TN treatment. In 31 TN patients and 16 healthy controls, multi-tensor tractography was used to extract DTI-derived metrics-axial (AD), radial (RD), mean diffusivity (MD), and fractional anisotropy (FA)-from the cisternal segment, root entry zone and pontine segment of trigeminal nerves for false discovery rate-corrected Student's t-tests. Ipsilateral diffusivities were bootstrap resampled to visualize group-level diffusivity thresholds of long-term response. To obtain an individual-level statistical classifier of surgical response, we conducted discriminant function analysis (DFA) with the type of surgery chosen alongside ipsilateral measurements and ipsilateral/contralateral ratios of AD and RD from all regions of interest as prediction variables. Abnormal diffusivity in the trigeminal pontine fibers, demonstrated by increased AD, highlighted non-responders (n = 14) compared to controls. Bootstrap resampling revealed three ipsilateral diffusivity thresholds of response-pontine AD, MD, cisternal FA-separating 85% of non-responders from responders. DFA produced an 83.9% (71.0% using leave-one-out-cross-validation) accurate prognosticator of response that successfully identified 12/14 non-responders. Our study demonstrates that pre-surgical DTI metrics can serve as a highly predictive, individualized tool to prognosticate surgical response. We further highlight abnormal pontine segment diffusivities as key features of treatment non-response and confirm the axiom that central pain does not commonly benefit from peripheral treatments.

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