Background: Deep brain stimulation for obsessive-compulsive disorder is a rapidly developing treatment strategy for treatment-refractory patients. Both the exact target and impact on distributed brain networks remain a matter of debate. Here, we investigated which regions connected to stimulation sites contribute to clinical improvement effects and whether connectivity is able to predict outcomes.
Methods: We analyzed 22 patients (13 female) with treatment-refractory obsessive-compulsive disorder undergoing deep brain stimulation targeting the anterior limb of the internal capsule/nucleus accumbens. We calculated stimulation-dependent optimal connectivity separately for patient-specific connectivity data of 10 patients and for 12 additional patients using normative connectivity. Models of optimal connectivity were subsequently used to predict outcome in both an out-of-sample cross-validation and a leave-one-out cross-validation across the whole group.
Results: The resulting models successfully cross-predicted clinical outcomes of the respective other sample, and a leave-one-out cross-validation across the whole group further demonstrated robustness of our findings (r = .630, p < .001). Specifically, the degree of connectivity between stimulation sites and medial and lateral prefrontal cortices significantly predicted clinical improvement. Finally, we delineated a frontothalamic pathway that is crucial to be modulated for beneficial outcome.
Conclusions: Specific connectivity profiles, encompassing frontothalamic streamlines, can predict clinical outcome of deep brain stimulation for obsessive-compulsive disorder. After further validation, our findings may be used to guide both deep brain stimulation targeting and programming and to inform noninvasive neuromodulation targets for obsessive-compulsive disorder.
Keywords: Connectome; Deep brain stimulation (DBS); Diffusion magnetic resonance imaging (dMRI); Lead-DBS; Obsessive-compulsive disorder (OCD); Tractography.
Copyright © 2019 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.