Juan Carlos Baldermann1, Corina Melzer2, Alexandra Zapf3, Sina Kohl4, Lars Timmermann5, Marc Tittgemeyer2, Daniel Huys4, Veerle Visser-Vandewalle6, Andrea A Kühn7, Andreas Horn7, Jens Kuhn8. 1. Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany. Electronic address: juan.baldermann@uk-koeln.de. 2. Max Planck Institute for Metabolism Research Cologne, University Hospital Cologne, Cologne, Germany. 3. Department of Medical Psychology ǀ Neuropsychology and Gender Studies & Center for Neuropsychological Diagnostics and Intervention, University Hospital Cologne, Cologne, Germany. 4. Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany. 5. Department of Neurology, University Hospital Giessen & Marburg, Marburg, Germany. 6. Department of Stereotactic and Functional Neurosurgery, University of Cologne, Cologne, Germany. 7. Department of Neurology, Movement Disorders and Neuromodulation Unit, Charité-University Medicine, Berlin, Germany. 8. Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany; Department of Psychiatry and Psychotherapy, Johanniter Hospital Oberhausen, Oberhausen, Germany.
Abstract
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.
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.
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