A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder

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Publicado en:Nature Communications vol. 11, no. 1 (2020)
Autor principal: Li, Ningfei
Otros Autores: Baldermann, Juan Carlos, Kibleur Astrid, Treu Svenja, Harith, Akram, Elias Gavin J B, Boutet Alexandre, Lozano, Andres M, Al-Fatly, Bassam, Strange, Bryan, Barcia, Juan A, Ludvic, Zrinzo, Joyce, Eileen, Chabardes Stephan, Visser-Vandewalle Veerle, Polosan Mircea, Kuhn, Jens, Kühn, Andrea A, Horn, Andreas
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Nature Publishing Group
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Acceso en línea:Citation/Abstract
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Resumen:Multiple surgical targets for treating obsessive-compulsive disorder with deep brain stimulation (DBS) have been proposed. However, different targets may modulate the same neural network responsible for clinical improvement. We analyzed data from four cohorts of patients (N = 50) that underwent DBS to the anterior limb of the internal capsule (ALIC), the nucleus accumbens or the subthalamic nucleus (STN). The same fiber bundle was associated with optimal clinical response in cohorts targeting either structure. This bundle connected frontal regions to the STN. When informing the tract target based on the first cohort, clinical improvements in the second could be significantly predicted, and vice versa. To further confirm results, clinical improvements in eight patients from a third center and six patients from a fourth center were significantly predicted based on their stimulation overlap with this tract. Our results show that connectivity-derived models may inform clinical improvements across DBS targets, surgeons and centers. The identified tract target is openly available in atlas form.Li et al. analyzed structural connectivity of deep brain stimulation electrodes in 50 patients suffering from obsessive-compulsive disorder operated at four centers. Connectivity to a specific tract within the anterior limb of the internal capsule was associated with optimal treatment response across cohorts, surgeons and centers.
ISSN:2041-1723
DOI:10.1038/s41467-020-16734-3
Fuente:Medical Database