Abstract
BackgroundThough deep brain stimulation (DBS) shows increasing potential in treatment-resistant depression (TRD), the underlying neural mechanisms remain unclear. Here, we investigated functional and structural connectivities related to and predictive of clinical effectiveness of DBS at ventral capsule/ventral striatum region for TRD.MethodsStimulation effects of 71 stimulation settings in 10 TRD patients were assessed. The electric fields were estimated and combined with normative functional and structural connectomes to identify connections as well as fibre tracts beneficial for outcome. We calculated stimulation-dependent optimal connectivity and constructed models to predict outcome. Leave-one-out cross-validation was used to validate the prediction value.ResultsSuccessful prediction of antidepressant effectiveness in out-of-sample patients was achieved by the optimal connectivity profiles constructed with both the functional connectivity (R=0.49 at p<10-4; deviated by 14.4±10.9% from actual, p<0.001) and structural connectivity (R=0.51 at p<10-5; deviated by 15.2±11.5% from actual, p<10-5). Frontothalamic pathways and cortical projections were delineated for optimal clinical outcome. Similarity estimates between optimal connectivity profile from one modality (functional/structural) and individual brain connectivity in the other modality (structural/functional) significantly cross-predicted the outcome of DBS. The optimal structural and functional connectivity mainly converged at the ventral and dorsal lateral prefrontal cortex and orbitofrontal cortex.ConclusionsConnectivity profiles and fibre tracts following frontothalamic streamlines appear to predict outcome of DBS for TRD. The findings shed light on the neural pathways in depression and may be used to guide both presurgical planning and postsurgical programming after further validation.
Funder
SJTU
Scenery Inc
Shanghai Sailing Program
National Natural Science Foundation of China
Shanghai Clinical Research Centre for Mental Health
Medical Research Council
Guangci Professorship Programme of Ruijin Hospital
Shanghai Municipal Science and Technology Commission
Subject
Psychiatry and Mental health,Neurology (clinical),Surgery
Cited by
6 articles.
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