Deep brain stimulation (DBS) is an established clinical therapy for movement disorders and is positioned to grow as a treatment for neuropsychiatric disorders. Subcallosal cingulate white matter (SCCWM) DBS has potential to improve the lives of patients with treatment-resistant depression (TRD);however, the specific white matter pathway(s) responsible for therapeutic benefit from stimulation remain unknown. The goal of this project is to identify the key axonal pathways directly stimulated by therapeutic SCCWM DBS. We will combine patient-specific diffusion-weighted imaging (DWI) based tractography with neurostimulation modeling to enable probabilistic identification of the axonal pathways whose direct activation is linked to changes in clinical outcome metrics measured in SCCWM DBS patients. We hypothesize that therapeutic benefit from SCCWM DBS is dependent upon activation of pathways associated with the ventromedial pre-frontal cortex (vmPFC) and its subcortical connections. We will use patient-specific tractography-activation models (TAMs) to evaluate our hypothesis by analyzing patients enrolled in investigator initiated clinical trials of SCCWM DBS (FDA IDE G060028 &FDA IDE G130107).
Our specific aims call for the development of TAMs in a cohort of 35 total SCCWM DBS patients. Results from these models will enable us to evolve our hypothesis on the target pathways for stimulation and help us to differentiate between therapeutic and non-therapeutic pathways by creating a probabilistic stimulation atlas (PSA). We will also compare our SCCWM results with TAMs derived from ventral capsule (VC) DBS for TRD, as it may be possible that common target pathways exist between the different surgical targets. Finally, we will use our TAMs to investigate theoretically optimal methods for stimulating our PSA-identified target pathways. The results of this study have great potential to assist in the evolution of neuropsychiatric DBS technology and help guide future clinical protocols.
Deep brain stimulation (DBS) is a powerful clinical technology, positively impacting the lives of tens of thousands of patients. The goal of this project is to apply the concepts of patient-specific DBS computer modeling to study the effects of DBS on patients with treatment resistant depression. Results from this project will enable the design of more efficacious stimulation strategies for patients implanted with DBS systems.
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