Programming deep brain stimulation (DBS) is still based on a trial-and-error approach, often becoming a time-consuming process for both treating physicians and patients. Several strategies have been proposed to streamline DBS programming, most of which are preliminary and mainly address Parkinson's disease, a condition readily responsive to DBS adjustments. In the present proof-of-principle pilot study, we successfully demonstrate that local field potential (LFP)-based programming can be an effective approach when used for DBS indications that have a delayed temporal onset of benefit.
Materials and Methods
A recently commercialized implantable pulse generator (IPG) with the capability to non-invasively and chronically stream live and/or record LFPs from a DBS electrode after implantation was used to program one pediatric patient with generalized dystonia and an adult with seizures refractory to multiple medications and vagal nerve stimulation.
Results
The IPG survey function detected a peak in the delta range (1.95 Hz) in the left globus pallidus of the first patient. This LFP was detected when recording in the brain area adjacent to contacts 9 and 10 and absent when recording from other areas. The chronic recording of the 1.95 Hz LFP with two sets of stimulation showed a greater power increase with the settings associated with a worsening of dystonia. Broadband LFP home recording of “absence seizure” and “focal/partial seizure” was used in the second patient and reviewer with the IPG “timeline” and “event” functions. The chronic recording of the 2.93 Hz and 8.79 Hz (spit sensing) showed a reduced power with the stimulation setting associated with seizure control.
Conclusions
The approach presented in this pilot proof-of-concept study may inform and streamline the DBS programming for conditions requiring clinicians and patients to wait weeks before appreciating any clinical benefit. Prospective studies on larger samples of patients are warranted.
Keywords
Deep brain stimulation
local field potential
neuromodulation
percept
programming
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Conflict of Interest: Alfonso Fasano received honoraria and research support from Abbott, Boston Scientific, Brainlab, Ceregate, InBrain, and Medtronic. Suneil K. Kalia received honoraria from Medtronic and InBrain. All other authors have no relevant disclosures.
Source(s) of financial support: This study was funded by the University of Toronto and University Health Network Chair in Neuromodulation and Multidisciplinary Care to AF.
[Correction added on September 6, 2021, after first online publication: The copyright line was changed.]
