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Evaluation of intradural stimulation efficiency and selectivity in a computational model of spinal cord stimulation.
Abstract
Spinal cord stimulation (SCS) is an alternative or adjunct therapy to treat chronic
pain, a prevalent and clinically challenging condition. Although SCS has substantial
clinical success, the therapy is still prone to failures, including lead breakage,
lead migration, and poor pain relief. The goal of this study was to develop a computational
model of SCS and use the model to compare activation of neural elements during intradural
and extradural electrode placement. We constructed five patient-specific models of
SCS. Stimulation thresholds predicted by the model were compared to stimulation thresholds
measured intraoperatively, and we used these models to quantify the efficiency and
selectivity of intradural and extradural SCS. Intradural placement dramatically increased
stimulation efficiency and reduced the power required to stimulate the dorsal columns
by more than 90%. Intradural placement also increased selectivity, allowing activation
of a greater proportion of dorsal column fibers before spread of activation to dorsal
root fibers, as well as more selective activation of individual dermatomes at different
lateral deviations from the midline. Further, the results suggest that current electrode
designs used for extradural SCS are not optimal for intradural SCS, and a novel azimuthal
tripolar design increased stimulation selectivity, even beyond that achieved with
an intradural paddle array. Increased stimulation efficiency is expected to increase
the battery life of implantable pulse generators, increase the recharge interval of
rechargeable implantable pulse generators, and potentially reduce stimulator volume.
The greater selectivity of intradural stimulation may improve the success rate of
SCS by mitigating the sensitivity of pain relief to malpositioning of the electrode.
The outcome of this effort is a better quantitative understanding of how intradural
electrode placement can potentially increase the selectivity and efficiency of SCS,
which, in turn, provides predictions that can be tested in future clinical studies
assessing the potential therapeutic benefits of intradural SCS.
Type
Journal articleSubject
Spinal CordHumans
Paresthesia
Electrodes
Electric Conductivity
Finite Element Analysis
Models, Neurological
Spinal Cord Stimulation
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https://hdl.handle.net/10161/23855Published Version (Please cite this version)
10.1371/journal.pone.0114938Publication Info
Howell, Bryan; Lad, Shivanand P; & Grill, Warren M (2014). Evaluation of intradural stimulation efficiency and selectivity in a computational
model of spinal cord stimulation. PloS one, 9(12). pp. e114938. 10.1371/journal.pone.0114938. Retrieved from https://hdl.handle.net/10161/23855.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Warren M. Grill
Edmund T. Pratt, Jr. School Distinguished Professor of Biomedical Engineering
Our research employs engineering approaches to understand and control neural function.
We work on fundamental questions and applied development in electrical stimulation
of the nervous system to restore function to individuals with neurological impairment
or injury.
Current projects include:• understanding the mechanisms of and developing advanced
approaches to deep brain stimulation to treat movement disorders, • developing
novel approaches to peripheral nerve e
Bryan Howell
Assistant Research Professor in the Department of Biomedical Engineering
My lab studies implantable and wearable devices for treating neurological impairment,
namely with deep brain stimulation (DBS) and transcranial electrical stimulation (tES).
Projects evolve through theoretical and preclinical stages of development, combining
biophysical and dynamic causal modeling, medical imaging, and device prototyping,
to test new concepts and strategies for these neurotechnologies. Noninvasive studies
on tES are conducted in tissue phantoms and healthy human subjects in-hous
Shivanand Lad
Professor of Neurosurgery
Dr. Nandan Lad is a neurosurgeon, scientist, and entrepreneur and Professor and Vice
Chair of Innovation for Duke Neurosurgery. He is Director of the Functional & Restorative
Neuromodulation Program and the Duke NeuroInnovations Program, a systematic approach
to innovation to large unmet clinical needs. He completed his MD and PhD in Biochemistry
at Chicago Medical School and his neurosurgical residency training at Stanford with
fellowships in both Surgical Innovation and
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