Literature DB >> 20728313

Predicting white matter targets for direct neurostimulation therapy.

Marvin A Rossi1, Glenn Stebbins, Christopher Murphy, David Greene, Spencer Brinker, David Sarcu, Aaron Tenharmsel, Travis Stoub, Michael A Stein, Thomas J Hoeppner, Richard W Byrne, Michael E Moseley, Roland A Bammer, Steve Bild, Jennifer Dennis, Nichole Arnett, Antoaneta Balabanov, Donna Bergen, Andres M Kanner, Michael C Smith.   

Abstract

A novel depth electrode placement planning strategy is presented for propagating current to distant epileptic tissue during direct neurostimulation therapy. Its goal is to predict optimal lead placement in cortical white matter for influencing the maximal extent of the epileptic circuit. The workflow consists of three fundamental techniques to determine responsive neurostimulation depth lead placement in a patient with bilaterally independent temporal lobe epileptogenic regions. (1) Pre-implantation finite element modeling was used to predict the volume of cortical activation (VOCA). This model estimated the electric field and neural tissue influenced surrounding two adjacent active depth contacts prior to implantation. The calculations included anticipated stimulation parameters. (2) Propagation of stimulation therapy was simulated pre-implantation using the VOCA model positioned in the subject's diffusion tensor imaging (DTI) determined 8h post-ictally compared to an interictal DTI. (3) Validation of the predicted stimulated anatomical targets was determined 4.3 months post-implantation using subtracted activated SPECT (SAS). Presurgically, the modeling system predicted white matter connectivity and visual side-effects to stimulation. Post-implantation, SAS validated focal blood flow changes in ipsilateral occipital and frontal regions, and contralateral temporal lobe. This workflow demonstrates the feasibility of planning white matter-electrode placement with individual specificity to predict propagation of electrical current throughout an epileptic circuit.
Copyright © 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 20728313     DOI: 10.1016/j.eplepsyres.2010.07.010

Source DB:  PubMed          Journal:  Epilepsy Res        ISSN: 0920-1211            Impact factor:   3.045


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