Patient-specific analysis of the volume of tissue activated during Deep Brain Stimulation

Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH 44195, USA.
NeuroImage (Impact Factor: 6.36). 02/2007; 34(2):661-70. DOI: 10.1016/j.neuroimage.2006.09.034
Source: PubMed


Despite the clinical success of deep brain stimulation (DBS) for the treatment of movement disorders, many questions remain about its effects on the nervous system. This study presents a methodology to predict the volume of tissue activated (VTA) by DBS on a patient-specific basis. Our goals were to identify the intersection between the VTA and surrounding anatomical structures and to compare activation of these structures with clinical outcomes. The model system consisted of three fundamental components: (1) a 3D anatomical model of the subcortical nuclei and DBS electrode position in the brain, each derived from magnetic resonance imaging (MRI); (2) a finite element model of the DBS electrode and electric field transmitted to the brain, with tissue conductivity properties derived from diffusion tensor MRI; (3) VTA prediction derived from the response of myelinated axons to the applied electric field, which is a function of the stimulation parameters (contact, impedance, voltage, pulse width, frequency). We used this model system to analyze the effects of subthalamic nucleus (STN) DBS in a patient with Parkinson's disease. Quantitative measurements of bradykinesia, rigidity, and corticospinal tract (CST) motor thresholds were evaluated over a range of stimulation parameter settings. Our model predictions showed good agreement with CST thresholds. Additionally, stimulation through electrode contacts that improved bradykinesia and rigidity generated VTAs that overlapped the zona incerta/fields of Forel (ZI/H2). Application of DBS technology to various neurological disorders has preceded scientific characterization of the volume of tissue directly affected by the stimulation. Synergistic integration of clinical analysis, neuroimaging, neuroanatomy, and neurostimulation modeling provides an opportunity to address wide ranging questions on the factors linked with the therapeutic benefits and side effects of DBS.

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    • "The simplified model, however, did not reproduce all of the experimental findings. It is possible that discrepancies between the model and experiments may be due to anisotropy and heterogeneity in the conductivity of brain tissue and/or the geometry of the target neural elements (figure 9), and future computational models should account for these features when designing electrodes for specific DBS applications (Butson et al 2007, Chaturvedi et al 2010, Frankemolle et al 2010). "
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    ABSTRACT: Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, the efficiency and selectivity of DBS can be improved. Our objective was to design electrode geometries that increased the efficiency and selectivity of DBS. We coupled computational models of electrodes in brain tissue with cable models of axons of passage (AOPs), terminating axons (TAs), and local neurons (LNs); we used engineering optimization to design electrodes for stimulating these neural elements; and the model predictions were tested in vivo. Compared with the standard electrode used in the Medtronic Model 3387 and 3389 arrays, model-optimized electrodes consumed 45-84% less power. Similar gains in selectivity were evident with the optimized electrodes: 50% of parallel AOPs could be activated while reducing activation of perpendicular AOPs from 44 to 48% with the standard electrode to 0-14% with bipolar designs; 50% of perpendicular AOPs could be activated while reducing activation of parallel AOPs from 53 to 55% with the standard electrode to 1-5% with an array of cathodes; and, 50% of TAs could be activated while reducing activation of AOPs from 43 to 100% with the standard electrode to 2-15% with a distal anode. In vivo, both the geometry and polarity of the electrode had a profound impact on the efficiency and selectivity of stimulation. Model-based design is a powerful tool that can be used to improve the efficiency and selectivity of DBS electrodes.
    Journal of Neural Engineering 07/2015; 12(4):046030. DOI:10.1088/1741-2560/12/4/046030 · 3.30 Impact Factor
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    • "Model predictions of the voltage distribution in the brain during DBS were validated by in vivo recordings in a non-human primate [8]. Model predictions of the VTA/SFM were indirectly validated by detecting stimulation-induced side effects such as STN DBS-induced activation of the corticospinal tract [3] [5]. These experiments and others provided evidence to demonstrate the accuracy of the modeling approach. "
    Brain Stimulation 06/2015; 20(5). DOI:10.1016/j.brs.2015.06.005 · 4.40 Impact Factor
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    • "The computational model used to establish the effects of stimulation has been previously described in detail (Butson et al., 2007). The electric field was calculated using a finite element model constructed in COMSOL v4.3 (COMSOL, Lenexa, KS), taking into account the geometry of the stimulation electrode and the configuration of anodes and cathodes. "
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    ABSTRACT: Recent studies in patients with treatment-resistant depression have shown similar results with the use of deep brain stimulation (DBS) in the subcallosal cingulate gyrus (SCG), ventral capsule/ventral striatum (VC/VS) and nucleus accumbens (Acb). As these brain regions are interconnected, one hypothesis is that by stimulating these targets one would just be influencing different relays in the same circuitry. We investigate behavioural, immediate early gene expression, and functional connectivity changes in rats given DBS in homologous regions, namely the ventromedial prefrontal cortex (vmPFC), white matter fibers of the frontal region (WMF) and nucleus accumbens. We found that DBS delivered to the vmPFC, Acb but not WMF induced significant antidepressant-like effects in the FST (31%, 44%, and 17% reduction in immobility compared to controls). Despite these findings, stimulation applied to these three targets induced distinct patterns of regional activity and functional connectivity. While animals given vmPFC DBS had increased cortical zif268 expression, changes after Acb stimulation were primarily observed in subcortical structures. In animals receiving WMF DBS, both cortical and subcortical structures at a distance from the target were influenced by stimulation. In regards to functional connectivity, DBS in all targets decreased intercorrelations among cortical areas. This is in contrast to the clear differences observed in subcortical connectivity, which was reduced after vmPFC DBS but increased in rats receiving Acb or WMF stimulation. In conclusion, results from our study suggest that, despite similar antidepressant-like effects, stimulation of the vmPFC, WMF and Acb induce distinct changes in regional brain activity and functional connectivity.
    Neurobiology of Disease 08/2014; 71. DOI:10.1016/j.nbd.2014.08.007 · 5.08 Impact Factor
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