Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has rapidly emerged as an effective treatment in medically refractory Parkinson's disease (PD). However, our understanding of the effects of DBS is limited and as a result programming DBS devices for optimal clinical benefit is a difficult and time consuming process. The central hypothesis of the planned work is that patient-specific models of DBS can predict a theoretically optimal stimulation parameter setting that will provide therapeutic benefit equal to that achieved by current trial-and-error programming strategies. The fundamental concept behind this project is that if clinicians had tools that enabled visualization of the anatomical and electrical effects of DBS they would be able to quickly and accurately adjust the stimulation for maximal therapeutic benefit. Previous work of the principal investigator and his collaborators has provided the core scientific components necessary to realize such a tool. However, no quantitative measures of the size and shape of the 3D volume of tissue activated by DBS currently exist within the clinical arena. Therefore, we propose the development of patient-specific models of STN DBS based on anatomical and diffusion tensor magnetic resonance imaging (MRI). We will use these models to establish correlations between electrode locations / stimulation parameters / volumes of activation and therapeutic benefit as determined from clinical evaluation of individual patients. We will then use the models to define theoretically optimal stimulation parameter settings custom to the individual. The therapeutic efficacy of the model-designed settings will then be compared to the settings determined by current clinical practice. If our hypothesis is supported, we believe the technology and software developed in this study could significantly decrease the time and effort necessary to program DBS devices, and be applicable to a wide range of clinical applications including PD, essential tremor, dystonia, epilepsy, and obsessive-compulsive disorder.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21NS050449-02
Application #
7140439
Study Section
Special Emphasis Panel (ZRG1-BDCN-K (10))
Program Officer
Pancrazio, Joseph J
Project Start
2005-07-15
Project End
2007-06-30
Budget Start
2006-07-01
Budget End
2007-06-30
Support Year
2
Fiscal Year
2006
Total Cost
$172,749
Indirect Cost
Name
Cleveland Clinic Lerner
Department
Other Basic Sciences
Type
Schools of Medicine
DUNS #
135781701
City
Cleveland
State
OH
Country
United States
Zip Code
44195
Butson, Christopher R; Cooper, Scott E; Henderson, Jaimie M et al. (2011) Probabilistic analysis of activation volumes generated during deep brain stimulation. Neuroimage 54:2096-104
Chaturvedi, Ashutosh; Butson, Christopher R; Lempka, Scott F et al. (2010) Patient-specific models of deep brain stimulation: influence of field model complexity on neural activation predictions. Brain Stimul 3:65-7
Maks, C B; Butson, C R; Walter, B L et al. (2009) Deep brain stimulation activation volumes and their association with neurophysiological mapping and therapeutic outcomes. J Neurol Neurosurg Psychiatry 80:659-66
Luján, J Luis; Noecker, Angela M; Butson, Christopher R et al. (2009) Automated 3-dimensional brain atlas fitting to microelectrode recordings from deep brain stimulation surgeries. Stereotact Funct Neurosurg 87:229-40
Butson, Christopher R; McIntyre, Cameron C (2008) Current steering to control the volume of tissue activated during deep brain stimulation. Brain Stimul 1:7-15
Lujan, J Luis; Chaturvedi, Ashutosh; McIntyre, Cameron C (2008) Tracking the mechanisms of deep brain stimulation for neuropsychiatric disorders. Front Biosci 13:5892-904
Butson, Christopher R; McIntyre, Cameron C (2007) Differences among implanted pulse generator waveforms cause variations in the neural response to deep brain stimulation. Clin Neurophysiol 118:1889-94
Butson, Christopher R; Cooper, Scott E; Henderson, Jaimie M et al. (2007) Patient-specific analysis of the volume of tissue activated during deep brain stimulation. Neuroimage 34:661-70
McIntyre, Cameron C; Miocinovic, Svjetlana; Butson, Christopher R (2007) Computational analysis of deep brain stimulation. Expert Rev Med Devices 4:615-22
Butson, C R; Noecker, A M; Maks, C B et al. (2007) StimExplorer: deep brain stimulation parameter selection software system. Acta Neurochir Suppl 97:569-74

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