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Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes

delete2018-01-24
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OA
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D
Daria Nesterovich Anderson
B
Braxton Osting
A
Alan D. Dorval
C
Christopher R. Butson *
DOI:10.1088/1741-2552/aaa14bdelete
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摘要

摘要

En 中文
Objective. Deep brain stimulation (DBS) is a growing treatment option for movement and psychiatric disorders. As DBS technology moves toward directional leads with increased numbers of smaller electrode contacts, trial-and-error methods of manual DBS programming are becoming too time-consuming for clinical feasibility. We propose an algorithm to automate DBS programming in near real-time for a wide range of DBS lead designs. Approach. Magnetic resonance imaging and diffusion tensor imaging are used to build finite element models that include anisotropic conductivity. The algorithm maximizes activation of target tissue and utilizes the Hessian matrix of the electric potential to approximate activation of neurons in all directions. We demonstrate our algorithm's ability in an example programming case that targets the subthalamic nucleus (STN) for the treatment of Parkinson's disease for three lead designs: the Medtronic 3389 (four cylindrical contacts), the direct STNAcute (two cylindrical contacts, six directional contacts), and the Medtronic-Sapiens lead (40 directional contacts). Main results. The optimization algorithm returns patient-specific contact configurations in near real-time-less than 10 s for even the most complex leads. When the lead was placed centrally in the target STN, the directional leads were able to activate over 50% of the region, whereas the Medtronic 3389 could activate only 40%. When the lead was placed 2 mm lateral to the target, the directional leads performed as well as they did in the central position, but the Medtronic 3389 activated only 2.9% of the STN. Significance. This DBS programming algorithm can be applied to cylindrical electrodes as well as novel directional leads that are too complex with modern technology to be manually programmed. This algorithm may reduce clinical programming time and encourage the use of directional leads, since they activate a larger volume of the target area than cylindrical electrodes in central and off-target lead placements.
Keyword:
deep brain stimulation
optimization algorithm
hessian
activating function
Parkinson's disease
finite element model
directional electrodes
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期刊

Journal of Neural Engineering 封面图
Journal of Neural Engineering
IF:
3.8
论文数:
4.0K
被引数:
1.5W

机构

U
university of utah
学者数:
1.1K
论文数: 524
被引数: 0
U
Utah System of Higher Education
学者数:
4.6W
论文数: 4.0W
被引数: 1.2W
引用论文

引用论文

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