Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes. (24th January 2018)
- Record Type:
- Journal Article
- Title:
- Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes. (24th January 2018)
- Main Title:
- Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes
- Authors:
- Anderson, Daria Nesterovich
Osting, Braxton
Vorwerk, Johannes
Dorval, Alan D
Butson, Christopher R - Abstract:
- Abstract: 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, theAbstract: 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. … (more)
- Is Part Of:
- Journal of neural engineering. Volume 15:Number 2(2018:Apr.)
- Journal:
- Journal of neural engineering
- Issue:
- Volume 15:Number 2(2018:Apr.)
- Issue Display:
- Volume 15, Issue 2 (2018)
- Year:
- 2018
- Volume:
- 15
- Issue:
- 2
- Issue Sort Value:
- 2018-0015-0002-0000
- Page Start:
- Page End:
- Publication Date:
- 2018-01-24
- Subjects:
- deep brain stimulation -- optimization algorithm -- hessian -- activating function -- Parkinson's disease -- finite element model -- directional electrodes
Neurosciences -- Periodicals
Biomedical engineering -- Periodicals
612.8 - Journal URLs:
- http://iopscience.iop.org/1741-2552/ ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1741-2552/aaa14b ↗
- Languages:
- English
- ISSNs:
- 1741-2560
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 11126.xml