Systems and methods for determining volume of activation for deep brain stimulation
First Claim
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1. A computer system comprising a processor that comprises:
- a finite element model (FEM) circuit, configured to determine a FEM that models an implanted electrode, a tissue medium in which the electrode is implanted, and an electrode-tissue interface;
a Fourier FEM solver circuit communicatively coupled to the FEM circuit and configured to calculate a potential distribution in the tissue medium using information from the FEM circuit and a capacitive component of at least one of the electrode, the tissue medium, and the electrode-tissue interface, wherein the calculating includes;
separating a stimulus waveform into frequency components;
obtaining a solution of a Poisson equation at at least one frequency component with a stiffness matrix (σ
+iω
), wherein the stiffness matrix is representative of the capacitive component of the at least one of the electrode, the tissue medium, and the electrode-tissue interface; and
using the solution to reassemble the stimulus waveform; and
a volume of activation (VOA) circuit, communicatively coupled to the Fourier FEM solver circuit, configured to provide a predicted VOA using the potential distribution and a neuron model.
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Abstract
This document discusses, among other things, systems and methods for determining volume of activation for deep brain stimulation (“DBS”) using a finite element model (FEM) circuit to determine a FEM of an implanted electrode and a tissue medium in which the electrode is implanted, a Fourier FEM solver circuit to calculate a potential distribution in the tissue medium using information from the FEM circuit and a capacitive component of at least one of the implanted electrode and the tissue medium, and a volume of activation (VOA) circuit to predict a VOA using the potential distribution and a neuron model.
211 Citations
19 Claims
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1. A computer system comprising a processor that comprises:
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a finite element model (FEM) circuit, configured to determine a FEM that models an implanted electrode, a tissue medium in which the electrode is implanted, and an electrode-tissue interface; a Fourier FEM solver circuit communicatively coupled to the FEM circuit and configured to calculate a potential distribution in the tissue medium using information from the FEM circuit and a capacitive component of at least one of the electrode, the tissue medium, and the electrode-tissue interface, wherein the calculating includes; separating a stimulus waveform into frequency components; obtaining a solution of a Poisson equation at at least one frequency component with a stiffness matrix (σ
+iω
), wherein the stiffness matrix is representative of the capacitive component of the at least one of the electrode, the tissue medium, and the electrode-tissue interface; andusing the solution to reassemble the stimulus waveform; and a volume of activation (VOA) circuit, communicatively coupled to the Fourier FEM solver circuit, configured to provide a predicted VOA using the potential distribution and a neuron model. - View Dependent Claims (2, 3)
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4. A computer system comprising a processor that comprises:
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a finite element model (FEM) circuit, configured to determine a FEM that models an implanted electrode and a tissue medium in which the electrode is implanted; a Fourier FEM solver circuit communicatively coupled to the FEM circuit and configured to calculate a potential distribution in the tissue medium using information from the FEM circuit and a capacitive component of at least one of the electrode and the tissue medium, wherein the calculating includes; separating a stimulus waveform into frequency components; obtaining a solution of a Poisson equation at at least one frequency component with a stiffness matrix (σ
+iω
), wherein the stiffness matrix is representative of the capacitive component of the at least one of the electrode and the tissue medium; andusing the solution to reassemble the stimulus waveform; and a volume of activation (VOA) circuit, communicatively coupled to the Fourier FEM solver circuit, configured to provide a predicted VOA using the potential distribution and a neuron model. - View Dependent Claims (5, 6, 7, 8)
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9. A non-transitory computer-readable storage medium, including instructions that, when performed by a computer, cause the computer to:
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determine a finite element model (FEM) of an implanted electrode and a tissue medium in which the electrode is implanted; calculate a potential distribution in the tissue medium using a Fourier FEM solver and a capacitive component of at least one of the electrode and the tissue medium, wherein the calculating includes; separating a stimulus waveform into frequency components; obtaining a solution of a Poisson equation at at least one frequency component with a stiffness matrix (σ
+iω
), wherein the stiffness matrix is representative of the capacitive component of the at least one of the electrode and the tissue medium; andusing the solution to reassemble the stimulus waveform; and predict a volume of activation (VOA) using the potential distribution and a neuron model.
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10. A computer system comprising a processor that is programmed to perform steps comprising:
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determining a finite element model (FEM) of an implanted electrode and a tissue medium in which the electrode is implanted; calculating a potential distribution in the tissue medium using a Fourier FEM solver and a capacitive component of at least one of the electrode and the tissue medium, wherein the calculating includes; separating a stimulus waveform into frequency components; obtaining a solution of a Poisson equation at at least one frequency component with a stiffness matrix (σ
+iω
), wherein the stiffness matrix is representative of the capacitive component of the at least one of the electrode and the tissue medium; andusing the solution to reassemble the stimulus waveform; and predicting a volume of activation (VOA) using the potential distribution and a neuron model.
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11. A computer-assisted method comprising:
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determining a finite element model (FEM) of an implanted electrode, a tissue medium in the electrode is implanted, and an electrode-tissue interface; calculating a potential distribution in the tissue medium using a Fourier FEM solver and a capacitive component of at least one of the electrode, the tissue medium, and the electrode-tissue interface, wherein the calculating the potential distribution in the tissue medium includes; separating a stimulus waveform into frequency components; obtaining a solution of a Poisson equation at at least one frequency component with a stiffness matrix (σ
+iω
), wherein the stiffness matrix is representative of the capacitive component of the at least one of the electrode, the tissue medium, and the electrode-tissue interface; andusing the solution to reassemble the stimulus waveform; and predicting a volume of activation (VOA) using the potential distribution and a neuron model. - View Dependent Claims (12, 13)
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14. A computer-assisted method comprising:
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determining a finite element model (FEM) of an implanted electrode and a tissue medium in which the electrode is implanted; calculating a potential distribution in the tissue medium using a Fourier FEM solver and a capacitive component of at least one of the electrode and the tissue medium, wherein the calculating the potential distribution includes; separating a stimulus waveform into frequency components; obtaining a solution of a Poisson equation at at least one frequency component with a stiffness matrix (σ
+iω
), wherein the stiffness matrix is representative of the capacitive component of the at least one of the electrode and the tissue medium; andusing the solution to reassemble the stimulus waveform; and predicting a volume of activation (VOA) using the potential distribution and a neuron model. - View Dependent Claims (15, 16, 17, 18)
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19. A method comprising:
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determining a finite element model (FEM) of an implanted electrode, a tissue medium in which the electrode is implanted, and an electrode-tissue interface; calculating an impedance by dividing a stimulation voltage by an integrated current density along an active electrode contact; calculating a potential distribution in the tissue medium in both time and space using a Fourier FEM solver, using a capacitive component of at least one of the electrode, the tissue medium, and the electrode-tissue interface, and using the calculated impedance, wherein the calculating the potential distribution includes; separating a stimulus waveform into frequency components; obtaining a solution of a Poisson equation at at least one frequency component with a stiffness matrix (σ
+iω
), wherein the stiffness matrix is representative of a capacitive component of at least one of the electrode and the tissue medium; andusing the solution to reassemble the stimulus waveform; and predicting a volume of activation (VOA) using multiple stimulation waveforms;
using the potential distribution, and using a neuron model;wherein the predicting the VOA includes interpolating the potential distribution onto a plurality of model axons.
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Specification