Systems and methods for determining volume of activation for deep brain stimulation

• US 9,020,789 B2
• Filed: 04/04/2012
• Issued: 04/28/2015
• Est. Priority Date: 07/07/2004
• Status: Active Grant

• Current Assignee: Cleveland Clinic Foundation
• Original Assignee: Cleveland Clinic Foundation
• Inventors: Butson, Christopher R., Maks, Christopher B., McIntyre, Cameron C.
• Primary Examiner(s): Chad, Aniss
• Application Number:
  US13/506,216
• Publication Number:
  US 20120197611A1
• Time in Patent Office: 1,119 Days
• Field of Search: 703/2, 703/11
• US Class Current: 703/6
• CPC Class Codes: A61B 5/053 Measuring electrical impedance or conductance of a portion of the body
• CPC Class Codes: A61B 5/0538 invasively, e.g. using a catheter
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence
• CPC Class Codes: A61B 5/7217 of noise originating from a therapeutic or surgical apparatus, e.g. from a pacemaker
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61N 1/0534 Electrodes for deep brain stimulation
• CPC Class Codes: G06F 2119/06 Power analysis or power optimisation
• CPC Class Codes: G06F 30/23 using finite element methods [FEM] or finite difference methods [FDM]
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

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.

Claims

1. A computer system comprising:

a processor configured to execute;

a finite element model (FEM) module to determine a FEM that models an implanted electrode and a tissue medium in which the electrode is implanted;

a Fourier FEM solver module to calculate a potential distribution in the tissue medium using information from the FEM module and a capacitive component of at least one of the electrode and the tissue medium; and

a volume of activation (VOA) module to provide a predicted VOA using the potential distribution and a neuron model.

2. The system of claim 1, wherein the processor is configured to calculate, by the execution of the Fourier FEM solver module, the potential distribution in the tissue medium using information from the FEM module and the capacitive component of the electrode.

3. The system of claim 1 wherein the processor is configured to calculate, by the execution of the Fourier FEM solver module, the potential distribution in the tissue medium using information from the FEM module and the capacitive component of the tissue medium.

4. The system of claim 1, wherein the processor is configured to calculate, by the execution of the Fourier FEM solver module, the potential distribution in the tissue medium in both time and space.

5. The system of claim 1, wherein the processor is configured to interpolate, by the execution of the VOA module, the potential distribution onto a plurality of model axons.

6. The system of claim 1, wherein the processor is configured to predict, by the execution of the VOA module, a VOA using multiple stimulation waveforms.

7. The system of claim 1, wherein the processor is configured to execute an impedance module to calculate an impedance by dividing a stimulation voltage by an integrated current density along an active electrode contact;

and wherein the processor is configured to calculate, by the execution of the Fourier FEM solver module, a potential distribution using the calculated impedance.

8. A computer system comprising:

a processor configured to execute;

a finite element model (FEM) module 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 module to calculate a potential distribution in the tissue medium using information from the FEM module and a capacitive component of at least one of the electrode, the tissue medium, and the electrode-tissue interface; and

a volume of activation (VOA) module to provide a predicted VOA using the potential distribution and a neuron model.

9. The system of claim 8, wherein the processor is configured to calculate, by the execution of the Fourier FEM solver module, the potential distribution in the tissue medium using information from the FEM module and the capacitive component of the electrode-tissue interface.

10. The system of claim 9, wherein the electrode-tissue interface includes an encapsulation area around the electrode.

11. A non-transitory computer-readable storage medium, having stored thereon instructions executable by a processor, the instructions which, when executed by the processor, cause the processor to perform a method, the method comprising:

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; and

predicting a volume of activation (VOA) using the potential distribution and a neuron model.

12. A computer system comprising:

hardware means for;

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; and

predicting a volume of activation (VOA) using the potential distribution and a neuron model.

13. A computer-implemented method comprising:

determining, by a computer processor, a finite element model (FEM) of an implanted electrode and a tissue medium in which the electrode is implanted;

calculating, by the processor, 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; and

predicting, by the processor, a volume of activation (VOA) using the potential distribution and a neuron model.

14. The method of claim 13, wherein the calculating the potential distribution in the tissue medium includes using the Fourier FEM solver and the capacitive component of the electrode.

15. The method of claim 13, wherein the calculating the potential distribution in the tissue medium includes using the Fourier FEM solver and the capacitive component of the tissue medium.

16. The method of claim 13, wherein the calculating the potential distribution in the tissue medium includes calculating the potential distribution in the tissue medium in both time and space.

17. The method of claim 13, wherein the using the potential distribution and the neuron model includes interpolating the potential distribution onto a plurality of model axons.

18. The method of claim 13, wherein the predicting the VOA includes using multiple stimulation waveforms.

19. The method of claim 13, further comprising:

calculating an impedance by dividing a stimulation voltage by an integrated current density along an active electrode contact, wherein the calculating the potential distribution includes using the calculated impedance.

20. A computer-implemented method comprising:

determining, by a computer processor, a finite element model (FEM) of an implanted electrode, a tissue medium in which the electrode is implanted, and an electrode-tissue interface;

calculating, by the processor, 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; and

predicting, by the processor, a volume of activation (VOA) using the potential distribution and a neuron model.

21. The method of claim 20, wherein the calculating the potential distribution in the tissue medium includes using the Fourier FEM solver and the capacitive component of the electrode-tissue interface.

22. The method of claim 21, wherein the using the capacitive component of the electrode-tissue interface includes using the capacitive component of an encapsulation layer around the electrode.

23. A computer system comprising:

a processor configured to execute;

a finite element model (FEM) module to determine a FEM that models an implanted electrode and a tissue medium in which the electrode is implanted;

a Fourier FEM solver module to calculate a potential distribution in the tissue medium using information from the FEM circuit and a capacitive component of the electrode and not of the tissue medium; and

a volume of activation (VOA) module to provide a predicted VOA using the potential distribution and a neuron model.

24. A computer system comprising:

a processor configured to execute;

a finite element model (FEM) module to determine a FEM that models an implanted electrode and a tissue medium in which the electrode is implanted;

a Fourier FEM solver module to calculate a potential distribution in the tissue medium using information from the FEM circuit and a capacitive component of the tissue medium and not the electrode; and

a volume of activation (VOA) module to provide a predicted VOA using the potential distribution and a neuron.