BRAIN STIMULATION MODELS, SYSTEMS, DEVICES, AND METHODS

• US 20110196253A1
• Filed: 04/15/2011
• Published: 08/11/2011
• Est. Priority Date: 07/07/2004
• Status: Active Grant

• Current Assignee: Cleveland Clinic Foundation
• Original Assignee: Cleveland Clinic Foundation
• Inventors: HENDERSON, Jaimie M., HALL, John D., BUTSON, Christopher R., MCINTYRE, Cameron C.
• Granted Patent: US 9,135,400 B2
• Time in Patent Office: Days
• US Class Current: 600/547
• CPC Class Codes: A61B 2090/364 Correlation of different images or relation of image positions in respect to the body
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 90/37 Surgical systems with images on a monitor during operation
• CPC Class Codes: A61N 1/0529 Electrodes for brain stimulation
• CPC Class Codes: A61N 1/0531 Brain cortex electrodes
• CPC Class Codes: A61N 1/0534 Electrodes for deep brain stimulation
• CPC Class Codes: A61N 1/0539 Anchoring of brain electrode systems, e.g. within burr hole
• CPC Class Codes: A61N 1/36082 Cognitive or psychiatric applications, e.g. dementia or Alzheimer's disease
• CPC Class Codes: A61N 1/36135 using physiological parameters
• CPC Class Codes: A61N 1/36146 specified by the stimulation parameters
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

This document discusses, among other things, brain stimulation models, systems, devices, and methods, such as for deep brain stimulation (DBS) or other electrical stimulation. In an example, a target volume of activation (VOA) can be received, a test VOA can be simulated, and at least one of a target electrode location or parameter can be provide using a relationship between the target VOA and the test VOA.

Claims

1. A method for displaying a volume of influence by an electrode inserted in neural tissue of a patient, comprising:

receiving a target volume of influence;

calculating a predicted volume of influence, wherein the predicted volume of influence is a prediction of the amount of neural tissue that will be activated by the electrode;

displaying the target volume of influence and the predicted volume of influence on a display screen.

2. The method of claim 1, further comprising displaying anatomical features on the display screen.

3. The method of claim 1, further comprising displaying a representation of the electrode on the display screen.

4. The method of claim 1, further comprising configuring a mathematical model of the electrode inserted inside the neural tissue, wherein the mathematical model comprises a parameter representing a tissue conductivity characteristic of the neural tissue.

5. The method of claim 4, wherein calculating the predicted volume of influence comprises:

solving the mathematical model to calculate the second derivative or an approximation of the second derivative of the electrical potential produced by the electrode under a set of electrode stimulation conditions within the neural tissue; and

determining the predicted volume of influence using the second derivative or approximation of the second derivative of the electrical potential.

6. The method of claim 5, wherein the step of determining the predicted volume of influence comprises comparing the second derivative or approximation of the second derivative to a threshold value that represents activation of neurons in the neural tissue.

7. The method of claim 6, wherein the threshold value is obtained from the application of the set of electrode stimulation conditions to pre-determined threshold criteria.

8. The method of claim 7, wherein the pre-determined threshold criteria are determined from the application of different electrode stimulation conditions to one or more neuron models that represent the neuron activation mechanism in the neural tissue.

9. The method of claim 5, wherein the electrode stimulation conditions include one or more of electrode stimulation parameters, electrode position, or electrode configuration.

10. The method of claim 7, further comprising:

solving the mathematical model to calculate the electrical field produced by the electrode;

having a neuron model to represent the neuron activation mechanism in the neural tissue;

placing the neuron model in the calculated electrical field; and

determining the threshold value for the second derivative or approximation of the second derivative of the electrical potential for the activation of neurons in the neuron model.

11. The method of claim 4, wherein the mathematical model is a finite element analysis (FEA) model of the electrode inside the neural tissue.

12. The method of claim 5, wherein the mathematical model is solved by calculating the second difference of the electrical potential along one or more directions.

13. The method of claim 5, further comprising:

repeatedly solving the mathematical model using different electrode stimulation conditions to obtain multiple predicted volumes of influence as test volumes of influence; and

comparing the multiple test volumes of influence to the target volume of tissue to be influenced.

14. The method of claim 4, wherein the mathematical model further comprises a representation of an encapsulation tissue around the electrode.

15. The method of claim 1, wherein the neural tissue is represented as having a constant tissue conductivity.

16. The method of claim 4, wherein the tissue conductivity characteristic is electrical conductivity of the neural tissue.

17. The method of claim 13, wherein the electrode simulation conditions include one or more of electrode position, electrode configuration, or electrode stimulation parameters.

18. The method of claim 13, further comprising selecting a particular electrode stimulation condition based on the comparison of the multiple test volumes of influence to the target volume of tissue to be influenced.

19. The method of claim 1, wherein the mathematical model further comprises a representation of an encapsulation tissue around the electrode.

20. A non-transitory computer-readable storage medium comprising instructions for:

receiving a target volume of influence;

calculating a predicted volume of influence, wherein the predicted volume of influence is a prediction of the amount of neural tissue that will be activated by the electrode; and

displaying the target volume of influence and the predicted volume of influence on a display screen.

21. A computer system having a display screen, the computer system programmed to perform steps that comprise:

receiving a target volume of influence;

calculating a predicted volume of influence, wherein the predicted volume of influence is a prediction of the amount of neural tissue that will be activated by the electrode;

displaying the target volume of influence and the predicted volume of influence on the display screen.