VOA generation system and method using a fiber specific analysis

• US 9,254,387 B2
• Filed: 08/09/2012
• Issued: 02/09/2016
• Est. Priority Date: 08/09/2011
• Status: Active Grant

• Current Assignee: Boston Scientific Neuromodulation Corporation (Boston Scientific Corporation)
• Original Assignee: Boston Scientific Neuromodulation Corporation (Boston Scientific Corporation)
• Inventors: Blum, David Arthur, Moffitt, Michael A., Steinke, Karl
• Primary Examiner(s): DIETRICH, JOSEPH M
• Application Number:
  US13/507,962
• Publication Number:
  US 20130116744A1
• Time in Patent Office: 1,279 Days
• Field of Search: 607/45, 607/46
• US Class Current: 1/1
• CPC Class Codes: A61N 1/0534 Electrodes for deep brain stimulation
• CPC Class Codes: A61N 1/36082 Cognitive or psychiatric applications, e.g. dementia or Alzheimer's disease
• CPC Class Codes: A61N 1/36185 Selection of the electrode configuration
• CPC Class Codes: A61N 1/37247 User interfaces, e.g. input or presentation means

Abstract

A system and method for generating an estimated volume of activation (VOA) corresponding to settings applied to a stimulation leadwire includes a processor performing the following: determining, for each of a plurality of neural elements, one or more respective parameters characterizing an electrical distribution along the neural element, looking up the one or more parameters for each of the neural elements in a look-up table (LUT), obtaining threshold values for each of the neural elements recorded in the LUT in association with the looked-up parameters, comparing, for each of the neural elements, a value of the leadwire settings to each of the respective threshold value, estimating based on the comparisons which of the neural elements would be activated by the settings, and generating a structure corresponding to a region including the neural elements estimated to be activated.

Claims

1. A computer system for generating an estimated volume of activation (VOA), the system comprising:

a computer processor configured to;

for each of a plurality of neural elements that are in a vicinity of a leadwire;

determine a parameter that characterizes the respective neural element;

based on the determined parameter, select one or more of a plurality of parameters that are each stored in association with a respective threshold activation value;

based on the selected one or more of the plurality of stored parameters and the associated one or more respective threshold activation values, set a respective threshold activation value of the respective neural element, wherein the respective neural element becomes activated at the respective threshold activation value and is not activated below the respective threshold activation value; and

determine whether a user-input stimulation value to be applied to the leadwire meets the respective threshold activation value set for the respective neural element; and

generate a surface structure corresponding to those of the neural elements whose respective threshold activation values have been determined to be met by the user-input stimulation value.

2. The system of claim 1, wherein the leadwire is arranged to provide an anodic stimulation.

3. The system of claim 1, wherein the selection of the one or more of the plurality of parameters includes matching the parameter to the one or more of the a plurality of stored parameters.

4. The system of claim 3, wherein the processor is configured to match the parameter characterizing the respective neural element to different ones of the plurality of parameters depending on whether the respective neural element is associated with a cathodic or anodic stimulation.

5. The system of claim 3, wherein the processor is configured to match the parameter characterizing the respective neural element to different ones of the plurality of parameters depending, on whether the leadwire is arranged to provide a cathodic or anodic stimulation.

6. The system of claim 1, wherein the characterization is of an electrical environment of the respective neural element.

7. The system of claim 3 wherein the matching performed for the respective threshold activation value includes finding one of the plurality of stored parameters that is an exact match to the parameter determined for the respective neural element, and the parameter stored in association with the matched one of the plurality of stored parameters is selected as the respective threshold value of the respective neural element.

8. The system of claim 1, wherein, where an exact match to the respectively determined parameter of the respective neural element is not found among the plurality of stored parameters:

the processor is configured to select the one or more of the plurality of parameters as a nearest match; and

the determination of the respective threshold activation value includes obtaining a modification of the one or more threshold activation values stored in association with the one or more of the plurality of parameters.

9. The system of claim 8, wherein, where an exact match to the respectively determined parameter of the respective neural element is not found among the plurality of stored parameters:

the one or more of the plurality of parameters includes at least two parameters, and the determination of the respective threshold activation value includes interpolating the at least two threshold activation values stored in association with the at least two parameters.

10. The system of claim 8, wherein, where an exact match to the respectively determined parameter of the respective neural element is not found among the plurality of stored parameters:

the one or more of the plurality of parameters includes at least two parameters, and the determination of the respective threshold activation value includes extrapolating from the at least two threshold activation values stored in association with the at least two parameters.

11. The system of claim 1, wherein the parameter characterizes an electrical distribution along the respective neural element.

12. The system of claim 11. wherein the electrical distribution is modeled according to the user-input stimulation value.

13. The system of claim 12, wherein:

the leadwire includes a plurality of electrodes;

the user-input stimulation value includes a respective stimulation value for multiple ones of the plurality of electrodes; and

the processor is configured to normalize the user-input stimulation values according to a condition that a sum of the user-input stimulations values equals a predetermined normalization value.

14. The system of claim 13, wherein the normalization value is 1.

15. The system of claim 11, wherein the parameter includes a peak voltage and peak value of a second difference of the voltages along the respective neural element.

16. The system of claim 1, wherein the leadwire includes a plurality of electrodes, the user-input stimulation value includes equal values for electrodes at each of a first side and a second side of the leadwire, the plurality of neural elements for which the determinations are performed are selectively neural elements at the first side of the leadwire, and the processor is configured to generate a reflection of the surface structure.

17. The system of claim 1, wherein the user-input stimulation value includes one of a current amplitude and a voltage amplitude.

18. The system of claim 1, wherein the user-input stimulation value includes a respective distinct stimulation value for each of a plurality of contacts of the leadwire.

19. The system of claim 18, wherein the respective distinct stimulation values include current values.

20. The system of claim 1, wherein the leadwire is configured to provide one of a deep brain stimulation (DBS) therapy, a spinal cord stimulation (SCS) therapy, an Occipital NS therapy, a Trigemenal NS therapy, a peripheral field stimulation therapy, and a sacral root stimulation therapy.

21. The system of claim 1 wherein the determined parameter does not exactly match the selected one or more of the plurality of stored parameters, and the selection of the one or more of the plurality of stored parameters is based on a proximity of values between the determined parameter and the selected one or more parameters.

22. The system of claim 21, further comprising:

initially performing modeling for storing a first set of the plurality of characterization parameters and associated threshold values, and subsequently extrapolating a second set of the plurality of characterization parameters and associated threshold values based on the first set.

23. The system of claim 22, further comprising interpolating a third set of the plurality of characterization parameters and associated threshold values based on at least one of the first set and the second set.

25. The system of claim 1, wherein:

the processor is configured to;

perform modeling for storing a first set of the stored a plurality of characterization parameters and associated threshold values; and

perform extrapolation and interpolation based on the first set of the plurality of characterization parameters and associated threshold values to obtain a second set of the plurality of characterization parameters and associated threshold values; and

the respective threshold activation value of the respective neural element is one of the stored threshold activation values which is stored in association with one of the stored plurality of characterization parameters to which the determined parameter characterizing the respective neural is a match.

26. The system of claim 1, wherein:

the processor is configured to;

perform modeling for storing a first set of the stored a plurality of characterization parameters and associated threshold values; and

perform extrapolation based on the first set of the plurality of characterization parameters and associated threshold values to obtain a second set of the plurality of characterization parameters and associated threshold values; and

the respective threshold activation value of the respective neural element is obtained by interpolating the plurality of characterization parameters and associated threshold values to obtain a match to the determined parameter characterizing the respective neural element and a respective associated characterization parameter.

24. The system of 22, wherein:

the selected one or more of the plurality of parameters includes a plurality of characterization parameters to which the determined parameter characterization of the respective neural element is not an exact match; and

the respective threshold activation value of the respective neural element is determined by interpolating the selected plurality of parameters.

27. A computer system for generating an estimated volume of activation (VOA), the system comprising:

a computer processor configured to;

for each of a plurality of neural elements that are in a vicinity of a leadwire;

determine a respective threshold activation value, wherein the respective neural element becomes activated at the respective threshold activation value and is not activated below the respective threshold activation value; and

determine whether a user-input stimulation value to be applied to the leadwire meets the respective threshold activation value of the respective neural element; and

generate a surface structure corresponding to those of the neural elements whose respective threshold activation values have been determined to be met by the user-input stimulation value;

wherein one of;

(A) the processor is configured to select a first grid that is of a first size based on the user-input stimulation value, the determination of whether the user-input stimulation value meets the respective threshold is initially performed for neural elements positioned at a perimeter of the selected first grid, and, in response to a determination that the user-input stimulation value meets the respective threshold activation value of one of the neural elements positioned at the perimeter of the selected value, the processor is configured to select a second grid of a second size that is larger than the first size; and

(B) the processor is configured to selectively apply a marching cubes algorithm to only each pair of adjacent ones of the plurality of neural elements that includes one neural element whose respective threshold activation value is met by the user-input stimulation value and one neural element whose respective threshold activation value is not met by the user-input stimulation value, and the generation of the surface structure is based in part on a result of the applied marching cubes algorithm.

28. The system of claim 27, wherein:

the processor is configured to selectively apply the marching cubes algorithm to only each pair of adjacent ones of the plurality of neural elements that includes one neural element whose respective threshold activation value is met by the user-input stimulation value and one neural element whose respective threshold activation value is not met by the user-input stimulation value; and

the generation of the surface structure is based in part on the result of the applied marching cubes algorithm.

29. The system of claim 27, wherein the processor is configured to select the first grid that is of the first size based on the user-input stimulation value, the determination of whether the user-input stimulation value meets the respective threshold is initially performed for the neural elements positioned at the perimeter of the selected first grid, and, in response to the determination that the user-input stimulation value meets the respective threshold activation value of one of the neural elements positioned at the perimeter of the selected value, the processor is configured to select the second grid of the second size that is larger than the first size.

30. A computer system for generating an estimated volume of activation (VOA), the system comprising:

a computer processor configured to;

for each of a plurality of neural elements that are in a vicinity of a leadwire;

determine a respective threshold activation value, wherein the respective neural element becomes activated at the respective threshold activation value and is not activated below the respective threshold activation value; and

determine whether a user-input stimulation value to be applied to the leadwire meets the respective threshold activation value of the respective neural element; and

generate a surface structure corresponding to those of the neural elements whose respective threshold activation values have been determined to be met by the user-input stimulation value;

wherein, for each of the plurality of neural elements, the determination of the respective threshold value includes;

determining at least one respective parameter that characterizes at least one of a spread and a height of a distribution of electrical values along the respective neural element; and

obtaining the respective threshold value based on the respective determined parameter.

31. The system of claim 30, wherein the determined at least one respective parameter characterizes the spread and the height of the a distribution of electrical values along the respective neural element.

32. The system of claim 31, wherein the obtaining of the respective threshold value includes looking up a value of the at least one respective parameter in a look-up table that pairs each of a plurality of values for the at least one respective parameter with a respective threshold value.

33. The system of claim 31, wherein the at least one parameter includes a combination of two parameters.

34. The system of claim 31, wherein the at least one parameter includes a peak of all voltage values along the respective neural element and a peak of all second difference voltage values along the respective neural element.

35. The system of claim 31, wherein the determined at least one peak is the peak one of voltage levels along the respective neural element.

36. The system of claim 35, wherein the obtaining of the respective threshold value includes looking up the determined peak voltage level in a look-up table that pairs each of a plurality of voltage levels with one or more respective threshold values.

37. The system of claim 31, wherein the determined at least one peak is peak one of second difference voltage values along the respective neural.

38. The system of claim 37, wherein the obtaining of the respective threshold value includes looking up the determined peak second difference voltage value in a look-up table that pairs each of a plurality of voltage levels with one or more respective threshold values.

39. The system of claim 30, wherein the determined at least one respective parameter characterizes the spread of the distribution of electrical values along the respective neural element.