Granted Patent B2

US 12,201,410 · App. 17/646,856 · Granted Jan 21, 2025

Inventors: Nolan Williams (Half Moon Bay, CA); Keith Sudheimer (Stanford, CA)

Assignee: The Board of Trustees of the Leland Stanford Junior University

A61B5/02405A61B5/165A61B5/4836A61N2/004A61N2/006A61N2/02G01R33/4806G01R33/4808G01R33/565G16H20/30A61B5/681A61B2576/026G16H50/30

Abstract

Claims (38)

1. A method for generating a brain stimulation target, comprising:

obtaining image data of a patient's brain, where the image data describes neuronal activations within the patient's brain;

determining a brain stimulation target by:

mapping a stimulation region of interest in the patient's brain;

locating functional subregions within the stimulation region of interest based on the image data;

determining functional relationships between the functional subregions and a target region of interest deeper in the patient's brain than the stimulation region of interest;

generating parameters for each functional subregion;

generating a target quality score for each functional subregion based on the parameters, where the target quality score indicates surface influence on the target region of interest;

selecting a brain stimulation target based on the generated target quality scores and a neurological condition of the patient; and

applying neurostimulation using a neurostimulation device to the selected brain stimulation target in order to treat the neurological condition of the patient.

2. The method of claim 1 , wherein the image data describes neuronal activity during a resting state.

3. The method of claim 1 , wherein obtaining the image data further comprises preprocessing the image data.

4. The method of claim 3 , wherein preprocessing the image data comprises performing at least one preprocessing step selected from the group consisting of physiological noise regression, slice-time correction, motion correction, co-registration, band-pass filtering, and de-trending.

5. The method of claim 1 , wherein a brain atlas is used for mapping the stimulation region of interest onto a brain anatomy of the patient.

6. The method of claim 1 , wherein each functional subregion describes homogenous brain activity.

7. The method of claim 1 , wherein the functional subregions are identified and separated from each other using hierarchical agglomerative clustering.

8. The method of claim 1 , wherein the parameters for each functional subregion are selected from the group consisting of: size of the functional subregion, concentration of voxels that make up the functional subregion, correlation between the functional subregion and other functional subregions, and accessibility of the functional subregion to a transcranial magnetic stimulation device.

9. The method of claim 1 , wherein the target quality score reflects a combination of weighted parameters of each functional subregion, where a higher quality score reflects a better brain stimulation target.

10. The method of claim 9 , wherein the surface influence for a given functional subregion is calculated as a voxel number weighted combination of the Spearman correlation coefficients derived from a hierarchical clustering algorithm describing the correlation coefficients between the given functional subregion and the target region of interest.

11. The method of claim 1 , where the brain stimulation target is a transcranial magnetic stimulation target.

12. The method of claim 1 , wherein the neurostimulation is applied using an aTBS protocol.

13. A system for generating a brain stimulation target, comprising:

a target generation computing system comprising at least one processor and a memory containing a neuronavigation application, where the neuronavigation application directs the processor to:

obtain image data from an imaging device, where the image data describes neuronal activations within a patient's brain;

map a stimulation region of interest in the patient's brain;

locate functional subregions within the stimulation region of interest based on the image data;

determine functional relationships between the functional subregions and a target region of interest deeper in the patient's brain than the stimulation region of interest;

generate subregion parameters for each functional subregion;

generate a target quality score for each functional subregion based on the subregion parameters, where the target quality score indicates surface influence on the target region of interest; and

select a brain stimulation target based on the generated target quality scores and a neurological condition of the patient; and

a neurostimulation device configured to deliver neurostimulation at the selected brain stimulation target in order to treat the neurological condition of the patient.

14. The system of claim 13 , wherein the image data describes neuronal activity during a resting state.

15. The system of claim 13 , wherein the neuronavigation application further directs the processor to preprocess the image data.

16. The system of claim 15 , wherein to preprocess image data, the neuronavigation application further directs the processor to perform at least one preprocessing step selected from the group consisting of physiological noise regression, slice-time correction, motion correction, co-registration, band-pass filtering, and de-trending.

17. The system of claim 13 , wherein a brain atlas is used to map the stimulation region of interest.

18. The system of claim 13 , wherein each functional subregion describes homogenous brain activity.

19. The system of claim 13 , wherein the functional subregions are located using hierarchical agglomerative clustering.

20. The system of claim 13 , wherein the subregion parameters are selected from the group consisting of: size of the functional subregion, concentration of voxels that make up the functional subregion, correlation between the functional subregion and other functional subregions, and accessibility of the subregion from the surface of the brain.

Assignments (1)

Continuity (4)

References Cited (280)