IP Library Granted Patent US 12,257,096
Granted Patent B2
US 12,257,096 · App. 17/894,589 · Granted Mar 25, 2025

Patient-specific infusion coverage estimates using segmented 3D brain representations

Inventors: Lyubomir Zagorchev (Burlington, MA); Damon Hyde (Somerville, MA); Chen Li (Plainfield, OH)
Assignee: ClearPoint Neuro, Inc.
A61B6/541A61B34/20A61B2034/2051
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Quick Facts
Patent No.
US 12,257,096
App. No.
17/894,589
Granted
Mar 25, 2025
Kind
B2
Abstract

Systems and methods provide automated systems for accurately estimating infusion coverage within a target brain region in real-time (or approximately real-time) during surgical procedures. Such accurate and real-time infusion coverage estimation enables intraoperative monitoring and adjustment of infusion parameters (e.g., cannula tip location, infusate delivery flow rate, etc.) for achieving optimal/improved infusion coverage for a given drug therapy. Accordingly, examples of the presently disclosed technology can improve the efficacy and safety of drug therapies delivered to the brain.

Claims (50)

1. A method, comprising:

subtracting a first 3D image of a patient's brain acquired before infusate has been delivered to the patient's brain from a second 3D image of the patient's brain acquired after infusate has been delivered to the patient's brain;

based on the subtraction, generating a 3D infusate delivery representation, the 3D infusate delivery representation volumetrically representing the delivered infusate within the patient's brain;

comparing the 3D infusate delivery representation to a segmented 3D representation of the patient's brain, wherein the segmented 3D representation of the patient's brain comprises a 3D target brain region sub-representation representing a target brain region of the patient;

based on the comparison, estimating a level of coverage for delivered infusate within the target brain region; and

providing a notification related to the estimated level of coverage for delivered infusate within the target brain region.

2. The method of claim 1 , wherein comparing the 3D infusate delivery representation to the segmented 3D representation of the patient's brain comprises overlaying the 3D infusate delivery representation and the segmented 3D representation of the patient's brain.

3. The method of claim 2 , wherein estimating the level of coverage for delivered infusate within the target brain region comprises:

estimating a volume for delivered infusate within the target brain region based on an amount of overlap between the 3D infusate delivery representation and the 3D target brain region sub-representation after the 3D infusate delivery representation and the segmented 3D representation of the patient's brain have been overlaid;

estimating a volume of the target brain region based on the 3D target brain region sub-representation; and

estimating the level of coverage for delivered infusate within the target brain region by comparing the estimated volume for delivered infusate within the target brain region to the estimated volume for the target brain region.

4. The method of claim 3 , wherein estimating the volume for delivered infusate within the target brain region based on the amount of overlap between the 3D infusate delivery representation and the 3D target brain region sub-representation comprises counting a number of voxels shared by the 3D infusate delivery representation and the 3D target brain region sub-representation after the 3D infusate delivery representation and the segmented 3D representation of the patient's brain have been overlaid.

5. The method of claim 3 , wherein estimating the volume of the target brain region comprises counting a number of voxels that comprise the 3D target brain region sub-representation.

6. The method of claim 1 , wherein the first 3D image of the patient's brain and second image 3D of the patient's brain are acquired using the same image sequence parameters and image geometry.

7. The method of claim 1 , further comprising, prior to subtracting the first 3D image of the patient's brain from the second 3D image of the patient's brain, aligning the second 3D image of the patient's brain with the first 3D image of the patient's brain to account for a change in position of the patient between acquisition of the first 3D image of the patient's brain and acquisition of the second 3D image of the patient's brain.

8. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising:

subtracting a first 3D image of a patient's brain acquired before infusate has been delivered to the patient's brain from a second 3D image of the patient's brain acquired after infusate has been delivered to the patient's brain;

based on the subtraction, generating a 3D infusate delivery representation, the 3D infusate delivery representation volumetrically representing the delivered infusate within the patient's brain;

comparing the 3D infusate delivery representation to a segmented 3D representation of the patient's brain, wherein the segmented 3D representation of the patient's brain comprises a 3D target brain region sub-representation representing a target brain region of the patient;

based on the comparison, estimating a volume of delivered infusate located outside of the target brain region; and

providing a notification related to the estimated volume of delivered infusate located outside of the target brain region.

9. The non-transitory computer-readable medium of claim 8 , wherein the method further comprises:

based on the comparison, estimating a level of coverage for delivered infusate within the target brain region; and

providing a notification related to the estimated level of coverage for delivered infusate within the target brain region.

10. The non-transitory computer-readable medium of claim 8 , wherein comparing the 3D infusate delivery representation to the segmented 3D representation of the patient's brain comprises overlaying the 3D infusate delivery representation and the segmented 3D representation of the patient's brain.

11. The non-transitory computer-readable medium of claim 10 , wherein estimating the level of coverage for delivered infusate within the target brain region comprises:

estimating a volume for delivered infusate within the target brain region based on an amount of overlap between the 3D infusate delivery representation and the 3D target brain region sub-representation after the 3D infusate delivery representation and the segmented 3D representation of the patient's brain have been overlaid;

estimating a volume of the target brain region based on the 3D target brain region sub-representation; and

estimating the level of coverage for delivered infusate within the target brain region by comparing the estimated volume for delivered infusate within the target brain region to the estimated volume for the target brain region.

12. The non-transitory computer-readable medium of claim 11 , wherein estimating the volume for delivered infusate within the target brain region based on the amount of overlap between the 3D infusate delivery representation and the 3D target brain region sub-representation comprises counting a number of voxels shared by the 3D infusate delivery representation and the 3D target brain region sub-representation after the 3D infusate delivery representation and the segmented 3D representation of the patient's brain have been overlaid.

13. The non-transitory computer-readable medium of claim 10 , wherein estimating the volume of delivered infusate located outside of the target brain region comprises estimating the volume of delivered infusate located outside of the target brain region based on an amount of overlap between the 3D infusate delivery representation and the 3D target brain region sub-representation after the 3D infusate delivery representation and the segmented 3D representation of the patient's brain have been overlaid.

14. The non-transitory computer-readable medium of claim 13 , wherein estimating the volume for delivered infusate located outside of the target brain region based on the amount of overlap between the 3D infusate delivery representation and the 3D target brain region sub-representation comprises counting a number of voxels of the 3D infusate delivery representation that are not shared with the 3D target brain region sub-representation after the 3D infusate delivery representation and the segmented 3D representation of the patient's brain have been overlaid.

15. The non-transitory computer-readable medium of claim 8 , wherein the 3D target brain region sub-representation comprises a 3D closed mesh boundary surface.

16. A system comprising:

one or more processing resources; and

a non-transitory computer-readable medium, coupled to the one or more processing resources, having stored therein instructions that when executed by the one or more processing resources cause the system to:

compare a first 3D image of a patient's brain acquired before infusate has been delivered to the patient's brain to a second 3D image of the patient's brain acquired after infusate has been delivered to the patient's brain;

based on the image comparison, generate a 3D infusate delivery representation, the 3D infusate delivery representation volumetrically representing the delivered infusate within the patient's brain;

overlay the 3D infusate delivery representation and the segmented 3D representation of the patient's brain, wherein:

the segmented 3D representation of the patient's brain comprises one or more 3D sub-representations, a given 3D sub-representation representing a given brain region of the patient, and

one of the one or more 3D sub-representations comprises a 3D target brain region sub-representation representing a target brain region of the patient;

based on the overlaid 3D infusate delivery representation and segmented 3D representation of the patient's brain, estimate a level of coverage for delivered infusate within the target brain region; and

provide a notification related to the estimated level of coverage for delivered infusate within the target brain region.

17. The system of claim 16 , wherein the image comparison comprises subtracting the first 3D image of the patient's brain from the second 3D image of the patient's brain.

18. The system of claim 16 , wherein the first 3D image of the patient's brain and the second 3D image of the patient's brain are acquired using the same image sequence parameters and image geometry.

19. The system of claim 16 , wherein estimating the level of coverage for delivered infusate within the target brain region comprises:

estimating a volume for delivered infusate within the target brain region based on an amount of overlap between the 3D infusate delivery representation and the 3D target brain region sub-representation after the 3D infusate delivery representation and the segmented 3D representation of the patient's brain have been overlaid;

estimating a volume of the target brain region based on the 3D target brain region sub-representation; and

estimating the level of coverage for delivered infusate within the target brain region by comparing the estimated volume for delivered infusate within the target brain region to the estimated volume for the target brain region.

20. The system of claim 16 , wherein the segmented 3D representation of the patient's brain comprises a 3D mesh representation and the 3D target brain region sub-representation comprises a 3D closed mesh boundary surface.

Assignments (2)
SECURITY INTEREST Recorded May 13, 2025
From: CLEARPOINT NEURO, INC.
To: CALW SA LLC, AS PURCHASER AGENT
Reel/Frame 071276/0191 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 26, 2022
From: ZAGORCHEV, LYUBOMIR; HYDE, DAMON; LI, CHEN
To: CLEARPOINT NEURO, INC.
Reel/Frame 060916/0168 →