Systems and methods for pre-operative modeling

• US 10,373,719 B2
• Filed: 09/03/2015
• Issued: 08/06/2019
• Est. Priority Date: 09/10/2014
• Status: Active Grant

• Current Assignee: Intuitive Surgical Operations, Inc. (Intuitive Surgical Holdings, LLC)
• Original Assignee: Intuitive Surgical Operations, Inc. (Intuitive Surgical Holdings, LLC)
• Inventors: Soper, Timothy D., Zhao, Tao, Donhowe, Caitlin Q., Duindam, Vincent, Barbagli, Federico
• Primary Examiner(s): Wu, Xiao M
• Assistant Examiner(s): Elbinger, Steven Z
• Application Number:
  US14/845,031
• Publication Number:
  US 20160070878A1
• Time in Patent Office: 1,433 Days
• Field of Search: None
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/252 indicating steps of a surgical procedure
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A method for modeling a patient anatomy includes applying a first modeling function to a set of volumetric image data for a patient anatomy to produce a first model of the patient anatomy, presenting the first model to a user, receiving an input from the user, and generating a revised model based upon the input.

Claims

1. A computing system comprising:

a user interface;

a processor; and

a memory comprising machine readable instructions that when executed by the processor, cause the system to;

through the user interface, present a patient-specific model of a patient anatomy to a user, the patient-specific model being formed by applying a first segmentation function to a set of volumetric image data for the patient anatomy to produce the patient-specific model of the patient anatomy;

through the user interface, receive an input from the user;

generate a revised model by applying an adjusted segmentation function to the set of volumetric image data, the adjusted segmentation function based upon the input; and

present the revised model to the user,

wherein the patient-specific model is associated with a plurality of patient-specific model parameters, wherein the plurality of patient-specific model parameters includes a leak rate, the leak rate being a measurement of additional passageways within the patient-specific model that do not correspond to actual passageways within the patient anatomy.

2. The system of claim 1 wherein the plurality of patient-specific model parameters includes a center line composite length.

3. The system of claim 1 wherein the plurality of patient-specific model parameters includes a quantity of voxels in the patient-specific model.

4. The system of claim 1 wherein the plurality of patient-specific model parameters includes a quantity of branches in the patient-specific model.

5. The system of claim 1 wherein the input received from the user includes additional voxels representing additional features of the patient anatomy.

6. The system of claim 1 wherein the input received from the user includes a seed location and to generate the revised model, the processor is further to cause the system to apply a second segmentation function to the set of volumetric image data in a region of the seed location.

7. The system of claim 1 wherein the input received from the user includes a tunable parameter for at least a portion of the patient-specific model and to generate the revised model, the processor is further to cause the system to reapply the first segmentation function with different parameters.

8. The system of claim 1 wherein the input received from the user includes identification of a route to a target region.

9. The system of claim 8 wherein the input received from the user includes identification of vasculature proximate to the route to the target region.

10. The system of claim 1 wherein the input received from the user includes a threshold voxel intensity value and to generate the revised model, the processor is further to cause the system to omit voxels with a voxel intensity less than the threshold voxel intensity value.

11. The system of claim 1, wherein the processor is further to cause the system to:

apply a plurality of segmentation functions to the set of volumetric image data for the patient anatomy to produce a plurality of models of the patient anatomy, wherein the first segmentation function is one of the plurality of segmentation functions and the patient-specific model is one of the plurality of models; and

present the plurality of models to the user.

12. The system of claim 11, wherein the input received from the user is an evaluation of the plurality of models.

13. The system of claim 12, wherein generating the revised model includes combining sub-portions of at least two of the plurality of models.

14. The system of claim 13 wherein the input received from the user includes identification of the sub-portions of the at least two of the plurality of models.

15. The system of claim 13, wherein the sub-portions of the models are mixed based on at least one of:

a selected airway link or airway links connected to the selected link.

16. The system of claim 12 wherein to apply the plurality of segmentation functions to the set of volumetric data for the patient anatomy, the processor is further to cause the system to generate a set of intermediate modeling data for each of the plurality of segmentation functions and generating the revised model includes applying the input to the intermediate modeling data.

17. The system of claim 16 wherein the intermediate modeling data is associated with a subset of the set of volumetric image data.

18. The system of claim 1, wherein the patient-specific model includes a plurality of regions, each region having a probabilistic value indicating a probability that that region is a passageway in the patient anatomy.