METHOD AND DEVICE FOR DETERMINING THE LOCATION OF AN ENDOSCOPE

• US 20120203067A1
• Filed: 01/31/2012
• Published: 08/09/2012
• Est. Priority Date: 02/04/2011
• Status: Abandoned Application

• Current Assignee: Penn State Research Foundation
• Original Assignee: Penn State Research Foundation
• Inventors: Higgins, William E., Gibbs, Jason D., Cornish, Duane C.
• Application Number:
  US13/362,123
• Publication Number:
  US 20120203067A1
• Time in Patent Office: Days
• US Class Current: 600/117
• CPC Class Codes: A61B 1/00006 of control signals
• CPC Class Codes: A61B 1/00133 Drive units for endoscopic tools inserted through or with the endoscope
• CPC Class Codes: A61B 1/2676 Bronchoscopes
• CPC Class Codes: A61B 2034/102 Modelling of surgical devices, implants or prosthesis
• CPC Class Codes: A61B 2034/2046 Tracking techniques
• CPC Class Codes: A61B 2034/2061 using shape-sensors, e.g. fiber shape sensors with Bragg gratings
• CPC Class Codes: A61B 2090/062 penetration depth
• CPC Class Codes: A61B 34/20 Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• CPC Class Codes: A61B 5/066 Superposing sensor position on an image of the patient, e.g. obtained by ultrasound or x-ray imaging
• CPC Class Codes: A61B 6/12 Arrangements for detecting or locating foreign bodies
• CPC Class Codes: A61B 6/5247 combining images from an ionising-radiation diagnostic technique and a non-ionising radiation diagnostic technique, e.g. X-ray and ultrasound
• CPC Class Codes: G06F 18/251 of input or preprocessed data
• CPC Class Codes: G06V 10/803 of input or preprocessed data
• CPC Class Codes: G06V 20/647 by matching two-dimensional images to three-dimensional objects
• CPC Class Codes: G06V 20/653 by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces

Abstract

A technician-free strategy enables real-time guidance of bronchoscopy. The approach uses measurements of the bronchoscope'"'"'s movement to predict its position in 3D virtual space. To achieve this, a bronchoscope model, defining the device'"'"'s shape in the airway tree to a given point p, provides an insertion depth to p. In real time, the invention compares an observed bronchoscope insertion depth and roll angle, measured by an optical sensor, to precalculated insertion depths along a predefined route in the virtual airway tree to predict a bronchoscope'"'"'s location and orientation.

Claims

1. A method of determining the location of an endoscope within a body lumen, comprising the steps of:

precomputing a virtual model of an endoscope that approximates insertion depths at a plurality of view sites along a predefined path to a region of interest (ROI);

providing an endoscope with a device operative to observe actual insertion depths during a live procedure;

comparing, in real time, the observed insertion depths to the precomputed insertion depths at each view site along the predefined path;

predicting the location of the endoscope relative to the virtual model at each view site by selecting the view site with the precomputed insertion depth that is closest to the observed insertion depth; and

generating an endoluminal rendering providing navigational instructions based upon the predicted locations.

2. The method of claim 1, wherein:

the lumen forms part of an airway tree; and

the endoscope is a bronchoscope.

3. The method of claim 1, wherein:

the device is operative to observe roll angle in addition to insertion depth; and

the observed roll angle is used to rotate the default viewing direction at a selected view site.

4. The method of claim 1, including the step of using the method of Gibbs et al. to predetermine the optimal path leading to an ROI.

5. The method of claim 1, including the step of displaying the rendered predicted locations and actual view sites from the device.

6. The method of claim 1, wherein the virtual model is a MDCT image-based shape model.

7. The method of claim 1, wherein the step of precomputing allows for an inverse lookup of the predicted locations.

8. The method of claim 1, including the step of calculating separate insertion depths to each view site along the medial axes of the lumen.

9. The method of claim 1, including the step of approximating the endoscope as a series of line segments.

10. The method of claim 1, wherein the lumen is defined using voxel locations, the method including the step of calculating separate insertion depths to any voxel location within the lumen.

11. The method of claim 1, wherein the lumen is defined using voxel locations, the method including the step of approximating the shape of the endoscope to any voxel location within the lumen.

12. The method of claim 8, wherein the insertion depth to each view site is calculated by summing distances along the lumen medial axes.

13. The method of claim 10, wherein the insertion depth to each voxel location within the lumen is calculated by finding the shortest distance from a root voxel location to every voxel location within the lumen using Dijkstra'"'"'s algorithm.

14. The method of claim 10, wherein the insertion depth to each voxel location within the lumen is calculated by using a dynamic programming algorithm.

15. The method of claim 9, wherein the shape of the endoscope is approximated using the lumen medial axes.

16. The method of claim 11, wherein the shape of the endoscope to any voxel location is approximated using Dijkstra'"'"'s algorithm.

17. The method of claim 11, wherein the shape of the endoscope to any voxel location is approximated using a dynamic programming algorithm.

18. The method of claim 16, wherein the edge weight used in Dijkstra'"'"'s algorithm is determined using a dot product and the Euclidean distance between voxel locations within the lumen.

19. The method of claim 14, wherein the dynamic programming function includes an optimization function, and the optimization function is based on the dot product between voxel locations within the lumen.

20. The method of claim 1, wherein the device is an optical sensor.

24. The method of claim 21, wherein the method used for tracking applies the method of claim 1 to possible candidate branches based on the endoscopic insertion depth.

25. The method of claim 24, including the steps of:

registering candidate virtual bronchoscopic (VB) views to the endoscopic video; and

comparing the registered views to the endoscopic video using an image similarity metric.

26. The method of claim 25, wherein the registration of VB views to endoscopic video uses the method of Merritt et al.

27. The method of claim 25, wherein the image similarity metric is normalized sum-of-squared error.

28. The method of claim 24, including the step of creating a probability indicating if a candidate view was generated from the same location and orientation as the real bronchoscope.

29. The method of claim 28, including the step of combining multiple probabilities to make a final decision regarding which branch the endoscope actually entered.

21. A method for guiding an endoscope within a body lumen, comprising the steps of:

computing the optimal route leading to a region of interest (ROI);

tracking the tip of the endoscope;

generating an endoluminal rendering providing navigational instructions based upon the tracked locations; and

instructing a user to retract the endoscope if the endoluminal rendering indicates that the user is off the optimal route.

22. The method of claim 21, wherein:

the lumen forms part of an airway tree; and

the endoscope is a bronchoscope.

23. The method of claim 21, wherein the optimal route leading to the ROI is computed using the method of Gibbs et al.

30. The method of claim 21, including the step of displaying a view from the endoscope'"'"'s tracked location and orientation that is fused with guidance information indicating if the endoscope operator is on the correct route to the ROI.

31. The method of claim 21, including the step of instructing a user to retract the endoscope if the endoscope goes off of the optimal route.