Methods and systems for image-guided placement of implants

• US 20040240715A1
• Filed: 05/29/2003
• Published: 12/02/2004
• Est. Priority Date: 05/29/2003
• Status: Active Grant

• Current Assignee: Board of Regents of the University of Texas System (University of Texas System)
• Original Assignee: Board of Regents of the University of Texas System (University of Texas System)
• Inventors: Tedla, Buzuayehu, Wicker, Ryan B.
• Granted Patent: US 7,194,120 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: A61B 17/1735 for rasps or chisels
• CPC Class Codes: A61B 17/1757 for the spine
• CPC Class Codes: A61B 2017/564 Methods for bone or joint treatment
• CPC Class Codes: A61B 2090/364 Correlation of different images or relation of image positions in respect to the body
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80

Abstract

Methods and computer systems for determining the placement of an implant in a patient in need thereof comprising the step of analyzing intensity-based medical imaging data obtained from a patient, isolating an anatomic site of interest from the imaging data, determining anatomic spatial relationships with the use of an algorithm, wherein the algorithm is optionally automated.

Claims

1. A method for determining the placement of pedicle screws comprising the step of:

determining a trajectory for the placement of a pedicle screw in a patient with the use of an algorithm, wherein the trajectory is obtained from medical imaging data of the patient'"'"'s spine, wherein the algorithm is performed on a computer.

2. The method of claim 1, wherein the algorithm is implemented with a computer processor.

3. The method of claim 1 further comprising the step of determining the diameter of the pedicle screw.

4. The method of claim 1 further comprising the step of determining the depth for inserting the pedicle screw.

5. The method of claim 1, wherein the algorithm is used to analyze medical imaging data comprising an image of a patient'"'"'s spine.

6. The method of claim 5, wherein the medical imaging data are intensity-based imaging data.

7. The method of claim 5, wherein the medical imaging data are chosen from the group consisting of computed tomography data, positron emission tomography data, ultrasound data, and magnetic resonance imaging data.

8. The method of claim 5 further comprising the step of analyzing the imaging data to determine if the algorithm is compatible with the imaging data.

9. The method of claim 5, wherein the algorithm further comprises the steps of isolating the bony anatomy of the spine from the imaging data;

determining the minimum thickness of a spinal pedicle, the pedicle length, and orientation to the spine.

10. The method of claim 2, wherein the algorithm is automated.

11. A computer system determining pedicle screw placement comprising:

a processor receiving imaging data and using the data to calculate the optimum trajectory, depth and diameter of a pedicle screw path within the bony structure, wherein the imaging data comprises an image of a bony structure.

12. The system of claim 11, wherein the processor interpolates the imaging data, segments the interpolated data;

extracts the boundary of the bony structure from the interpolated data;

identifies the pedicle from the extracted boundary, calculates the minimum pedicle width, maximum depth and direction of the pedicle based on the coordinate system of the medical imaging.

13. The system of claim 12, wherein the system is automated.

14. A computer system for determining pedicle screw placement comprising:

a processor; and

a computer readable medium connected to the processor, wherein the readable media includes processor instructions configured to be read by the processor and thereby cause the processor to access a set of imaging data comprising one or more images of a bony structure and using the data to compute the optimum placement of a pedicle screw in the bony structure.

15. A computer system of claim 14, wherein the system is automated.

16. A method for determining the placement of an implant in a patient in need thereof comprising the step of:

analyzing intensity-based medical imaging data obtained from a patient;

isolating an anatomic site of interest from the imaging data; and

determining anatomic spatial relationships from the imaging data with the use of an algorithm to identify the placement of the implant.

17. The method of claim 16, wherein the algorithm further comprises the steps of determining the minimum thickness of the anatomic site, the length of the anatomic site, and orientation to the anatomic site relative to the rest of the body.

18. The method of claim 16 further comprising the step of determining the diameter of the implant.

19. The method of claim 16 further comprising the step of determining the depth for inserting the implant.

20. The method of claim 16, wherein the intensity-based medical imaging data are chosen from the group consisting of computed tomography data, positron emission tomography data, ultrasound data, and magnetic resonance imaging data.

21. The method of claim 16 further comprising the step of analyzing the imaging data to determine if the algorithm is compatible with the imaging data.

22. The method of claim 16, wherein the algorithm is implemented with a computer processor.

23. The method of claim 22, wherein the algorithm is automated.

24. A method to determine the trajectory of an implant at an anatomic area comprising the steps of:

importing data collected from one or more images of an anatomic site;

pre-processing the data to ensure compatibility with an algorithm;

isolating an anatomic area of interest from the data using a thresholding segmentation algorithm;

defining the boundaries of the anatomic area in three-dimensions; and

calculating the trajectory of an implant at the anatomic area using search calculations based on the anatomic area and the implant.

25. The algorithm of claim 24, wherein the calculations are chosen from the group consisting of minimum anatomic diameter, maximum implant diameter, optimum implant trajectory, maximum length of the anatomic site, optimum length of the implant, and combinations thereof.

26. The algorithm of claim 25, wherein the calculations are search algorithms that include geometric considerations.