Patient registration for total hip arthroplasty procedure using pre-operative computed tomography (CT), intra-operative fluoroscopy, and/or point cloud data

Patent metadata

Field	Value
Publication number	US-12507972-B2
Application number	US-202418743647-A
Country	US
Kind code	B2
Filing date	Jun 14, 2024
Priority date	Jun 14, 2024
Publication date	Dec 30, 2025
Grant date	Dec 30, 2025

Abstract

A system for computer assisted navigation during surgery includes a computer platform that operates to register a target surgical area of a patient. In certain cases, a process includes: obtaining a pre-op CT image of a pelvic region of a patient and intra-operatively obtaining a point cloud data about the pelvic region with a navigated instrument, generating a 3D bone model which excludes non-targeted area such as a femur, and then merging the 3D bone model to the point cloud to register the target surgical area.

First claim

We claim:

1 . A system for computer assisted navigation during a surgery, comprising a computer platform operative to:
obtain a plurality of fluoroscopy images at different orientation of the pelvic region of the patient captured during the surgery, wherein the plurality of fluoroscopy images of the pelvic region include a target surgical area, identify a plurality of known points of the pelvic region in the plurality of fluoroscopy images, determine an anterior pelvic plane (APP) in the plurality of fluoroscopy images based on the identified known points, identify a center of rotation of the acetabulum in the plurality of fluoroscopy images, determine a functional pelvic plane (FPP) in the plurality of fluoroscopy images based on the identified center of rotation, and register the target surgical area based on the determined APP and the determined FPP in the plurality of fluoroscopy images.

2 . The system of claim 1 , wherein the plurality of fluoroscopy images includes both a lateral image and an anterior/posterior (AP) image of the pelvic region.

3 . The system of claim 1 , wherein the plurality of known points on the plurality of fluoroscopy images include:
a left anterior superior iliac spine (ASIS), a right ASIS, and a pubic symphysis, and wherein the APP is determined based on the identified left ASIS, right ASIS, and pubic symphysis.

4 . The system of claim 1 , wherein at least one of the fluoroscopy images includes a non-target surgical area and the computer platform excludes the non-target area from the at least one fluoroscopy image.

5 . The system of claim 1 , wherein the computer platform identifies the plurality of known points of the pelvic region with an artificial neural network (ANN) including a trained machine learning algorithm that is trained by providing an annotated fluoroscopy image data set of a plurality of patients.

6 . The system of claim 1 , wherein the computer platform is further operative to, after registering the location of the target surgical area, use inputs from a navigated instrument to verify at least one landmark on the patient.

7 . The system of claim 1 , wherein the computer platform is further operative to, after registering the location of the target surgical area, use inputs from a navigated instrument to determine a location of an incision relative to the target surgical area.

8 . The system of claim 1 , wherein the computer platform is further operative to, after registering the location of the target surgical area, use inputs from a navigated instrument to determine a location of a verification divot.

9 . The system of claim 1 , wherein the verification divot is disposed on a surveillance marker attached to the patient.

10 . The system of claim 1 , wherein registering the target surgical area includes generating a registration matrix of the target surgical area.

11 . The system of claim 1 , wherein the computer platform is further operative to:
generate a model of the target surgical area based on the registered location.

12 . A computer program product comprising a non-transitory computer readable medium storing instructions executable by at least one processor to perform operations for computer assisted navigation during surgery to:
obtain a plurality of fluoroscopy images at different orientation of the pelvic region of the patient captured during the surgery, wherein the plurality of fluoroscopy images of the pelvic region include a target surgical area, identify a plurality of known points of the pelvic region in the plurality of fluoroscopy images, identify an anterior pelvic plane (APP) in the plurality of fluoroscopy images based on the identified known points, identify a center of rotation of the acetabulum in the plurality of fluoroscopy images, determine a functional pelvic plane (FPP) in the plurality of fluoroscopy images based on the identified center of rotation, and register the target surgical area based on the determined APP and the determined FPP in the plurality of fluoroscopy images.

13 . The computer program product of claim 12 , wherein the plurality of known points on the plurality of fluoroscopy images include:
a left anterior superior iliac spine (ASIS), a right ASIS, and a pubic symphysis, and wherein the APP is determined based on the identified left ASIS, right ASIS, and pubic symphysis.

14 . The computer program product of claim 12 , wherein at least one of the fluoroscopy images includes a femur as a non-target surgical area and the instructions perform operations to exclude the non-target area from the at least one fluoroscopy image.

15 . The computer program product of claim 12 , wherein the instructions perform operations to identify the plurality of known points of the pelvic region with an artificial neural network (ANN) including a trained machine learning algorithm that is trained by providing an annotated fluoroscopy image data set of a plurality of patients.

16 . The computer program product of claim 12 , wherein the computer platform is further operative to, after registering the location of the target surgical area, use inputs from a navigated instrument to verify at least one landmark on the patient.

17 . The computer program product of claim 16 , wherein the instructions perform operations to, after registering the location of the target surgical area, use inputs from a navigated instrument to determine a location of a verification divot.

18 . The computer program product of claim 17 , wherein the verification divot is disposed on a surveillance marker attached to the patient.

Assignees

• Globus Medical Inc

Inventors

• Cameron Hayden
• Washburn Ii Richard H
• Oluwasakin Israel
• Cragg Stephen
• Duch Loris
• Brot Benoit

Classifications

• G06T17/00

  Three-dimensional [3D] modelling for computer graphics · CPC title

• G06T19/20

  Editing of three-dimensional [3D] images, e.g. changing shapes or colours, aligning objects or positioning parts · CPC title

• G06T2219/2004

  Aligning objects, relative positioning of parts · CPC title

• A61B2034/2065

  Tracking using image or pattern recognition · CPC title

• A61B2034/207

  Divots for calibration · CPC title