Method for tibia resection alignment approximation in knee replacement procedures
Aspects of the present disclosure involve systems, methods, computer program products, and the like, for utilizing a series of images of a patient's anatomy to determine a cut plane for use during a knee procedure. To determine a cut plane for use during a knee replacement procedure, the 2D images may be analyzed by a computer program to determine a best fit plane through one or more points along the proximal surface of the tibia and to determine one or more features of depressions within the proximal surface. With these landmarks identified in the images, a cut plane through the tibia for use during a TKA procedure may be determined. Further, the location of these features in the images may be determined by analyzing the gray scale value of one or more pixels around a selected point on the image. The pixel with the lowest gray scale value may then be assumed to be the edge of the cortical bone in the 2D image.
1. A method for determining a cut plane through a human tibia for an arthroplasty procedure on a human knee, the method comprising:
receiving a plurality of two-dimensional (2D) images of a patient's joint subject to the arthroplasty procedure at a computing device;
determining a plane for a plurality of points along a table surface of a human tibia of a first set of 2D images of the plurality of 2D images, the table surface comprising at least a portion of a proximal end of the human tibia, said plurality of points comprising at least three points;
wherein the plane for the plurality of points along the table surface of the human tibia is a best fit plane along the table surface of the human tibia within the at least one of the plurality of 2D images;
wherein the plurality of points along the table surface of the human tibia of the first set of 2D images are determined by:
obtaining a reference point on the at least one of the plurality of 2D images;
creating a range of pixels of the at least one of the plurality of 2D images from the reference point, wherein each pixel in the range of pixels comprises a gray scale value; and
determining the pixel in a first range of pixels with the lowest gray scale value;
calculating a cut plane for use during the arthroplasty procedure on a human knee, wherein the cut plane is parallel to the calculated plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images; and
generating a cutting jig for the arthroplasty procedure comprising a cut slot corresponding to the calculated cut plane.
2. The method of claim 1 wherein the best fit plane is calculated through a least squares plane calculation.
3. The method of claim 1 further comprising determining a cut plane depth on the human tibia, the cut plane depth comprising a distance measured distally along the human tibia from the best fit plane.
4. The method of claim 3 further comprising calculating a depression curve within at least one of the plurality of 2D images representing a depression feature of the table surface of the human tibia.
5. The method of claim 4 further comprising determining a maximum depth of the depression feature of the table surface of the human tibia from the depression curve.
6. The method of claim 5 wherein the cut plane depth is greater than the maximum depth of the depression feature of the table surface of the human tibia as measured from the best fit plane for the plurality of points along the table surface of the human tibia.
7. The method of claim 1 wherein calculating the cut plane for use during the arthroplasty procedure comprises: calculating a best fit plane normal vector to the best fit plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images; and
orienting a normal vector of the cut plane to be parallel to the best fit plane normal vector.
8. The method of claim 1 wherein the calculated cut plane corresponds to a resection plane of the human tibia during a total knee arthroplasty procedure.
9. The method of claim 1 wherein the plurality of 2D images of a patient's joint subject to the arthroplasty procedure are magnetic resonance imagining (MRI) images.
10. A system for processing a medical scan of a patient in preparation for an arthroplasty procedure on a human knee, the system comprising:
a network interface configured to receive one or more medical images of a patient's anatomy; and a processing device in communication with the network interface; and
a computer-readable medium in communication with the processing device configured to store information and instructions that, when executed by the processing device, performs the operations of:
receiving a plurality of two-dimensional (2D) images of a patient's joint subject to the arthroplasty procedure at a computing device;
determining a plane for a plurality of points along a table surface of a human tibia of a first set of 2D images of the plurality of 2D images, the table surface comprising at least a portion of a proximal end of the human tibia said plurality of points comprising at least three points;
wherein the plane for the plurality of points along the table surface of the human tibia is a best fit plane along the table surface of the human tibia within the at least one of the plurality of 2D images;
wherein the plurality of points along the table surface of the human tibia of the first set of 2D images are determined by:
obtaining a reference point on the at least one of the plurality of 2D images;
creating a range of pixels of the at least one of the plurality of 2D images from the reference point, wherein each pixel in the range of pixels comprises a gray scale value; and
determining the pixel in a first range of pixels with the lowest gray scale value;
calculating a cut plane for use during the arthroplasty procedure on a human knee, wherein the cut plane is parallel to the calculated plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images; and
generating a cutting jig for the arthroplasty procedure comprising a cut slot corresponding to the calculated cut plane.
11. The system of claim 10 wherein the best fit plane is calculated through a least squares plane calculation.
12. The system of claim 10 wherein the information and instructions, when executed by the processing device, further performs the operation of determining a cut plane depth on the human tibia, the cut plane depth comprising a distance measured distally along the tibia from the best fit plane.
13. The system of claim 12 wherein the information and instructions, when executed by the processing device, further performs the operation of calculating a depression curve within at least one of the plurality of 2D images representing a depression feature of the table surface of the human tibia.
14. The system of claim 13 wherein the information and instructions, when executed by the processing device, further performs the operation of determining a maximum depth of the depression feature of the table surface of the human tibia from the depression curve.
15. The system of claim 14 wherein the cut plane depth is greater than the maximum depth of the depression feature of the table surface of the human tibia as measured from the best fit plane for the plurality of points along the table surface of the human tibia.
16. The system of claim 10 wherein calculating the cut plane for use during the arthroplasty procedure comprises:
calculating a best fit plane normal vector to the best fit plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images; and
orienting a normal vector of the cut plane to be parallel to the best fit plane normal vector.
17. The system of claim 10 wherein the calculated cut plane corresponds to a resection plane of the human tibia during a total knee arthroplasty procedure.
18. The system of claim 10 wherein the plurality of 2D images of a patient's joint subject to the arthroplasty procedure are magnetic resonance imagining (MRI) images.
19. A method for determining a cut plane through a human tibia for an arthroplasty procedure on a human knee, the method comprising:
receiving a plurality of two-dimensional (2D) images of a patient's joint subject to the arthroplasty procedure at a computing device;
determining a plane for a plurality of points along a table surface of a human tibia of a first set of 2D images of the plurality of 2D images, the table surface comprising at least a portion of a proximal end of the human tibia;
calculating a depression curve within at least one of the plurality of 2D images representing a depression feature of the table surface of the human tibia;
calculating a cut plane for use during the arthroplasty procedure on a human knee, wherein the cut plane is parallel to the calculated plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images;
determining a cut plane depth on the human tibia, the cut plane depth comprising a distance measured distally along the human tibia from the best fit plane; and
generating a cutting jig for the arthroplasty procedure comprising a cut slot corresponding to the calculated cut plane.
20. The method of claim 19 further comprising determining a maximum depth of the depression feature of the table surface of the human tibia from the depression curve.
21. The method of claim 20 wherein the cut plane depth is greater than the maximum depth of the depression feature of the table surface of the human tibia as measured from the best fit plane for the plurality of points along the table surface of the human tibia.
22. A method for determining a cut plane through a human tibia for an arthroplasty procedure on a human knee, the method comprising:
receiving a plurality of two-dimensional (2D) images of a patient's joint subject to the arthroplasty procedure at a computing device;
determining a plane for a plurality of points along a table surface of a human tibia of a first set of 2D images of the plurality of 2D images, the table surface comprising at least a portion of a proximal end of the human tibia, said plurality of points comprising at least three points;
wherein the plane for the plurality of points along the table surface of the human tibia is a best fit plane along the table surface of the human tibia within the at least one of the plurality of 2D images;
calculating a cut plane for use during the arthroplasty procedure on a human knee;
wherein calculating the cut plane for use during the arthroplasty procedure comprises:
calculating a best fit plane normal vector to the best fit plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images; and
orienting a normal vector of the cut plane to be parallel to the best fit plane normal vector;
wherein the cut plane is parallel to the calculated plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images; and
generating a cutting jig for the arthroplasty procedure comprising a cut slot corresponding to the calculated cut plane.
23. A system for processing a medical scan of a patient in preparation for an arthroplasty procedure on a human knee, the system comprising:
a network interface configured to receive one or more medical images of a patient's anatomy; and a processing device in communication with the network interface; and
a computer-readable medium in communication with the processing device configured to store information and instructions that, when executed by the processing device, performs the operations of:
receiving a plurality of two-dimensional (2D) images of a patient's joint subject to the arthroplasty procedure at a computing device;
determining a plane for a plurality of points along a table surface of a human tibia of a first set of 2D images of the plurality of 2D images, the table surface comprising at least a portion of a proximal end of the human tibia said plurality of points comprising at least three points;
wherein the plane for the plurality of points along the table surface of the human tibia is a best fit plane along the table surface of the human tibia within the at least one of the plurality of 2D images;
calculating a depression curve within at least one of the plurality of 2D images representing a depression feature of the table surface of the human tibia;
determining a cut plane depth on the human tibia, the cut plane depth comprising a distance measured distally along the tibia from the best fit plane;
calculating a cut plane for use during the arthroplasty procedure on a human knee, wherein the cut plane is parallel to the calculated plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images; and
generating a cutting jig for the arthroplasty procedure comprising a cut slot corresponding to the calculated cut plane.
24. A system for processing a medical scan of a patient in preparation for an arthroplasty procedure on a human knee, the system comprising:
a network interface configured to receive one or more medical images of a patient's anatomy; and a processing device in communication with the network interface; and
a computer-readable medium in communication with the processing device configured to store information and instructions that, when executed by the processing device, performs the operations of:
receiving a plurality of two-dimensional (2D) images of a patient's joint subject to the arthroplasty procedure at a computing device;
determining a plane for a plurality of points along a table surface of a human tibia of a first set of 2D images of the plurality of 2D images, the table surface comprising at least a portion of a proximal end of the human tibia said plurality of points comprising at least three points;
wherein the plane for the plurality of points along the table surface of the human tibia is a best fit plane along the table surface of the human tibia within the at least one of the plurality of 2D images;
calculating a best fit plane normal vector to the best fit plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images;
orienting a normal vector of the cut plane to be parallel to the best fit plane normal vector;
calculating a cut plane for use during the arthroplasty procedure on a human knee, wherein the cut plane is parallel to the calculated plane for the plurality of points along the table surface of the human tibia of the first set of 2D images of the plurality of 2D images; and
generating a cutting jig for the arthroplasty procedure comprising a cut slot corresponding to the calculated cut plane.