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Research Papers

A Model-Free Feature-Based Bi-Planar RSA Method for Kinematic Analysis of Total Knee Arthroplasty

[+] Author and Article Information
Shahram Amiri1

Department of Orthopaedics,  University of British Columbia, Vancouver, BC, V5Z 1M9, Canadashahramiri@gmail.com

Carolyn Anglin

Biomedical Engineering, Dept. of Civil Engineering,  McCaig Institute for Bone and Joint Health University of Calgary, Calgary, AB, T2N 1N4, Canadacanglin@ucalgary.ca

Kenard Agbanlog

Department of Orthopaedics,  University of British Columbia, Vancouver, BC, V5Z 1M9, Canadakenard.agbanlog@gmail.com

Bassam A. Masri

Department of Orthopaedics,  University of British Columbia, Vancouver, BC, V5Z 1M9, Canadabassam.masri@vch.ca

David R. Wilson

Department of Orthopaedics,  University of British Columbia, Vancouver, BC, V5Z 1M9, Canadadavid.wilson@ubc.ca

For more information about this software, please see sourceforge.net/projects/jointtrack/.

1

Present address: Centre for Hip Health and Mobility, Robert HN Ho Research Center, 766-2635 Laurel Street, Vancouver, BC, V6H 2K2, Canada.

J Biomech Eng 134(3), 031009 (Mar 27, 2012) (8 pages) doi:10.1115/1.4006198 History: Received September 28, 2011; Accepted February 20, 2012; Revised February 20, 2012; Posted February 24, 2012; Published March 26, 2012; Online March 27, 2012

Fluoroscopic imaging is commonly used for assessing relative motions of orthopaedic implants. One limiting factor to in vivo model-based roentgen stereophotogrammetric analysis of total knee arthroplasty is the need for 3D models of the implants.The 3D models of the implant components must be reverse-engineered, if not provided by the company, which makes this method impractical for a clinical study involving many types or sizes of implants. This study introduces a novel feature-based methodology that registers the features at the implant-bone or implant-cement interface of the components that have elementary shapes. These features include pegs with hemispherical heads, and straight, circular or curved edges located on flat faces of the box of the femoral component or the stem geometry of the tibial component. Software was developed to allow easy registration of these features through a graphical user interface. The accuracy and precision of registration for multiple flexion angles from 0 to 120 deg was determined with reference to registered poses of the implants through experiments on bone replica models and also on a cadaver specimen implanted with total knee prostheses. When compared to an equivalent bi-planar model-based registration, the results were comparable: The mean accuracy of this feature-based method was 1.45 deg and 1.03 mm (in comparison to 0.95 deg and 1.32 mm for the model-based approach), and the mean precision was 0.57 deg and 0.26 mm (in comparison to 0.42 deg and 0.44 mm for the model-based approach).The methodology and the developed software can easily accommodate different design of implants with various fixation features. This method can facilitate in vivo kinematic analysis of total knee arthroplasty by eliminating the need for 3D models of the implant components.

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Copyright © 2012 by American Society of Mechanical Engineers
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Figures

Grahic Jump Location
Figure 4

The auxiliary radiographic images Y and Z were acquired in the imaging configuration shown in Fig. 2. These images were used to determine further information about the component features. In the case of the example implant, these radiographs were used to determine the 3D distance between the femoral pegs (C1 and C2).

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Figure 5

Bone replica models implanted with prostheses were used to determine the accuracy of 3D reconstruction. Optotrak optoelectronic motion tracking markers were attached to the bones (a), and an optoelectronic digitizing probe was used to digitize the surfaces of the implant components on their implant-bone interface through the cut-out made on the bones for accessing these surfaces (b). The tibial component was digitized with reference to the tibial bone in the same fashion.

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Figure 6

Radiographic images of the cadaveric specimen implanted with TKA components. The labeled elementary features correspond to those in Fig. 1. The contrast between the component and the background was reduced by the soft tissues (compared to the bone replica model images) and the partially radiopaque bone cement (compared to the bone replica model images, Fig. 3).

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Figure 7

The 3D visual representation and coordinate system of the component registered based on the feature-based method produced by the Joint3D program (a). The reconstructed 3D poses of the components from the model-based and feature-based methods are superimposed (b) to visually show that the feature-based method can be used equivalently to study the TKA kinematics.

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Figure 1

The elementary features of the implant components were used in combination to reconstruct their corresponding 3D coordinate systems. For the femoral component (a) the origin was located at the midpoint between the pegs (C1 and C2), the anteroposterior (AP) axis was parallel to the edge (L1) of the box, the proximodistal (PD) axis was parallel to the posterior edge of one of the condyles (L2), and the mediolateral (ML) axis was parallel to the line connecting the pegs (C1 and C2). For the tibial component (b), the transverse plane (P1) was determined as the plane fitted to the points containing the planar curved edges (S1 and S2), the PD axis was defined parallel to the normal vector (n1) to this plane, the AP axis was parallel to the straight side of the tibial tray (L3), the ML axis was perpendicular to AP on plane P1, and the origin was defined as the projection of the center of the circular edge (E1) over the plane P1.

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Figure 2

Imaging setup and configuration for studying the knee joint in a lunge activity. The imaging system consists of a C-arm tilted 15 deg from an upright position to accommodate the upper body of a subject in a weightbearing position, tracked with a motion tracking camera (a) used in a multiplanar radiography approach [14]. To depict the features on the implant-bone interface of the prosthesis, the subject is expected to be rotated 5 deg with reference to the axis of the C-arm (b). To capture the features shown in Fig. 1, two radiographs were sequentially acquired from the knee joint when the C-arm was rotated by 5 deg from the horizontal orientation; the second image was rotated 15 deg with respect to the first (c). Auxiliary images were acquired at a supine position of the knee. The first image was rotated 5 deg from the horizontal reference line, and the second image was rotated 20 deg with respect to the first. The specimens and bone models imaged in this study were positioned at the poses replicating the positions of the person shown in these pictures (no in vivo images were collected during this study).

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Figure 3

Joint3D software was developed to segment the elementary features of the component at their bone interface and to conduct the feature-based reconstruction. The features labeled in the radiographs (a) and (b) in the picture correspond to the features depicted in Fig. 1. The software reconstructs the 3D positions of the components based on the identified locations of the features.

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