Benjamin J. Fregly 1 Phone: (352) 392-8157 Fax: (352) 392-7303 e-mail: fregly@ufl.edu Department of Mechanical and Aerospace Engineering, Department of Biomedical Engineering, Department of Othopaedics and Rehabilitation, University of Florida, Gainesville, FL 32611 Haseeb A. Rahman Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611 Scott A. Banks Department of Mechanical and Aerospace Engineering, Department of Orthopaedics and Rehabilitation, University of Florida, Gainesville, FL 32611 and The Biomotion Foundation, West Palm Beach, FL 33480 Theoretical Accuracy of Model-Based Shape Matching for Measuring Natural Knee Kinematics with Single-Plane Fluoroscopy Quantification of knee motion under dynamic, in vivo loaded conditions is necessary to understand how knee kinematics influence joint injury, disease, and rehabilitation. Though recent studies have measured three-dimensional knee kinematics by matching geometric bone models to single-plane fluoroscopic images, factors limiting the accuracy of this approach have not been thoroughly investigated. This study used a three-step computational approach to evaluate theoretical accuracy limitations due to the shape matching process alone. First, cortical bone models of the femur, tibia/fibula, and patella were created from CT data. Next, synthetic (i.e., computer generated) fluoroscopic images were created by ray tracing the bone models in known poses. Finally, an automated matching algorithm utilizing edge detection methods was developed to align flat-shaded bone models to the synthetic images. Accuracy of the recovered pose parameters was assessed in terms of measurement bias and precision. Under these ideal conditions where other sources of error were eliminated, tibiofemoral poses were within 2 mm for sagittal plane translations and 1.5 deg for all rotations while patellofemoral poses were within 2 mm and 3 deg. However, statistically significant bias was found in most relative pose parameters. Bias disappeared and precision improved by a factor of two when the syn- thetic images were regenerated using flat shading (i.e., sharp bone edges) instead of ray tracing (i.e., attenuated bone edges). Analysis of absolute pose parameter errors revealed that the automated matching algorithm systematically pushed the flat-shaded bone mod- els too far into the image plane to match the attenuated edges of the synthetic ray-traced images. These results suggest that biased edge detection is the primary factor limiting the theoretical accuracy of this single-plane shape matching procedure. DOI: 10.1115/1.1933949 1 Introduction Between 1997 and 2002, the number of Americans afflicted with arthritis more than doubled to 70 million, making arthritis the new leading cause of work disability 1. According to the Arthri- tis Foundation, the most common form of arthritis, osteoarthritis OA, appears in the knee more than any other joint. Disease development and progression are influenced by abnormal joint kinematics under dynamic, weight-bearing conditions 2,3. Therefore, knowledge of kinematics in healthy and arthritic knees would be extremely valuable for understanding the disease’s eti- ology and predisposing factors as well as for guiding surgical planning, technique, and procedure. Few studies have measured three-dimensional 3D knee kine- matics under loaded, physiological conditions with submillimeter accuracy as needed to study arthritis-related issues. Video-based motion analysis with surface markers has been used widely to study gross body motion but less to study detailed joint motion due to the problem of skin and soft tissue motion artifacts 4–10. Use of redundant surface markers to correct for motion artifacts shows promise and evaluation of these methods is ongoing 9,10. However, the most direct way to eliminate these issues is to mea- sure joint motion using x-ray techniques. For artificial knees, single-plane fluoroscopy has been used to measure implant motion directly 11–15. With this approach, 3D computer aided design CAD models of the metallic components are aligned to each 2D fluoroscopic image to quantify pose translation and rotation pa- rameters. This approach works well since the metallic components have precisely known geometric features and produce sharp edges in fluoroscopic images. For natural knees, since CAD models of the bones are not readily available from the manufacturer, biplane fluoroscopy with implanted bone markers has been used instead 16–18. Though more accurate than single-plane fluoroscopy, this approach requires surgical implantation of metal beads which re- stricts its use to research projects with limited populations. Building on the example of artificial knee studies, researchers have recently begun to use single-plane fluoroscopy to measure natural knee motion 19–21. For the shape matching procedure, implant CAD models are replaced with geometric bone models created from medical imaging data. However, in fluoroscopic im- ages, cortical bone edges are less well defined than are metallic implant edges 16. Consequently, to evaluate the extent to which this approach can be used to study arthritis-related issues, a theo- retical accuracy assessment is needed to quantify expected errors in measured joint relative and bone absolute kinematics. This study quantifies relative and absolute accuracy limitations due to the shape matching process alone when natural knee kine- matics are measured by aligning flat-shaded, edge detected bone models to single plane fluoroscopic images. Similar to the ap- proach used for knee implant components, flat shading is used in 1 Corresponding author. Contributed by the Bioengineering Division for publication in the JOURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received January 5, 2004. Revi- sion received January 27, 2005. Associate Editor: Marcus G. Pandy. 692 / Vol. 127, AUGUST 2005 Copyright © 2005 by ASME Transactions of the ASME