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MRI vs CT-based 2D-3D auto-registration accuracy for quantifying shoulder motion using biplane video-radiography
Institution:1. Biomechanics and Movement Science Program, University of Delaware, Newark, DE, USA;2. Nemours Alfred I. duPont Hospital for Children, Wilmington, Delaware, USA;1. Medical College of Wisconsin, 8700 Watertown Plank Road, Milwaukee, WI 53226 USA;2. Marquette University, 1515 W. Wisconsin Avenue, Milwaukee, WI 53233 USA;3. Meriter UnityPoint, 6408 Copps Avenue, Monona, WI 53716 USA
Abstract:Biplane 2D-3D registration approaches have been used for measuring 3D, in vivo glenohumeral (GH) joint kinematics. Computed tomography (CT) has become the gold standard for reconstructing 3D bone models, as it provides high geometric accuracy and similar tissue contrast to video-radiography. Alternatively, magnetic resonance imaging (MRI) would not expose subjects to radiation and provides the ability to add cartilage and other soft tissues to the models. However, the accuracy of MRI-based 2D-3D registration for quantifying glenohumeral kinematics is unknown. We developed an automatic 2D-3D registration program that works with both CT- and MRI-based image volumes for quantifying joint motions. The purpose of this study was to use the proposed 2D-3D auto-registration algorithm to describe the humerus and scapula tracking accuracy of CT- and MRI-based registration relative to radiostereometric analysis (RSA) during dynamic biplanar video-radiography. The GH kinematic accuracy (RMS error) was 0.6–1.0 mm and 0.6–2.2° for the CT-based registration and 1.4–2.2 mm and 1.2–2.6° for MRI-based registration. Higher kinematic accuracy of CT-based registration was expected as MRI provides lower spatial resolution and bone contrast as compared to CT and suffers from spatial distortions. However, the MRI-based registration is within an acceptable accuracy for many clinical research questions.
Keywords:Glenohumeral kinematics  Automatic 2D-3D registration  Shoulder motion tracking  Motion tracking accuracy  Radiostereometric analysis (RSA)
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