Automatic registration of MRI-based joint models to high-speed biplanar radiographs for precise quantification of in vivo anterior cruciate ligament deformation during gait |
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| Institution: | 1. Department of Orthopaedic Surgery, Duke University, Durham, NC, USA;2. Department of Biomedical Engineering, Duke University, Durham, NC, USA;3. Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, USA;1. Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA;2. Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH, USA;3. Sports Medicine Biodynamics Center, Division of Sports Cincinnati Children?s Hospital Medical Center, Cincinnati, OH, USA;4. Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, USA;5. Department of Orthopaedic Surgery, College of Medicine, University of Cincinnati, Cincinnati, OH, USA;6. The Micheli Center for Sports Injury Prevention, Boston, MA, USA;7. Mayo Clinic Biomechanics Laboratories and Sports Medicine Center, Departments of Orthopedics, Physical Medicine and Rehabilitation and Physiology & Biomedical Engineering, Mayo Clinic, Rochester and Minneapolis, MN.;1. Department of Orthopaedic Surgery, Duke University, Durham, NC, USA;2. Department of Biomedical Engineering, Duke University, Durham, NC, USA;3. Department of Radiology, Duke University, Durham, NC, USA;4. Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, USA;1. Duke Sports Medicine Center, Department of Orthopaedic Surgery, Duke University Medical Center, 375 MSRB, Box 3093, Durham, NC 27710, United States;2. Department of Radiology, Duke University Medical Center, United States;3. Department of Biomedical Engineering, Duke University, United States;4. Department of Orthopaedics, University of Pittsburgh Medical Center, United States;5. Durham VA Medical Center, Durham, NC, United States;1. Department of Orthopaedic Surgery, Duke University, Durham, NC, USA;2. Department of Biomedical Engineering, Duke University, Durham, NC, USA;3. Department of Radiology, Duke University, Durham, NC, USA;4. Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, USA;1. Biomechanics and Imaging Group, Department of Orthopedic Surgery, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands;2. Department of Bio-Medical Engineering, Steadman Philippon Research Institute, Vail, USA;3. Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands;4. Departments of Medical Informatics and Radiology, Erasmus Medical Center, Rotterdam, The Netherlands;5. Department of Computer Science, University of Copenhagen, Denmark;6. Department of Biomechanical Engineering, Faculty of Mechanical, Maritime, and Materials Engineering, Delft University of Technology, The Netherlands;1. Steadman Philippon Research Institute, Department of Biomedical Engineering, USA;2. University of Texas Health Science Center, Department of Orthopedic Surgery, USA |
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| Abstract: | Understanding in vivo joint mechanics during dynamic activity is crucial for revealing mechanisms of injury and disease development. To this end, laboratories have utilized computed tomography (CT) to create 3-dimensional (3D) models of bone, which are then registered to high-speed biplanar radiographic data captured during movement in order to measure in vivo joint kinematics. In the present study, we describe a system for measuring dynamic joint mechanics using 3D surface models of the joint created from magnetic resonance imaging (MRI) registered to high-speed biplanar radiographs using a novel automatic registration algorithm. The use of MRI allows for modeling of both bony and soft tissue structures. Specifically, the attachment site footprints of the anterior cruciate ligament (ACL) on the femur and tibia can be modeled, allowing for measurement of dynamic ACL deformation. In the present study, we demonstrate the precision of this system by tracking the motion of a cadaveric porcine knee joint. We then utilize this system to quantify in vivo ACL deformation during gait in four healthy volunteers. |
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| Keywords: | Kinematics Biomechanics ACL Biplanar radiography Optimization Strain Knee Injury mechanism Imaging |
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