Drew A Lansdown1, Musa Zaid2, Valentina Pedoia3, Karupppasamy Subburaj4, Richard Souza3, C Benjamin1, Xiaojuan Li1. 1. Department of Orthopaedic Surgery, University of California, San Francisco, San Francisco, California, USA. 2. School of Medicine, University of California, San Francisco, San Francisco, California, USA. 3. Musculoskeletal and Quantitative Imaging Research, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA. 4. Singapore University of Technology and Design, Singapore.
Abstract
PURPOSE: To describe three quantification methods for magnetic resonance imaging (MRI)-based knee kinematic evaluation and to report on the reproducibility of these algorithms. MATERIALS AND METHODS: T2 -weighted, fast-spin echo images were obtained of the bilateral knees in six healthy volunteers. Scans were repeated for each knee after repositioning to evaluate protocol reproducibility. Semiautomatic segmentation defined regions of interest for the tibia and femur. The posterior femoral condyles and diaphyseal axes were defined using the previously defined tibia and femur. All segmentation was performed twice to evaluate segmentation reliability. Anterior tibial translation (ATT) and internal tibial rotation (ITR) were calculated using three methods: a tibial-based registration system, a combined tibiofemoral-based registration method with all manual segmentation, and a combined tibiofemoral-based registration method with automatic definition of condyles and axes. Intraclass correlation coefficients and standard deviations across multiple measures were determined. RESULTS: Reproducibility of segmentation was excellent (ATT = 0.98; ITR = 0.99) for both combined methods. ATT and ITR measurements were also reproducible across multiple scans in the combined registration measurements with manual (ATT = 0.94; ITR = 0.94) or automatic (ATT = 0.95; ITR = 0.94) condyles and axes. CONCLUSION: The combined tibiofemoral registration with automatic definition of the posterior femoral condyle and diaphyseal axes allows for improved knee kinematics quantification with excellent in vivo reproducibility.
PURPOSE: To describe three quantification methods for magnetic resonance imaging (MRI)-based knee kinematic evaluation and to report on the reproducibility of these algorithms. MATERIALS AND METHODS: T2 -weighted, fast-spin echo images were obtained of the bilateral knees in six healthy volunteers. Scans were repeated for each knee after repositioning to evaluate protocol reproducibility. Semiautomatic segmentation defined regions of interest for the tibia and femur. The posterior femoral condyles and diaphyseal axes were defined using the previously defined tibia and femur. All segmentation was performed twice to evaluate segmentation reliability. Anterior tibial translation (ATT) and internal tibial rotation (ITR) were calculated using three methods: a tibial-based registration system, a combined tibiofemoral-based registration method with all manual segmentation, and a combined tibiofemoral-based registration method with automatic definition of condyles and axes. Intraclass correlation coefficients and standard deviations across multiple measures were determined. RESULTS: Reproducibility of segmentation was excellent (ATT = 0.98; ITR = 0.99) for both combined methods. ATT and ITR measurements were also reproducible across multiple scans in the combined registration measurements with manual (ATT = 0.94; ITR = 0.94) or automatic (ATT = 0.95; ITR = 0.94) condyles and axes. CONCLUSION: The combined tibiofemoral registration with automatic definition of the posterior femoral condyle and diaphyseal axes allows for improved knee kinematics quantification with excellent in vivo reproducibility.
Authors: Bruce D Beynnon; Robert J Johnson; Joseph A Abate; Braden C Fleming; Claude E Nichols Journal: Am J Sports Med Date: 2005-10 Impact factor: 6.202
Authors: Shawn Farrokhi; Carrie A Voycheck; Brian A Klatt; Jonathan A Gustafson; Scott Tashman; G Kelley Fitzgerald Journal: Clin Biomech (Bristol, Avon) Date: 2014-05-05 Impact factor: 2.063
Authors: Michal Kozanek; Ali Hosseini; Fang Liu; Samuel K Van de Velde; Thomas J Gill; Harry E Rubash; Guoan Li Journal: J Biomech Date: 2009-06-03 Impact factor: 2.712
Authors: Thomas P Andriacchi; Anne Mündermann; R Lane Smith; Eugene J Alexander; Chris O Dyrby; Seungbum Koo Journal: Ann Biomed Eng Date: 2004-03 Impact factor: 3.934
Authors: Martin Charles Logan; Andrew Williams; Jonathon Lavelle; Wady Gedroyc; Michael Freeman Journal: Am J Sports Med Date: 2004-06 Impact factor: 6.202
Authors: Drew A Lansdown; Valentina Pedoia; Musa Zaid; Keiko Amano; Richard B Souza; Xiaojuan Li; C Benjamin Ma Journal: Clin Orthop Relat Res Date: 2017-10 Impact factor: 4.176
Authors: Brian C Lau; Daniel U Thuillier; Valentina Pedoia; Ellison Y Chen; Zhihong Zhang; Brian T Feeley; Richard B Souza Journal: Knee Date: 2015-12-31 Impact factor: 2.199
Authors: Tzu-Chieh Liao; Hannah Jergas; Radhika Tibrewala; Emma Bahroos; Thomas M Link; Sharmila Majumdar; Richard B Souza; Valentina Pedoia Journal: J Orthop Res Date: 2020-10-05 Impact factor: 3.102