Abstract

Our objective was to identify precise mechanical metrics of the proximal tibia which differentiated OA and normal knees. We developed subject-specific FE models for 14 participants (7 OA, 7 normal) who were imaged three times each for assessing precision (repeatability). We assessed various mechanical metrics (minimum principal and von Mises stress and strain as well as structural stiffness) across the proximal tibia for each subject. In vivo precision of these mechanical metrics was assessed using CV%RMS. We performed parametric and non-parametric statistical analyses and determined Cohen’s d effect sizes to explore differences between OA and normal knees. For all FE-based mechanical metrics, average CV%RMS was less than 6%. Minimum principal stress was, on average, 75% higher in OA versus normal knees while minimum principal strain values did not differ. No difference was observed in structural stiffness. FE modeling could precisely quantify and differentiate mechanical metrics variations in normal and OA knees, in vivo. This study suggests that bone stress patterns may be important for understanding OA pathogenesis at the knee.

Details

Title
Mechanical Metrics of the Proximal Tibia are Precise and Differentiate Osteoarthritic and Normal Knees: A Finite Element Study
Author
Arjmand, Hanieh 1 ; Nazemi, Majid 1 ; Kontulainen, Saija A 2 ; McLennan, Christine E 3 ; Hunter, David J 4 ; Wilson, David R 5 ; Johnston, James D 1 

 Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada 
 College of Kinesiology, University of Saskatchewan, Saskatoon, SK, Canada 
 Division of Research, New England Baptist Hospital, Boston, MA, USA 
 Institute of Bone and Joint Research, Kolling Institute, University of Sydney and Rheumatology Department, Royal North Shore Hospital, Sydney, NSW, Australia 
 Department of Orthopaedics and Centre for Hip Health and Mobility, University of British Columbia and Vancouver Coastal Health Research Institute, Vancouver, BC, Canada 
Pages
1-10
Publication year
2018
Publication date
Jul 2018
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2081312587
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.