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Validation of full-length radiograph based musculoskeletal modeling method to estimate medial and lateral knee
Junqing Wang1, Fashu Xu2, Hui Zhang2
1Department of Orthopedic Surgery and Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China; Department of Orthopedic Surgery and west China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China; State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning Province, China.
Background:
Anatomical parameters of the pelvis, femur, and tibia derived from the full-length radiograph can be used to create a more accurate musculoskeletal model compared to marker-based linear scaling method. However, whether this model leads to more accurate estimations of medial knee contact force (MCF) and lateral knee contact force (LCF) than marker-based linear scaling method is still unknown.
Research Question:
This main purpose of this study was to determine whether musculoskeletal model generated from full-length radiograph improves the estimations of MCF and LCF.
Methods:
An open-source dataset including marker trajectories, ground reaction forces, in vivo knee contact forces, and full-length radiograph was used to evaluate the accuracy of full-length radiograph musculoskeletal modeling method. Subject-specific musculoskeletal models were created using anatomical parameters derived from the full-length radiograph or marker-based linear scaling methods. MCF and LCF were estimated using musculoskeletal simulations of normal walking trails. The accuracy of modeling methods was determined by comparing the estimated and in vivo measured MCF and LCF.
Results:
Compared to the marker-based linear scaling approach, the full-length radiograph musculoskeletal modeling method exhibited decreases of 38.3 % and 41.3 % in root mean square error for MCF and LCF respectively, as well as reductions of 50.0 % and 49.3 % in mean peak errors for MCF and LCF respectively.
Significance:
The full-length radiograph musculoskeletal modeling method provides a more accurate way to estimate MCF and LCF compared to the traditional maker-based linear scaling approach, which may contribute to understand the initiation, progression, and treatment of OA.
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