. 2021 Dec 2;214:106570.
doi: 10.1016/j.cmpb.2021.106570.
Online ahead of print.
1
, Jiakun Ren
2
, Zhongwei Sun
3
, Jing Zhang
4
, Kai Xu
4
, Lu Sun
4
, Pinglin Yang
1
, Dong Wang
1
, Yueyun Lian
1
, Jingjing Zhai
1
, Yali Gou
1
, Yanbing Ma
5
, Shengfeng Ji
5
, Xijing He
6
, Baohui Yang
7
Affiliations
Affiliations
- 1 Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China.
- 2 Department of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
- 3 Department of Engineering Mechanics, School of Civil Engineering, Southeast University, Nanjing, Jiangsu Province, China.
- 4 Department of Research and Development, ZSFab, Inc., Boston, Massachusetts, United States.
- 5 Department of Human Anatomy and Tissue Embryology, School of Medicine, Xi’an Jiaotong University, Xi’an, Shaanxi Province, China.
- 6 Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China. Electronic address: [email protected].
- 7 Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China. Electronic address: [email protected].
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Teng Lu et al.
Comput Methods Programs Biomed.
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. 2021 Dec 2;214:106570.
doi: 10.1016/j.cmpb.2021.106570.
Online ahead of print.
Authors
1
, Jiakun Ren
2
, Zhongwei Sun
3
, Jing Zhang
4
, Kai Xu
4
, Lu Sun
4
, Pinglin Yang
1
, Dong Wang
1
, Yueyun Lian
1
, Jingjing Zhai
1
, Yali Gou
1
, Yanbing Ma
5
, Shengfeng Ji
5
, Xijing He
6
, Baohui Yang
7
Affiliations
- 1 Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China.
- 2 Department of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
- 3 Department of Engineering Mechanics, School of Civil Engineering, Southeast University, Nanjing, Jiangsu Province, China.
- 4 Department of Research and Development, ZSFab, Inc., Boston, Massachusetts, United States.
- 5 Department of Human Anatomy and Tissue Embryology, School of Medicine, Xi’an Jiaotong University, Xi’an, Shaanxi Province, China.
- 6 Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China. Electronic address: [email protected].
- 7 Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China. Electronic address: [email protected].
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Abstract
Background and objective Conventional method for evaluating the biomechanical effects of a specific elastic modulus of cage (cage-E) on spinal fusions requires establishing a “one-on-one” biomechanical model, which seems laborious and inefficient when dealing with the emergence of numerous cage materials with various cage-Es. We aim to offer a much convenient method to instantly predicting the biomechanical effects of any targeted cage-E on transforaminal lumbar interbody fusion (TLIF) by using a parametric finite element (FE) analysis to determining the regression relationship between cage-E and biomechanical properties of TLIF. Materials and methods A L4/5 FE TLIF construct was modeled. Cage-E was linearly increased from 0.1 GPa (cancellous bone) to 110 GPa (titanium alloy). The function equations for assessing the influence of cage-E on the biomechanical indexes of TLIF were established using a logarithmic regression analysis. Experimental results As cage-E increased from 0.1 GPa to 110 GPa, all the biomechanical indexes initially increased or decayed rapidly, and then slowed over time. Logarithmic regression models and functional equations were successfully established between cage-E and these indexes (P<0.0001). Their determination coefficients ranged from 0.72 to 0.99. The range of motions decreased from 0.37-1.10° to 0.20-1.07°. The mean stresses of the central and peripheral grafts reduced from 0.10-0.41 and 0.25-0.42 MPa to 0.03-0.04 and 0.19-0.27 MPa, respectively. In addition, the maximum stresses of the screw-bone interface and posterior instrumentation reduced from 11.76-25.04 and 8.91-84.68 MPa to 9.71-18.92 and 6.99-70.59 MPa, respectively. Finally, the maximum stresses of the cage and endplate increased from 0.28-1.35 MPa and 3.90-8.63 MPa to 14.86-36.16 MPa and 11.01-36.55 MPa, respectively. Conclusions The decrease of cage-E reduces the risks of cage subsidence, cage breakage, and pseudarthrosis, while increasing the risk of instrumentation failure. The logarithmic regression models optimally demonstrate the relationship between cage-E and biomechanical properties of TLIF. The functional equations based on these models can be adopted to predict the biomechanical effects of any targeted cage-Es on TLIF, which effectively simplifies the procedures for the biomechanical assessments of cage materials.
Keywords:
Biomechanical properties; Cage; Elastic modulus; Finite element analysis; Logarithmic regression; Transforaminal lumbar interbody fusion.
Copyright © 2021. Published by Elsevier B.V.
Conflict of interest statement
Declaration of Competing Interest The authors declare no conflict of interest.
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