Validation of Material Algorithms for Femur Remodelling Using Medical Image Data
The aim of this study is the utilization of human medical CT images to quantitatively evaluate two sorts of “error-driven” material algorithms, that is, the isotropic and orthotropic algorithms, for bone remodelling. The bone remodelling simulations were implemented by a combination of the finite el...
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| Published in | Applied bionics and biomechanics Vol. 2017; no. 2017; pp. 1 - 10 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Cairo, Egypt
Hindawi Publishing Corporation
01.01.2017
Hindawi Wiley |
| Online Access | Get full text |
| ISSN | 1176-2322 1754-2103 1754-2103 |
| DOI | 10.1155/2017/5932545 |
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| Abstract | The aim of this study is the utilization of human medical CT images to quantitatively evaluate two sorts of “error-driven” material algorithms, that is, the isotropic and orthotropic algorithms, for bone remodelling. The bone remodelling simulations were implemented by a combination of the finite element (FE) method and the material algorithms, in which the bone material properties and element axes are determined by both loading amplitudes and daily cycles with different weight factor. The simulation results showed that both algorithms produced realistic distribution in bone amount, when compared with the standard from CT data. Moreover, the simulated L-T ratios (the ratio of longitude modulus to transverse modulus) by the orthotropic algorithm were close to the reported results. This study suggests a role for “error-driven” algorithm in bone material prediction in abnormal mechanical environment and holds promise for optimizing implant design as well as developing countermeasures against bone loss due to weightlessness. Furthermore, the quantified methods used in this study can enhance bone remodelling model by optimizing model parameters to gap the discrepancy between the simulation and real data. |
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| AbstractList | The aim of this study is the utilization of human medical CT images to quantitatively evaluate two sorts of “error-driven” material algorithms, that is, the isotropic and orthotropic algorithms, for bone remodelling. The bone remodelling simulations were implemented by a combination of the finite element (FE) method and the material algorithms, in which the bone material properties and element axes are determined by both loading amplitudes and daily cycles with different weight factor. The simulation results showed that both algorithms produced realistic distribution in bone amount, when compared with the standard from CT data. Moreover, the simulated L-T ratios (the ratio of longitude modulus to transverse modulus) by the orthotropic algorithm were close to the reported results. This study suggests a role for “error-driven” algorithm in bone material prediction in abnormal mechanical environment and holds promise for optimizing implant design as well as developing countermeasures against bone loss due to weightlessness. Furthermore, the quantified methods used in this study can enhance bone remodelling model by optimizing model parameters to gap the discrepancy between the simulation and real data. The aim of this study is the utilization of human medical CT images to quantitatively evaluate two sorts of "error-driven" material algorithms, that is, the isotropic and orthotropic algorithms, for bone remodelling. The bone remodelling simulations were implemented by a combination of the finite element (FE) method and the material algorithms, in which the bone material properties and element axes are determined by both loading amplitudes and daily cycles with different weight factor. The simulation results showed that both algorithms produced realistic distribution in bone amount, when compared with the standard from CT data. Moreover, the simulated L-T ratios (the ratio of longitude modulus to transverse modulus) by the orthotropic algorithm were close to the reported results. This study suggests a role for "error-driven" algorithm in bone material prediction in abnormal mechanical environment and holds promise for optimizing implant design as well as developing countermeasures against bone loss due to weightlessness. Furthermore, the quantified methods used in this study can enhance bone remodelling model by optimizing model parameters to gap the discrepancy between the simulation and real data.The aim of this study is the utilization of human medical CT images to quantitatively evaluate two sorts of "error-driven" material algorithms, that is, the isotropic and orthotropic algorithms, for bone remodelling. The bone remodelling simulations were implemented by a combination of the finite element (FE) method and the material algorithms, in which the bone material properties and element axes are determined by both loading amplitudes and daily cycles with different weight factor. The simulation results showed that both algorithms produced realistic distribution in bone amount, when compared with the standard from CT data. Moreover, the simulated L-T ratios (the ratio of longitude modulus to transverse modulus) by the orthotropic algorithm were close to the reported results. This study suggests a role for "error-driven" algorithm in bone material prediction in abnormal mechanical environment and holds promise for optimizing implant design as well as developing countermeasures against bone loss due to weightlessness. Furthermore, the quantified methods used in this study can enhance bone remodelling model by optimizing model parameters to gap the discrepancy between the simulation and real data. |
| Author | Luo, Shitong Han, Jianning Shen, Xingquan Bai, Xin Bai, Jing Shang, Yu |
| AuthorAffiliation | 2 Tsinghua University, No. 30 Shuangqing Road, Beijing 100084, China 1 North University of China, No. 3 Xueyuan Road, Taiyuan 030051, China |
| AuthorAffiliation_xml | – name: 2 Tsinghua University, No. 30 Shuangqing Road, Beijing 100084, China – name: 1 North University of China, No. 3 Xueyuan Road, Taiyuan 030051, China |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29440864$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1016_j_medengphy_2020_08_004 crossref_primary_10_1115_1_4065414 |
| Cites_doi | 10.1080/1025584031000064470 10.1016/j.jbiomech.2004.03.005 10.1080/10255840601003577 10.1016/S0021-9290(00)00069-5 10.1016/j.jbiomech.2014.12.021 10.1080/10255840410001712108 10.1016/j.medengphy.2004.09.013 10.1016/j.medengphy.2009.07.011 10.1007/s10237-015-0718-5 10.1016/S0021-9290(97)84505-8 10.1142/S021951941340006X 10.1016/S1672-6529(13)60230-9 10.1080/10255840290032180 10.1016/j.medengphy.2014.04.006 10.1016/S1350-4533(03)00138-3 10.1080/1025584042000205327 10.1016/j.medengphy.2009.10.004 10.1115/1.2895789 10.1046/j.1469-7580.2000.19720145.x 10.1016/S0021-9290(01)00069-0 10.1016/S0021-9290(00)00225-6 10.1007/s00774-004-0533-z 10.1016/j.medengphy.2010.01.004 10.1142/s0219519413500036 10.1186/1475-925X-12-130 10.1016/j.jbiomech.2015.03.027 10.1016/0021-9290(94)00087-K 10.1016/j.orthres.2005.02.002 10.1016/j.jbiomech.2004.08.017 10.1038/35015116 10.1016/S0021-9290(96)00189-3 10.1016/0021-9290(92)90056-7 10.1002/jor.1100080506 10.1016/0021-9290(87)90058-3 10.1016/s0021-9290(02)00028-3 10.1016/j.medengphy.2008.11.007 10.1016/S0021-9290(01)00192-0 10.1016/0021-9290(91)90350-V 10.1142/s021951941550061x 10.1016/0021-9290(87)90030-3 10.1016/j.clinbiomech.2006.01.010 10.1016/j.medengphy.2005.06.003 10.1142/s0219519416500962 10.1016/j.jbiomech.2016.03.007 |
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| Title | Validation of Material Algorithms for Femur Remodelling Using Medical Image Data |
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