Digital Image Processing Applied in the Deformation Analysis of Hip Prosthesis: Multivariate Regression Analysis
Total Hip Arthroplasty (THA) is one of the most performed surgical procedures to treat osteoarthritis of the hip joint or other skeletal disorders, such as Developmental Dysplasia of the Hip (DDH) or malformations. The purpose of the THA is to replace damaged bone/cartilage and recover the biomechan...
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2024-01-01
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| author | Jorge Ramos-Frutos Israel Miguel-Andres Diego Oliva Marco Perez-Cisneros Teresa Alonso-Rasgado Colin G. Bailey Jose Francisco del Valle-Mojica |
| author_facet | Jorge Ramos-Frutos Israel Miguel-Andres Diego Oliva Marco Perez-Cisneros Teresa Alonso-Rasgado Colin G. Bailey Jose Francisco del Valle-Mojica |
| author_sort | Jorge Ramos-Frutos |
| collection | DOAJ |
| description | Total Hip Arthroplasty (THA) is one of the most performed surgical procedures to treat osteoarthritis of the hip joint or other skeletal disorders, such as Developmental Dysplasia of the Hip (DDH) or malformations. The purpose of the THA is to replace damaged bone/cartilage and recover the biomechanics of the joint in the best possible way. Placing hip prostheses is common practice in the treatment of THA, but the effect of this treatment must be evaluated before surgery. This work proposes a method to assess hip deformation with an implanted acetabular cup, using digital image processing and multivariate linear regression. Images were acquired when a hemipelvis was subjected to mechanical load ranging from 0 to 1800 Newtons. Eighteen geometric characteristics were analyzed, and only seven were significant in the multivariate linear regression model. To decide on the variables that are considered important, three criteria were used on the multivariate linear regression model established in the different characteristics. The first criterion considers the significance of the model coefficients; the second criterion considers a coefficient of determination greater than 75%, and the third criterion considers that the proposed model is significant. If all three criteria are met, the response variable is considered significant. This analysis gives specialists a tool to make decisions before performing THA treatment. Moreover, this methodology could be applied to assess the deformation of the hip with different pathologies such as DDH, malformations, and overweight conditions. Finally, a relationship is generated between the extracted geometric characteristics and the experimental results obtained in the laboratory. |
| format | Article |
| id | doaj-art-b0f5967d4d7a4ac8aec0bd1ce2df9923 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-b0f5967d4d7a4ac8aec0bd1ce2df99232024-12-04T00:01:26ZengIEEEIEEE Access2169-35362024-01-011217693817694810.1109/ACCESS.2024.350616410767137Digital Image Processing Applied in the Deformation Analysis of Hip Prosthesis: Multivariate Regression AnalysisJorge Ramos-Frutos0https://orcid.org/0000-0002-5743-9343Israel Miguel-Andres1https://orcid.org/0000-0002-9433-7864Diego Oliva2https://orcid.org/0000-0001-8781-7993Marco Perez-Cisneros3https://orcid.org/0000-0001-6493-0408Teresa Alonso-Rasgado4https://orcid.org/0000-0002-7594-145XColin G. Bailey5Jose Francisco del Valle-Mojica6Departamento de Posgrados, Centro de Innovación Aplicada en Tecnologías Competitivas, León, MexicoDepartamento de Posgrados, Centro de Innovación Aplicada en Tecnologías Competitivas, León, MexicoDepartamento de Ingeniería Electro-Fotónica, CUCEI, Universidad de Guadalajara, Guadalajara, MexicoDepartamento de Ingeniería Electro-Fotónica, CUCEI, Universidad de Guadalajara, Guadalajara, MexicoSchool of Engineering and Materials Science, Queen Mary University, London, EnglandSchool of Engineering and Materials Science, Queen Mary University, London, EnglandSchool of Engineering and Materials Science, Queen Mary University, London, EnglandTotal Hip Arthroplasty (THA) is one of the most performed surgical procedures to treat osteoarthritis of the hip joint or other skeletal disorders, such as Developmental Dysplasia of the Hip (DDH) or malformations. The purpose of the THA is to replace damaged bone/cartilage and recover the biomechanics of the joint in the best possible way. Placing hip prostheses is common practice in the treatment of THA, but the effect of this treatment must be evaluated before surgery. This work proposes a method to assess hip deformation with an implanted acetabular cup, using digital image processing and multivariate linear regression. Images were acquired when a hemipelvis was subjected to mechanical load ranging from 0 to 1800 Newtons. Eighteen geometric characteristics were analyzed, and only seven were significant in the multivariate linear regression model. To decide on the variables that are considered important, three criteria were used on the multivariate linear regression model established in the different characteristics. The first criterion considers the significance of the model coefficients; the second criterion considers a coefficient of determination greater than 75%, and the third criterion considers that the proposed model is significant. If all three criteria are met, the response variable is considered significant. This analysis gives specialists a tool to make decisions before performing THA treatment. Moreover, this methodology could be applied to assess the deformation of the hip with different pathologies such as DDH, malformations, and overweight conditions. Finally, a relationship is generated between the extracted geometric characteristics and the experimental results obtained in the laboratory.https://ieeexplore.ieee.org/document/10767137/Image processingmultivariate regression analysistotal hip arthroplasty |
| spellingShingle | Jorge Ramos-Frutos Israel Miguel-Andres Diego Oliva Marco Perez-Cisneros Teresa Alonso-Rasgado Colin G. Bailey Jose Francisco del Valle-Mojica Digital Image Processing Applied in the Deformation Analysis of Hip Prosthesis: Multivariate Regression Analysis IEEE Access Image processing multivariate regression analysis total hip arthroplasty |
| title | Digital Image Processing Applied in the Deformation Analysis of Hip Prosthesis: Multivariate Regression Analysis |
| title_full | Digital Image Processing Applied in the Deformation Analysis of Hip Prosthesis: Multivariate Regression Analysis |
| title_fullStr | Digital Image Processing Applied in the Deformation Analysis of Hip Prosthesis: Multivariate Regression Analysis |
| title_full_unstemmed | Digital Image Processing Applied in the Deformation Analysis of Hip Prosthesis: Multivariate Regression Analysis |
| title_short | Digital Image Processing Applied in the Deformation Analysis of Hip Prosthesis: Multivariate Regression Analysis |
| title_sort | digital image processing applied in the deformation analysis of hip prosthesis multivariate regression analysis |
| topic | Image processing multivariate regression analysis total hip arthroplasty |
| url | https://ieeexplore.ieee.org/document/10767137/ |
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