X‐ray with finite element analysis is a viable alternative for MRI to predict knee osteoarthritis: Data from the Osteoarthritis Initiative
Magnetic resonance imaging (MRI) offers superior soft tissue contrast compared to clinical X‐ray imaging methods, while also providing accurate three‐dimensional (3D) geometries, it could be reasoned to be the best imaging modality to create 3D finite element (FE) geometries of the knee joint. Howev...
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Published in | Journal of orthopaedic research Vol. 42; no. 9; pp. 1964 - 1973 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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United States
01.09.2024
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Abstract | Magnetic resonance imaging (MRI) offers superior soft tissue contrast compared to clinical X‐ray imaging methods, while also providing accurate three‐dimensional (3D) geometries, it could be reasoned to be the best imaging modality to create 3D finite element (FE) geometries of the knee joint. However, MRI may not necessarily be superior for making tissue‐level FE simulations of internal stress distributions within knee joint, which can be utilized to calculate subject‐specific risk for the onset and development of knee osteoarthritis (KOA). Specifically, MRI does not provide any information about tissue stiffness, as the imaging is usually performed with the patient lying on their back. In contrast, native X‐rays taken while the patient is standing indirectly reveal information of the overall health of the knee that is not seen in MRI. To determine the feasibility of X‐ray workflow to generate FE models based on the baseline information (clinical image data and subject characteristics), we compared MRI and X‐ray‐based simulations of volumetric cartilage degenerations (N = 1213) against 8‐year follow‐up data. The results suggest that X‐ray‐based predictions of KOA are at least as good as MRI‐based predictions for subjects with no previous knee injuries. This finding may have important implications for preventive care, as X‐ray imaging is much more accessible than MRI. |
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AbstractList | Magnetic resonance imaging (MRI) offers superior soft tissue contrast compared to clinical X-ray imaging methods, while also providing accurate three-dimensional (3D) geometries, it could be reasoned to be the best imaging modality to create 3D finite element (FE) geometries of the knee joint. However, MRI may not necessarily be superior for making tissue-level FE simulations of internal stress distributions within knee joint, which can be utilized to calculate subject-specific risk for the onset and development of knee osteoarthritis (KOA). Specifically, MRI does not provide any information about tissue stiffness, as the imaging is usually performed with the patient lying on their back. In contrast, native X-rays taken while the patient is standing indirectly reveal information of the overall health of the knee that is not seen in MRI. To determine the feasibility of X-ray workflow to generate FE models based on the baseline information (clinical image data and subject characteristics), we compared MRI and X-ray-based simulations of volumetric cartilage degenerations (N = 1213) against 8-year follow-up data. The results suggest that X-ray-based predictions of KOA are at least as good as MRI-based predictions for subjects with no previous knee injuries. This finding may have important implications for preventive care, as X-ray imaging is much more accessible than MRI.Magnetic resonance imaging (MRI) offers superior soft tissue contrast compared to clinical X-ray imaging methods, while also providing accurate three-dimensional (3D) geometries, it could be reasoned to be the best imaging modality to create 3D finite element (FE) geometries of the knee joint. However, MRI may not necessarily be superior for making tissue-level FE simulations of internal stress distributions within knee joint, which can be utilized to calculate subject-specific risk for the onset and development of knee osteoarthritis (KOA). Specifically, MRI does not provide any information about tissue stiffness, as the imaging is usually performed with the patient lying on their back. In contrast, native X-rays taken while the patient is standing indirectly reveal information of the overall health of the knee that is not seen in MRI. To determine the feasibility of X-ray workflow to generate FE models based on the baseline information (clinical image data and subject characteristics), we compared MRI and X-ray-based simulations of volumetric cartilage degenerations (N = 1213) against 8-year follow-up data. The results suggest that X-ray-based predictions of KOA are at least as good as MRI-based predictions for subjects with no previous knee injuries. This finding may have important implications for preventive care, as X-ray imaging is much more accessible than MRI. Magnetic resonance imaging (MRI) offers superior soft tissue contrast compared to clinical X-ray imaging methods, while also providing accurate three-dimensional (3D) geometries, it could be reasoned to be the best imaging modality to create 3D finite element (FE) geometries of the knee joint. However, MRI may not necessarily be superior for making tissue-level FE simulations of internal stress distributions within knee joint, which can be utilized to calculate subject-specific risk for the onset and development of knee osteoarthritis (KOA). Specifically, MRI does not provide any information about tissue stiffness, as the imaging is usually performed with the patient lying on their back. In contrast, native X-rays taken while the patient is standing indirectly reveal information of the overall health of the knee that is not seen in MRI. To determine the feasibility of X-ray workflow to generate FE models based on the baseline information (clinical image data and subject characteristics), we compared MRI and X-ray-based simulations of volumetric cartilage degenerations (N = 1213) against 8-year follow-up data. The results suggest that X-ray-based predictions of KOA are at least as good as MRI-based predictions for subjects with no previous knee injuries. This finding may have important implications for preventive care, as X-ray imaging is much more accessible than MRI. Magnetic resonance imaging (MRI) offers superior soft tissue contrast compared to clinical X‐ray imaging methods, while also providing accurate three‐dimensional (3D) geometries, it could be reasoned to be the best imaging modality to create 3D finite element (FE) geometries of the knee joint. However, MRI may not necessarily be superior for making tissue‐level FE simulations of internal stress distributions within knee joint, which can be utilized to calculate subject‐specific risk for the onset and development of knee osteoarthritis (KOA). Specifically, MRI does not provide any information about tissue stiffness, as the imaging is usually performed with the patient lying on their back. In contrast, native X‐rays taken while the patient is standing indirectly reveal information of the overall health of the knee that is not seen in MRI. To determine the feasibility of X‐ray workflow to generate FE models based on the baseline information (clinical image data and subject characteristics), we compared MRI and X‐ray‐based simulations of volumetric cartilage degenerations ( N = 1213) against 8‐year follow‐up data. The results suggest that X‐ray‐based predictions of KOA are at least as good as MRI‐based predictions for subjects with no previous knee injuries. This finding may have important implications for preventive care, as X‐ray imaging is much more accessible than MRI. |
Author | Mononen, Mika E. Liukkonen, Mimmi K. Turunen, Mikael J. |
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Snippet | Magnetic resonance imaging (MRI) offers superior soft tissue contrast compared to clinical X‐ray imaging methods, while also providing accurate... Magnetic resonance imaging (MRI) offers superior soft tissue contrast compared to clinical X-ray imaging methods, while also providing accurate... |
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SubjectTerms | finite element analysis knee osteoarthritis prediction X‐ray |
Title | X‐ray with finite element analysis is a viable alternative for MRI to predict knee osteoarthritis: Data from the Osteoarthritis Initiative |
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