Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI
The early assessment of osteoarthritis is very crucial since articular cartilage has a very limited ability to regenerate and self-repair as the degeneration happened. Thus, MRI is the most important imaging modality for cartilage evaluation among all the other methods used to diagnose osteoarthriti...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | Article |
Published: |
Universiti Malaysia Perlis
2022
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/98652/ http://dspace.unimap.edu.my:80/xmlui/handle/123456789/75968 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.98652 |
---|---|
record_format |
eprints |
spelling |
my.utm.986522023-01-30T04:16:23Z http://eprints.utm.my/id/eprint/98652/ Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI Hamshary, F. A. S. Latif, M .J. A. Zakaria, M. S. Harun, M. N. Mahmud, J. Nguyen, H. Q. TJ Mechanical engineering and machinery The early assessment of osteoarthritis is very crucial since articular cartilage has a very limited ability to regenerate and self-repair as the degeneration happened. Thus, MRI is the most important imaging modality for cartilage evaluation among all the other methods used to diagnose osteoarthritis. However, the cartilage image obtain from low-field MRI is still uncertain particularly in quantitative assessment. Hence this study aims to determine the effect of dehydration on the correlation between grayscale MRI image and biomechanical properties of articular cartilage. In this study, the cartilage specimens were obtained from bovine femoral head which were dehydrate in stages in terms of time expose to room temperature. The specimens were then scanned at every dehydration stage using 0.2 T MRI to obtain the cartilage image and characterized the image based on the grayscale’s intensity. Subsequently, indentation test was conducted on specimens at every dehydration level to determine the cartilage biphasic properties of elastic modulus and permeability. The finding showed that the grayscale of cartilage had a moderate correlation with the cartilage biphasic elastic modulus and permeability. More importantly the low-field MRI was able to indicate the high rate of articular cartilage ability to loss its water content. Universiti Malaysia Perlis 2022-03 Article PeerReviewed Hamshary, F. A. S. and Latif, M .J. A. and Zakaria, M. S. and Harun, M. N. and Mahmud, J. and Nguyen, H. Q. (2022) Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI. International Journal of Nanoelectronics and Materials, 15 . pp. 259-269. ISSN 1985 5761 http://dspace.unimap.edu.my:80/xmlui/handle/123456789/75968 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
topic |
TJ Mechanical engineering and machinery |
spellingShingle |
TJ Mechanical engineering and machinery Hamshary, F. A. S. Latif, M .J. A. Zakaria, M. S. Harun, M. N. Mahmud, J. Nguyen, H. Q. Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI |
description |
The early assessment of osteoarthritis is very crucial since articular cartilage has a very limited ability to regenerate and self-repair as the degeneration happened. Thus, MRI is the most important imaging modality for cartilage evaluation among all the other methods used to diagnose osteoarthritis. However, the cartilage image obtain from low-field MRI is still uncertain particularly in quantitative assessment. Hence this study aims to determine the effect of dehydration on the correlation between grayscale MRI image and biomechanical properties of articular cartilage. In this study, the cartilage specimens were obtained from bovine femoral head which were dehydrate in stages in terms of time expose to room temperature. The specimens were then scanned at every dehydration stage using 0.2 T MRI to obtain the cartilage image and characterized the image based on the grayscale’s intensity. Subsequently, indentation test was conducted on specimens at every dehydration level to determine the cartilage biphasic properties of elastic modulus and permeability. The finding showed that the grayscale of cartilage had a moderate correlation with the cartilage biphasic elastic modulus and permeability. More importantly the low-field MRI was able to indicate the high rate of articular cartilage ability to loss its water content. |
format |
Article |
author |
Hamshary, F. A. S. Latif, M .J. A. Zakaria, M. S. Harun, M. N. Mahmud, J. Nguyen, H. Q. |
author_facet |
Hamshary, F. A. S. Latif, M .J. A. Zakaria, M. S. Harun, M. N. Mahmud, J. Nguyen, H. Q. |
author_sort |
Hamshary, F. A. S. |
title |
Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI |
title_short |
Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI |
title_full |
Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI |
title_fullStr |
Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI |
title_full_unstemmed |
Effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field MRI |
title_sort |
effect of water content on correlation of biomechanical properties and grayscale of articular cartilage using low-field mri |
publisher |
Universiti Malaysia Perlis |
publishDate |
2022 |
url |
http://eprints.utm.my/id/eprint/98652/ http://dspace.unimap.edu.my:80/xmlui/handle/123456789/75968 |
_version_ |
1756684239065055232 |
score |
13.211869 |