Cargando…

Nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle

Quantitative measurement of nanoscale surface roughness of articular cartilage tissue is significant to assess the surface topography for early treatment of osteoarthritis, the most common joint disease worldwide. Since it was not established by clinical diagnostic tools, the current studies have be...

Descripción completa

Detalles Bibliográficos
Autores principales: Youssef, Doaa, Hassab-Elnaby, Salah, El-Ghandoor, Hatem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7845957/
https://www.ncbi.nlm.nih.gov/pubmed/33513197
http://dx.doi.org/10.1371/journal.pone.0246395
_version_ 1783644650085548032
author Youssef, Doaa
Hassab-Elnaby, Salah
El-Ghandoor, Hatem
author_facet Youssef, Doaa
Hassab-Elnaby, Salah
El-Ghandoor, Hatem
author_sort Youssef, Doaa
collection PubMed
description Quantitative measurement of nanoscale surface roughness of articular cartilage tissue is significant to assess the surface topography for early treatment of osteoarthritis, the most common joint disease worldwide. Since it was not established by clinical diagnostic tools, the current studies have been suggesting the use of alternative diagnostic tools using pre-clinical methods. This study aims to measure the nanoscale surface roughness of articular cartilage tissue utilizing biospeckle which is used as a non-destructive and non-contact optical imaging technique. An experimental setup was implemented to capture biospeckle images from twelve cross-section areas of articular cartilage tissue gathered from bovine knee joints at 632 nm wavelength laser radiation. Then, to analyze the biospeckle image, a second-order statistical-based method was proposed through the combination of 308 highly correlated statistical features extracted from implemented gray-level co-occurrence matrices by employing principal component analysis. The result indicated that the measurement of the nanoscale surface roughness based on the first principal component only is able to provide accurate and precise quantitative measurement of early signs of articular cartilage degeneration up to 2500 nm.
format Online
Article
Text
id pubmed-7845957
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-78459572021-02-04 Nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle Youssef, Doaa Hassab-Elnaby, Salah El-Ghandoor, Hatem PLoS One Research Article Quantitative measurement of nanoscale surface roughness of articular cartilage tissue is significant to assess the surface topography for early treatment of osteoarthritis, the most common joint disease worldwide. Since it was not established by clinical diagnostic tools, the current studies have been suggesting the use of alternative diagnostic tools using pre-clinical methods. This study aims to measure the nanoscale surface roughness of articular cartilage tissue utilizing biospeckle which is used as a non-destructive and non-contact optical imaging technique. An experimental setup was implemented to capture biospeckle images from twelve cross-section areas of articular cartilage tissue gathered from bovine knee joints at 632 nm wavelength laser radiation. Then, to analyze the biospeckle image, a second-order statistical-based method was proposed through the combination of 308 highly correlated statistical features extracted from implemented gray-level co-occurrence matrices by employing principal component analysis. The result indicated that the measurement of the nanoscale surface roughness based on the first principal component only is able to provide accurate and precise quantitative measurement of early signs of articular cartilage degeneration up to 2500 nm. Public Library of Science 2021-01-29 /pmc/articles/PMC7845957/ /pubmed/33513197 http://dx.doi.org/10.1371/journal.pone.0246395 Text en © 2021 Youssef et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Youssef, Doaa
Hassab-Elnaby, Salah
El-Ghandoor, Hatem
Nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle
title Nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle
title_full Nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle
title_fullStr Nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle
title_full_unstemmed Nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle
title_short Nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle
title_sort nanoscale quantitative surface roughness measurement of articular cartilage using second-order statistical-based biospeckle
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7845957/
https://www.ncbi.nlm.nih.gov/pubmed/33513197
http://dx.doi.org/10.1371/journal.pone.0246395
work_keys_str_mv AT youssefdoaa nanoscalequantitativesurfaceroughnessmeasurementofarticularcartilageusingsecondorderstatisticalbasedbiospeckle
AT hassabelnabysalah nanoscalequantitativesurfaceroughnessmeasurementofarticularcartilageusingsecondorderstatisticalbasedbiospeckle
AT elghandoorhatem nanoscalequantitativesurfaceroughnessmeasurementofarticularcartilageusingsecondorderstatisticalbasedbiospeckle