JOURNAL ARTICLE
CONTRAST-ENHANCED MICROTOMOGRAPHY FOR VOLUMETRIC ANALYSIS OF MICROSTRUCTURE IN LIGAMENTS AND TENDONS.
Published In: Journal of Mechanics in Medicine & Biology, 2023, v. 23, n. 6. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: BUSHARA, FATEHIA; MAGLIO, MELANIA; MARCHIORI, GREGORIO; GIAVARESI, GIANLUCA; SIGNORONI, ALBERTO; GUERRINI, FABRIZIO; LOPOMO, NICOLA FRANCESCO 3 of 3
Abstract
Tendons and ligaments play an important role to ensure mobility and stability. To correctly understand the characteristics of these fibrous collagenous connective tissues, it is fundamental to highlight their 3D microstructure. In this study a microtomography (microCT) system was used to acquire human hamstring tendons after performing specific preparations to enhance image contrast. Specifically, samples were treated either through chemical dehydration or by 2% of phosphotungstic acid (P T A) in water ( H 2 O) or in 70% ethanol (E t O H) solution. Acquired images were elaborated using dedicated techniques based on 3D Hessian multiscale filter so as to highlight the fibrous structure and identify specific geometric features. For any strategy of sample preparation, the proposed approach resulted to be adequate for identifying fascicle features, thus obtaining structures with diameter in the range of 100–600 μ m and proper longitudinal alignment. In conclusion, a novel contrast enhancement microCT protocol was designed and preliminarily validated for the microstructural analysis of fibrous tissues. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Mechanics in Medicine & Biology. 2023/08, Vol. 23, Issue 6, p1
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2023
- ISSN:0219-5194
- DOI:10.1142/S0219519423400286
- Accession Number:170031068
- Copyright Statement:Copyright of Journal of Mechanics in Medicine & Biology is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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