NDLI: Ultrasound observation of GAG content of human hip joint cartilage in different old age groups

Content Provider	IEEE Xplore Digital Library
Author	Pengling Ren Xiaofei Li Fan Fan Xiran Cai He Gong Yubo Fan Haijun Niu
Copyright Year	2015
Description	Author affiliation: Key Lab. of Minist. of Educ. for Biomech. & Mechanobiology, Beihang Univ., Beijing, China (Pengling Ren; Xiaofei Li; Fan Fan; Xiran Cai; He Gong; Yubo Fan; Haijun Niu)
Abstract	In this study, we observed the age-related changes of glycosaminoglycan (GAG) content of human hip joint cartilage based on ultrasound (US). Seventy human hip cartilage-bone samples were collected from hip-fracture patients (ages 51 to 96) and divided into 5 groups (10 years in an age group). They were firstly measured by ultrasound to obtain quantitative acoustic parameters, including the speed of sound (SOS), US amplitude attenuation coefficient (UAA) and normalized broadband US attenuation coefficient (nBUA). Then the samples were stained for GAG with toluidine blue. Results showed SOS, UAA, nBUA decreased by 5.49%, 36.67%, 25.57% from 50-80 age group (p<;0.01), but increased by 0.34%, 1.19%, 5.23% in the 90 age group compared with the 80 age group, respectively. There were linear correlations between SOS and GAG optical density (r=0.825, p<;0.01), as well as UAA and GAG optical density (r=0.708, p <; 0.01). However, nBUA showed less significant linear correlation to GAG optical density (r=0.688, p <; 0.07). In summary, GAG content of hip joint cartilage varied with aging in elderly people and conventional ultrasound can potentially be used to detect the age-related changes of acoustic parameters of human hip joint cartilage.
Starting Page	2697
Ending Page	2700
File Size	700828
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7318948
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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