Features and modalities for assessing early knee osteoarthritis

Ahmad Fadzil, Mohd Hani (2011) Features and modalities for assessing early knee osteoarthritis. In: 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011, 17 July 2011 through 19 July 2011, Bandung.

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Early detection of knee osteoarthritis (OA) is of great interest to orthopaedists, rheumatologists, radiologists and researchers. It is possible to detect knee osteoarthritis by measuring changes in selected articular cartilage features using sensitive modalities. This paper identifies the modalities that can potentially assess changes in morphological, mechanical or electrical and molecular features of the articular cartilage associated with the progression of OA. From the literature, it was found that the features that undergo earliest change are surface roughness for morphology, cartilage stiffness for mechanical properties and proteoglycan content for molecular composition. However, the earliest changes that can be accurately and consistently measured using non-invasive, non-ionizing and in-vivo modalities in the relevant categories of articular cartilage features are thickness, water and proteoglycan contents. It is argued that MRI is the most suitable modality for measuring early changes in thickness, water and proteoglycan content associated with early stage of osteoarthritis progression. Recent developments in MRI software and hardware, in particular the dual tuned (1H/23Na) MRI, provides the capability to measure accurate changes in thickness, water and proteoglycan contents of articular cartilage without using any contrast enhancement agent. Therefore, future research on early osteoarthritis should focus on using MRI as a measurement tool.

Item Type: Conference or Workshop Item (Paper)
Subjects: R Medicine > RZ Other systems of medicine
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QM Human anatomy
Departments / MOR / COE: Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Electrical & Electronic Engineering
Research Institutes > Institute for Health Analytics
Depositing User: Prof Ir Dr Ahmad Fadzil Mohd Hani
Date Deposited: 21 Nov 2011 06:29
Last Modified: 19 Jan 2017 08:23
URI: http://scholars.utp.edu.my/id/eprint/6699

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