Quantitative study of articular cartilage based on greyscale assessment using low-field MRI

• Main Authors: Seeni Ibramsa, Rizwana, Abd Latif, Mohd Juzaila, Zakaria, Mohamad Shukri, Harun, Muhamad Noor, Mahmud, Jamaluddin
• Format: Article
• Language: English
• Published: Insight Society 2022
• Online Access: http://eprints.utem.edu.my/id/eprint/26672/2/13107-39082-1-PB.PDF; http://eprints.utem.edu.my/id/eprint/26672/; https://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=13107
• Institution: Universiti Teknikal Malaysia Melaka

Osteoarthritis is a degenerative disorder that changes the biomechanical properties of articular cartilage in its development phase. MRI has become the diagnosing tool used widely to examine the articular cartilage in the synovial joint since it can provide excellent soft-tissue contrast. However, most diagnoses were conducted using clinical high-field MRI, while the low-field MRI was only used to obtain the geometrical data. This study aims to quantitatively assess the biomechanical properties of cartilage tissue using a low-field MRI system based on the image greyscale assessment. The articular cartilage image of intact bovine hip joints was obtained using 0.18 T MRI. The MRI images were characterized based on the intensity of the greyscale. The biomechanical properties of elastic modulus and permeability of cartilage were subsequently characterized by incorporating the creep indentation test data with the computational finite element model. Further correlation analyses were performed to examine the relationship between the greyscale of MRI images and biomechanical properties of elastic modulus and permeability of the cartilage. The cartilage greyscale was found to be strongly associated with the cartilage biphasic elastic modulus (r = 0.85), while the permeability (r = -0.51) was observed to have a moderate correlation with the greyscale. These findings show the capability of low-field MRI to produce an image that correlates with the articular cartilage's biomechanical properties, which could be adapted as a biomarker to detect osteoarthritis earlier than usual.