Mallikarjunaswamy Shivagangadharaiah Matada 1 , Mallikarjun Sayabanna Holi 2 , Rajesh Raman 3 , Sujana Theja Jayaramu Suvarna 4 Show Affiliations »
Abstract
BACKGROUND: Osteoarthritis (OA) is a degenerative disease of joint cartilage affecting the elderly people around the world. Visualization and quantification of cartilage is very much essential for the assessment of OA and rehabilitation of the affected people. Magnetic Resonance Imaging (MRI) is the most widely used imaging modality in the treatment of knee joint diseases. But there are many challenges in proper visualization and quantification of articular cartilage using MRI. Volume rendering and 3D visualization can provide an overview of anatomy and disease condition of knee joint. In this work, cartilage is segmented from knee joint MRI, visualized in 3D using Volume of Interest (VOI) approach. METHODS: Visualization of cartilage helps in the assessment of cartilage degradation in diseased knee joints. Cartilage thickness and volume were quantified using image processing techniques in OA affected knee joints. Statistical analysis is carried out on processed data set consisting of 110 of knee joints which include male (56) and female (54) of normal (22) and different stages of OA (88). The differences in thickness and volume of cartilage were observed in cartilage in groups based on age, gender and BMI in normal and progressive OA knee joints. RESULTS: The results show that size and volume of cartilage are found to be significantly low in OA as compared to normal knee joints. The cartilage thickness and volume is significantly low for people with age 50 years and above and Body Mass Index (BMI) equal and greater than 25. Cartilage volume correlates with the progression of the disease and can be used for the evaluation of the response to therapies. CONCLUSION: The developed methods can be used as helping tool in the assessment of cartilage degradation in OA affected knee joint patients and treatment planning. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.
BACKGROUND: Osteoarthritis (OA ) is a degenerative disease of joint cartilage affecting the elderly people around the world. Visualization and quantification of cartilage is very much essential for the assessment of OA and rehabilitation of the affected people . Magnetic Resonance Imaging (MRI) is the most widely used imaging modality in the treatment of knee joint diseases . But there are many challenges in proper visualization and quantification of articular cartilage using MRI. Volume rendering and 3D visualization can provide an overview of anatomy and disease condition of knee joint. In this work, cartilage is segmented from knee joint MRI, visualized in 3D using Volume of Interest (VOI) approach. METHODS: Visualization of cartilage helps in the assessment of cartilage degradation in diseased knee joints. Cartilage thickness and volume were quantified using image processing techniques in OA affected knee joints. Statistical analysis is carried out on processed data set consisting of 110 of knee joints which include male (56) and female (54) of normal (22) and different stages of OA (88). The differences in thickness and volume of cartilage were observed in cartilage in groups based on age , gender and BMI in normal and progressive OA knee joints. RESULTS: The results show that size and volume of cartilage are found to be significantly low in OA as compared to normal knee joints. The cartilage thickness and volume is significantly low for people with age 50 years and above and Body Mass Index (BMI) equal and greater than 25. Cartilage volume correlates with the progression of the disease and can be used for the evaluation of the response to therapies. CONCLUSION: The developed methods can be used as helping tool in the assessment of cartilage degradation in OA affected knee joint patients and treatment planning. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.
Entities: Disease
Gene
Species
Keywords:
3D visualization; Knee joint diseases; body mass index; magnetic resonance imaging; osteoarthritis
Mesh： See more »
Year: 2019
PMID： 32008564 DOI： 10.2174/1573405614666181018123251
Source DB: PubMed Journal: Curr Med Imaging Rev ISSN： 1573-4056