Knee Osteoarthritis Grading Using Mixture of Experts

Abdulkader Helwan
13 min readJan 1, 2024

Osteoarthritis (OA) of the knee is a degenerative condition affecting three knee compartments (lateral, medial, and patella-femoral), typically developing gradually throughout 10 to 15 years [1,2]. Primarily caused by wear, tear, and progressive loss of articular cartilage, it can also result from infections leading to joint cavity damage, resulting in discomforts such as limited mobility, joint pain, and swelling [3]. Cartilage tissue alterations and damage are common in all joints, with the knee and hip joints being particularly susceptible due to their weight-bearing nature. Knee OA predominantly occurs in individuals aged over 55, with a higher prevalence among those over 65, and it is estimated that by 2050, 130 million individuals globally will be affected. Early detection and treatment are crucial for mitigating the progression of knee OA and enhancing individuals’ quality of life [5].

The complexity of diagnosing and treating knee OA lies in its multifaceted nature, with numerous risk factors involved, including advanced age, gender, hormonal status, and body mass index (BMI). Additionally, various medical, environmental, and biological factors contribute to the disease’s development and progression, both modifiable and non-modifiable. In severe cases, patients with these risk factors may undergo total knee replacement. Presently, behavioral interventions such as weight loss, physical exercise, and joint muscle strengthening represent the primary therapies for individuals with knee OA. While these interventions may offer temporary pain relief and slow disease progression, there is a pressing need for more effective treatment options [6,7].

Accurate grading of knee OA is crucial for effective treatment planning and monitoring disease progression. Traditional grading systems often lack the precision required for personalized care, prompting researchers to explore advanced techniques.

In previous articles, we discussed Mixtures of Experts and provided a review of Knee Osteoarthritis using deep learning.