Osteoarthritis is the most common degenerative condition affecting the knee joint globally, with an incidence of about 7% of the population. In Italy, it affects approximately 3.9 million people, with a direct treatment cost of around €2.5 billion. At the joint level, osteoarthritis manifests with pain and reduced functionality, worsening as the disease progresses and severely limiting knee movement. Compounding this, osteoarthritis can impact both elderly and younger individuals due to traumatic factors. Despite its significant impact, effective treatments for osteoarthritis that address its underlying causes are still lacking, focusing mainly on symptom management. Therefore, improving diagnostic and prognostic approaches is crucial to better understand its onset and progression. MRI is a primary diagnostic tool for assessing the knee joint's pathophysiological state. It uses tissue-specific sequences to investigate joint homeostasis in detail, although it primarily provides insights into morphology, structure, and tissue composition rather than functional changes within the joint. This limitation is noteworthy because joint homeostasis involves complex interactions among biomechanical, structural, and biological processes, which are directly influenced by osteoarthritis. Gait analysis provides valuable diagnostic information on joint function. By integrating sensor measurements and electronic systems with patient-specific musculoskeletal models derived from MRI morphometric data, it is possible to assess the forces and moments within the joint during specific movements. Given that osteoarthritis affects the entire joint, employing multidisciplinary approaches can enhance diagnostic precision and provide insights into the progressive impact of degenerative conditions like osteoarthritis on joint health.