Effect of image-based personalization of knee muscles on medial and lateral knee contact forces during daily activities: a musculoskeletal modeling analysis on patients with varus malalignment and knee osteoarthritis

In computational bioengineering, particularly for practical applications in the medical and rehabilitative fields, significant interest is focused on musculoskeletal (MSK) modeling. Specifically, efforts are being made to develop personalized MSK models based on patient's physiological and anthropometric characteristics and properties. These models allow for movement analysis potentially capable of reliably predicting the biomechanical behavior of the human body and, consequently, of producing results that closely resemble physiological conditions. In this thesis work, starting from magnetic resonance imaging (MRI) of patients affected by knee varus deformity, personalized MSK models were developed with subject-specific muscle insertions in the anatomical region of interest. To achieve this, a specific workflow has been developed, optimized, and subsequently implemented. The objective is to evaluate the impact of image-based personalization of the MSK model on the prediction of medial and lateral knee contact forces during motion simulations, and therefore to assess the reliability of the patient-specific model by comparing its results with the patient’s electromyographic (EMG) data.