Personalized prediction of knee ligaments mechanical properties using MR images

Finished: 2021-07-09

MSc assignment

Computational models for personalized knee joint surgery pre-planning relies on the study and observation of the main tibiofemoral ligaments. In-vivo applications are limited by the non-applicable standard techniques of assessing the mechanical stiffness and rupture force of the abovementioned tissues that are commonly performed in vitro. This limits the achievement of noninvasive approaches for properties estimation based on knee laxity in clinical implementation. Magnetic resonance imaging (MRI) of the knee is the standard-of-care imaging modality to evaluate knee disorders and more musculoskeletal (MSK) MRI examinations are performed on the knee than on any other region of the body.

Due to the quantity and detail of images in each knee MRI exam, accurate interpretation of knee MRI is time-intensive and prone to inter- and intra-reviewer variability, even when performed by specialized radiologists.

In a recent study, it’s been explored the potential role of quantitative MRI and dimensional properties, in characterizing the mechanical properties of the main tibiofemoral ligaments. After MR scanning of cadaveric legs, all the main tibiofemoral bone-ligaments-bone specimens were tested in vitro. The digital image correlation technique was implemented to check the strain behaviour of the specimen and rupture region and to assure the fixation of the ligament bony block during the test. Linear mixed statistical models for repeated measures were used to examine the association of MRI parameters and dimensional measurements with the mechanical properties (stiffness and rupture force). The study revealed the potentials of using quantitative MR parameters combined with specimen volume to estimate the essential mechanical properties of all main tibiofemoral ligaments required for subject-specific computational modelling of the human knee joint.