Measuring Knee Joint Laxity in Three Degrees-of-Freedom In Vivo Using a Robotics- and Image-Based Technology.

Accurate and reliable information about three-dimensional (3D) knee joint laxity can prevent misdiagnosis and avoid incorrect treatments. Nevertheless, knee laxity assessments presented in the literature suffer from significant drawbacks such as soft tissue artifacts, restricting the knee within the measurement, and the absence of quantitative knee ligament property information. In this study, we demonstrated the applicability of a novel methodology for measuring 3D knee laxity, combining robotics- and image-based technology. As such technology has never been applied to healthy living subjects, the aims of this study were to develop novel technology to measure 3D knee laxity in vivo and to provide proof-of-concept 3D knee laxity measurements. To measure tibiofemoral movements, four healthy subjects were placed on a custom-built arthrometer located inside a low dose biplanar X-ray system with an approximately 60 deg knee flexion angle. Anteroposterior and mediolateral translation as well as internal and external rotation loads were subsequently applied to the unconstrained leg, which was placed inside a pneumatic cast boot. Bone contours were segmented in the obtained X-rays, to which subject-specific bone geometries from magnetic resonance imaging (MRI) scans were registered. Afterward, tibiofemoral poses were computed. Measurements of primary and secondary laxity revealed considerable interpersonal differences. The method differs from those available by the ability to accurately track secondary laxity of the unrestricted knee and to apply coupled forces in multiple planes. Our methodology can provide reliable information for academic knee ligament research as well as for clinical diagnostics in the future.

Development and Evaluation of a Subject-Specific Lower Limb Model With an Eleven-Degrees-of-Freedom Natural Knee Model Using Magnetic Resonance and Biplanar X-Ray Imaging During a Quasi-Static Lunge.

Musculoskeletal (MS) models can be used to study the muscle, ligament, and joint mechanics of natural knees. However, models that both capture subject-specific geometry and contain a detailed joint model do not currently exist. This study aims to first develop magnetic resonance image (MRI)-based subject-specific models with a detailed natural knee joint capable of simultaneously estimating in vivo ligament, muscle, tibiofemoral (TF), and patellofemoral (PF) joint contact forces and secondary joint kinematics. Then, to evaluate the models, the predicted secondary joint kinematics were compared to in vivo joint kinematics extracted from biplanar X-ray images (acquired using slot scanning technology) during a quasi-static lunge. To construct the models, bone, ligament, and cartilage structures were segmented from MRI scans of four subjects. The models were then used to simulate lunges based on motion capture and force place data. Accurate estimates of TF secondary joint kinematics and PF translations were found: translations were predicted with a mean difference (MD) and standard error (SE) of 2.13 ± 0.22 mm between all trials and measures, while rotations had a MD ± SE of 8.57 ± 0.63 deg. Ligament and contact forces were also reported. The presented modeling workflow and the resulting knee joint model have potential to aid in the understanding of subject-specific biomechanics and simulating the effects of surgical treatment and/or external devices on functional knee mechanics on an individual level.