Unicompartmental knee arthroplasty (UKA) has become a popular method of treating knee localized osteoarthritis (OA). Additionally, the posterior cruciate ligament (PCL) is essential to maintaining the physiological kinematics and functions of the knee joint. Considering these factors, the purpose of this study was to investigate the biomechanical effects on PCL-deficient knees in medial UKA. Computational simulations of five subject-specific models were performed for intact and PCL-deficient UKA with tibial slopes. Anteroposterior (AP) kinematics and contact stresses of the patellofemoral (PF) joint and the articular cartilage were evaluated under the deep-knee-bend condition.Aims
Methods
The aim of this study was to investigate the biomechanical effect of the anterolateral ligament (ALL), anterior cruciate ligament (ACL), or both ALL and ACL on kinematics under dynamic loading conditions using dynamic simulation subject-specific knee models. Five subject-specific musculoskeletal models were validated with computationally predicted muscle activation, electromyography data, and previous experimental data to analyze effects of the ALL and ACL on knee kinematics under gait and squat loading conditions.Objectives
Methods
The use of the haptically bounded saw blades in robotic-assisted total knee arthroplasty (RTKA) can potentially help to limit surrounding soft-tissue injuries. However, there are limited data characterizing these injuries for cruciate-retaining (CR) TKA with the use of this technique. The objective of this cadaver study was to compare the extent of soft-tissue damage sustained through a robotic-assisted, haptically guided TKA (RATKA) A total of 12 fresh-frozen pelvis-to-toe cadaver specimens were included. Four surgeons each prepared three RATKA and three MTKA specimens for cruciate-retaining TKAs. A RATKA was performed on one knee and a MTKA on the other. Postoperatively, two additional surgeons assessed and graded damage to 14 key anatomical structures in a blinded manner. Kruskal–Wallis hypothesis tests were performed to assess statistical differences in soft-tissue damage between RATKA and MTKA cases.Objectives
Methods
Posterior condylar offset (PCO) and posterior tibial slope (PTS) are critical factors in total knee arthroplasty (TKA). A computational simulation was performed to evaluate the biomechanical effect of PCO and PTS on cruciate retaining TKA. We generated a subject-specific computational model followed by the development of ± 1 mm, ± 2 mm and ± 3 mm PCO models in the posterior direction, and -3°, 0°, 3° and 6° PTS models with each of the PCO models. Using a validated finite element (FE) model, we investigated the influence of the changes in PCO and PTS on the contact stress in the patellar button and the forces on the posterior cruciate ligament (PCL), patellar tendon and quadriceps muscles under the deep knee-bend loading conditions.Objectives
Methods
Subtotal or total meniscectomy in the medial or lateral compartment
of the knee results in a high risk of future osteoarthritis. Meniscal
allograft transplantation has been performed for over thirty years
with the scientifically plausible hypothesis that it functions in
a similar way to a native meniscus. It is thought that a meniscal
allograft transplant has a chondroprotective effect, reducing symptoms
and the long-term risk of osteoarthritis. However, this hypothesis has
never been tested in a high-quality study on human participants.
This study aims to address this shortfall by performing a pilot
randomised controlled trial within the context of a comprehensive
cohort study design. Patients will be randomised to receive either meniscal transplant
or a non-operative, personalised knee therapy program. MRIs will
be performed every four months for one year. The primary endpoint
is the mean change in cartilage volume in the weight-bearing area
of the knee at one year post intervention. Secondary outcome measures
include the mean change in cartilage thickness, T2 maps, patient-reported
outcome measures, health economics assessment and complications.Objectives
Methods
