Specimen-Specific Natural, Pathological, and Implanted Knee Mechanics Using Finite Element Modeling

There is an increasing incidence of knee pain and injury among the population, and increasing demand for higher knee function in total knee replacement designs. As a result, clinicians and implant manufacturers are interested in improving patient outcomes, and evaluation of knee mechanics is essential for better diagnosis and repair of knee pathologies. Common knee pathologies include osteoarthritis (degradation of the articulating surfaces), patellofemoral pain, and cruciate ligament injury and/or rupture. The complex behavior of knee motion presents unique challenges in the diagnosis of knee pathology and restoration of healthy knee function. Quantifying knee mechanics is essential for developing successful rehabilitation therapies and surgical treatments. Researchers have used in-vitro and in-vivo experiments to quantify joint kinematics and loading, but experiments can be costly and time-intensive, and contact and ligament mechanics can be difficult to measure directly. Computational modeling can complement experimental studies by providing cost-effective solutions for quantifying joint and soft tissue forces. Musculoskeletal models have been used to measure whole-body motion, and predict joint and muscle forces, but these models can lack detail and accuracy at the joint-level. Finite element modeling provides accurate solutions of the internal stress/strain behavior of bone and soft tissue using subject-specific geometry and complex contact and material representations. While previous FE modeling has been used to simulate injury and repair, models are commonly based on literature description or average knee behavior. The research presented in this dissertation focused on developing subject-specific representations of the TF and PF joints including calibration and validation to experimental data for healthy, pathological, and implanted knee conditions. A combination of in-vitro experiment and modeling was used to compare healthy and cruciate-deficient joint mechanics, and develop subject-specific computational representations. Insight from in-vitro testing supported in-vivo simulations of healthy and implanted subjects, in which PF mechanics were compared between two common patellar component designs and the impact of cruciate ligament variability on joint kinematics and loads was assessed. The suite of computational models developed in this dissertation can be used to investigate knee pathologies to better inform clinicians on the mechanisms surrounding injury, support the diagnosis of at-risk patients, explore rehabilitation and surgical techniques for repair, and support decision-making for new innovative implant designs

Development and Assessment of a Micro-CT Based System for Quantifying Loaded Knee Joint Kinematics and Tissue Mechanics

Although anterior cruciate ligament (ACL) reconstruction is a highly developed surgical procedure, sub-optimal treatment outcomes persist. This can be partially attributed to an incomplete understanding of knee joint kinematics and regional tissue mechanic properties. A system for minimally-invasive investigation of knee joint kinematics and tissue mechanics under clinically relevant joint loads was developed to address this gap in understanding. A five degree-of-freedom knee joint motion simulator capable of dynamically loading intact human cadaveric knee joints to within 1% of user defined multi-axial target loads was developed. This simulator was uniquely designed to apply joint loads to a joint centered within the field of view of a micro-CT scanner. The use of micro-CT imaging and tissue-embedded radiopaque beads demonstrated high-resolution strain measurement, distinguishing differences in inter-bead distances as low as 0.007 mm. Inter-bead strain measurement was highly accurate and repeatable, with no significant error introduced from cyclic joint loading. Finally, regional strain was repeatably measured using radiopaque markers in four intact, human cadaveric knees to within 0.003 strain in response to multi-directional joint loads. This novel combination of dynamic knee joint motion simulation, tissue-embedded radiopaque markers, and micro-CT imaging provides the opportunity to increase our understanding of the kinematics and tissue mechanics of the knee, with the potential to improve ACL reconstruction outcomes

A Principal Component Analysis Investigation of Drop Landings for Defining Anterior Cruciate Ligament Injury Risk Factors

Injury to the anterior cruciate ligament (ACL) has been widely investigated through observational video analysis and laboratory based cadaveric, motion capture and computer simulation models. With the greater incidence of injury in the female population, recent emphasis has been placed on understanding ACL injury mechanisms in females. By using our understanding of injury mechanisms and prospective studies, injury prediction methods can be created. Once injury can be reliably predicted, training methods can be implemented to reduce likelihood of injury and avoid devastating consequences. There is a need for a reliable way to reduce motion capture data obtained in a laboratory setting to viable measures that characterize the entire data set and correlate such measures to clinically relevant tests. The present study performed motion analysis on healthy active young adult females during drop jump landings to characterize normal jump landing dynamics. Kinematic and kinetic data was reduced using principal component analysis to objectively determine variables of importance. Five principal components represented a cumulative 87.41% of the data set variance. Using principal component scores, significant associations were identified between principal component four (base of support at initial contact, peak knee abduction moment and 100 ms after initial contact) and knee flexion to extension isokinetic strength ratio. Additional significant correlation was found between principal component five (initial contact coronal knee moment and transverse knee moment) and abduction to adduction isokinetic strength ratio tested at 90°/sec. These results suggest principal component analysis is a viable method to reducing dynamic motion capture data. Further, principal component scores are a possible way to predict isokinetic strength ratios obtained in the clinic

Hip joint centre position estimation using a dual unscented Kalman filter for computer-assisted orthopaedic surgery

In computer-assisted knee surgery, the accuracy of the localization of the femur centre of rotation relative to the hip-bone (hip joint centre) is affected by the unavoidable and untracked pelvic movements because only the femoral pose is acquired during passive pivoting manoeuvres. We present a dual unscented Kalman filter algorithm that allows the estimation of the hip joint centre also using as input the position of a pelvic reference point that can be acquired with a skin marker placed on the hip, without increasing the invasiveness of the surgical procedure. A comparative assessment of the algorithm was carried out using data provided by in vitro experiments mimicking in vivo surgical conditions. Soft tissue artefacts were simulated and superimposed onto the position of a pelvic landmark. Femoral pivoting made of a sequence of star-like quasi-planar movements followed by a circumduction was performed. The dual unscented Kalman filter method proved to be less sensitive to pelvic displacements, which were shown to be larger during the manoeuvres in which the femur was more adducted. Comparable accuracy between all the analysed methods resulted for hip joint centre displacements smaller than 1 mm (error: 2.2 ± [0.2; 0.3] mm, median ± [inter-quartile range 25%; inter-quartile range 75%]) and between 1 and 6 mm (error: 4.8 ± [0.5; 0.8] mm) during planar movements. When the hip joint centre displacement exceeded 6 mm, the dual unscented Kalman filter proved to be more accurate than the other methods by 30% during multi-planar movements (error: 5.2 ± [1.2; 1] mm)

A forward dynamics simulation study of increasing load on the anterior cruciate ligament of the knee, for young women performing recreational drop jump activities.

Anterior Cruciate Ligament (ACL) injuries are among the most common injuries incurred by both recreational and professional athletes. ACL injuries often occur during popular contact sports like basketball, football, volleyball and baseball, and non-contact activities like aerobics, jogging and running. Non-contact actions like jumping, sprinting and sidecutting that involve sudden or rapid changes in motion may lead to ACL injuries. At the instance of an injury, the knee joint muscles and ligaments typically undergo extremely high loads. The ACL, which is an integral part of the knee joint undergo high strain rates and rapid energy absorption, and consequently get injured. As has been shown by others, ACL injury is related to a number of dynamic variables of the knee joint. An important observation made in recent years is that recreational (also professional) female athletes have higher incidences of noncontact ACL injuries than males 33, 35. The primary focus of this study was to determine effects of several dynamic variables, associated with both knee and ACL, during normal recreational drop-jump activities performed by young female athletes. Subjects recruited were eleven young adult female recreational athletes who felt comfortable participating in the drop-jump activities, from heights of 30, 40 and 50 cm. Using a simulation environment to recreate the trials, changes in ACL load and strain were observed along with several dynamic variables related to ACL load and strain, among which the three most important were, 1. knee flexion, 2. knee valgus (abduction) which may be accompanied by increased internal rotation, and, 3. flexor to extensor muscle recruitment ratios, i.e., the co-contraction of flexor and extensor muscles. Observations from the above simulations formed the basis of the final step involving forward dynamic simulation, where the knee joint was subject to higher valgus by decreasing the distance between the knees (medial translation). Significant changes to ACL load and strain were seen in the added medial translation simulations compared to the simulations from the original jumps. Mean fiber strain for the additional valgus simulation increased from 8.82 ± 0.08 % to 11.82 ± 0.04 % for the right ACL and from 8.18 ± 0.08 % to 11.34 ± 0.06 % for the left. Mean ACL tensile force increased from 1058.19 ± 2.04 N to 1102.19 ± 1.86 N for the right ACL and from 1056.77 ± 12.36 N to 1099.99 ± 2.02 N for the left. Average peak (from eleven subjects) ACL tensile force increased from 1165.36 ± 123.83 N to 1197.07 ± 129.11 N for the right ACL and from 1160.64 ± 121.32 N to 1193.11 ± 130.16 N for the left