Emily J. Miller

Tibiofemoral alignment in posterior stabilized total knee arthroplasty: Static alignment does not predict dynamic tibial plateau loading.

For total knee arthroplasty (TKA), neutral mechanical alignment produces balanced static knee loading. Dynamically, knee loading is affected by more than limb static alignment. We compared static and dynamic knee loading following TKA. Fifteen TKA patients were evaluated pre‐operatively and 2 months and 2 years post‐operatively. Tibiofemoral angles and medial tibial plateau loading were calculated. Pre‐operatively, static medial load was greater for varus than valgus knees. Post‐operatively, no relationship existed between tibiofemoral angle and static medial plateau load. Pre‐operatively and post‐operatively, dynamic medial load was not dependent on tibiofemoral angle. While all patients achieved equal static plateau load distributions at 2 years, only 47% had dynamic medial load distributions of 50 ± 10%. Static tibiofemoral alignment alone does not predict dynamic tibial loading.

Reliability of 3D gait data across multiple laboratories

The aim of this study was to analyze the repeatability of gait analysis studies performed across multiple trials, sessions, and laboratories. Ten healthy participants (6 male/4 female, mean age of 30, mean BMI of 24kg/m(2)) were assessed in 3 sessions conducted at each of the three Centers of Excellence for Amputee Care within the Department of Defense. For each test session, kinematic and kinetic parameters were collected during five walking trials for each limb. One independent examiner at each site placed markers on the subjects. Biomechanical data were collected at two walking speeds: self-selected and Froude speed. Variability of the gait data was attributed to inter-trial, inter-session, and inter-lab errors for each subject. These error sources were averaged across all ten subjects to obtain a pooled error estimate. The kinematic errors were fairly consistent at the two walking speeds tested. Median inter-lab kinematic errors were <5.0° (median 2.3°) for all joint angle measurements. However, the kinetic error differed significantly between walking speeds. The median inter-lab kinetic error for the self-selected speed was 0.112Nm/kg (ICR 0.091-0.184) with a maximum of 0.226Nm/kg. The errors were greatly reduced when the subjects walked at their Froude speed. The median inter-lab error was 0.048Nm/kg (ICR 0.025-0.078, maximum 0.086). These data demonstrate that it is possible to get reliable data across multiple gait laboratories, particularly when gait speed is standardized across testing sessions. A key similarity between sites was the use of identical anatomical segment definitions for the respective gait models.

Mechanical testing for three-dimensional motion analysis reliability

The purpose of this study was to use simple mechanical tests to evaluate the reliability of three-dimensional motion analysis systems and biomechanical models. Three different tests were conducted at four motion analysis laboratories where clinical care and research studies are routinely performed. The laboratories had different motion capture systems, different types and number of cameras, different types and numbers of force plates and different biomechanical models. These mechanical tests evaluated the accuracy of the motion capture system, the integration of the force plate and the motion capture system, and the strength of the biomechanical model used to calculate rotational kinematics. Results of motion capture system accuracy tests showed that, for all labs, the error between the measured and calculated distances between markers was less than 2mm and 1° for marker separations which ranged from 24mm to 500mm. Results from the force plate integration tests demonstrated errors in center of pressure calculation of less than 4mm across all labs, despite varied force plate and motion system configurations. Finally, errors across labs for single joint rotations and for combined rotations at the hip and knee were less than 2° at the hip and less than 10° at the knee. These results demonstrate that system accuracy and reliability can be obtained allowing the collection of comparable data across different motion analysis laboratories with varying configurations and equipment. This testing is particularly important when multi-center studies are planned in order to assure data consistency across labs.

Static and dynamic validation of inertial measurement units

Optical motion capture systems are used to assess human motion. While these systems provide a reliable analysis, they limit collection to a laboratory based setting. Devices such as Inertial Measurement Units (IMUs) have been developed as alternative tools. Commercially available IMUs are utilized for a variety of applications; however limited work has been done to determine the reliability of these devices. The objective of this study was to assess the accuracy and precision of a commercially available IMU, containing tri-axial accelerometers, gyroscopes, and magnetometers, under controlled static and dynamic conditions. The sensor output was validated against the gold standard measures of custom made mechanical testing apparatuses. The IMUs provide an accurate (within 0.6°) and precise (within 0.1°) measurement of static sensor orientation and an accurate (within 4.4° per second) and precise (within 0.2° per second) representation of angular velocity. The sensors are more accurate at lower velocities, but the percent error remains relatively constant across all angular velocities. Inclusion of IMUs as an appropriate measurement tool should be based on the application, specific demands and necessary reliability.

A principal component analysis approach to correcting the knee flexion axis during gait

Accurate and precise knee flexion axis identification is critical for prescribing and assessing tibial and femoral derotation osteotomies, but is highly prone to marker misplacement-induced error. The purpose of this study was to develop an efficient algorithm for post-hoc correction of the knee flexion axis and test its efficacy relative to other established algorithms. Gait data were collected on twelve healthy subjects using standard marker placement as well as intentionally misplaced lateral knee markers. The efficacy of the algorithm was assessed by quantifying the reduction in knee angle errors. Crosstalk error was quantified from the coefficient of determination (r(2)) between knee flexion and adduction angles. Mean rotation offset error (αo) was quantified from the knee and hip rotation kinematics across the gait cycle. The principal component analysis (PCA)-based algorithm significantly reduced r(2) (p<0.001) and caused αo,knee to converge toward 11.9±8.0° of external rotation, demonstrating improved certainty of the knee kinematics. The within-subject standard deviation of αo,hip between marker placements was reduced from 13.5±1.5° to 0.7±0.2° (p<0.001), demonstrating improved precision of the knee kinematics. The PCA-based algorithm performed at levels comparable to a knee abduction-adduction minimization algorithm (Baker et al., 1999) and better than a null space algorithm (Schwartz and Rozumalski, 2005) for this healthy subject population.

Verification of an improved hip joint center prediction method

In motion analysis, the hip joint center (HJC) is used to define the proximal location of the thigh segment and is also the point about which hip moments are calculated. The HJC cannot be palpated; its location must be calculated. Functional methods have been proposed but are difficult to perform by some clinical populations. Therefore, regression methods are utilized, but yield large errors in estimating the HJC location. These prediction methods typically utilize the anterior and posterior superior iliac spines, where excessive adipose tissue makes correctly locating difficult. A new regression method (Hara) utilizes leg length and has been shown to improve HJC location in cadavers and less error than previous pelvic based regression methods, such as those proposed by Harrington et al. This study compared the accuracy of the HJC location calculated with both of the Harrington methods and the Hara method. The coronal knee angle was calculated for each method using a static motion analysis trial, and compared to the tibiofemoral angle measured on a gold standard digital full-leg coronal radiograph. This study demonstrated that the Hara method was more accurate than either of the Harrington methods. The mean error between the gold standard x-ray measurement and the motion analysis calculation for the Harrington (stepwise and LOOCV), the Harrington (linear regression), and Hara regression methods, respectively were 6.0°, 4.0°, and 1.8°. Accurately modeling the HJC is critical for data interpretation and patient care. This study confirmed that the Hara HJC regression method is valid in an in-vivo setting.

Tibiofemoral Alignment for Total Knee Arthroplasty: Differences Between Static and Dynamic Tibial Plateau Loading

The surgical goal in total knee arthroplasty (TKA) is to obtain neutral mechanical alignment within three degrees [4]. This has been considered necessary to achieve optimal function, produce balanced medial and lateral loading distributions, and prolong implant longevity [7]. Under static loading, tibial-femoral alignment angle deviations of 3° have been shown to greatly alter the distribution of pressure and load between the medial and lateral tibial plateaus [13]. However, other studies have challenged the practice that coronal tibiofemoral alignment improves implant longevity [9,10]. These studies did not show a statistical difference in the number of revision surgeries between well aligned knees and mechanical alignment outliers (varus/valgus knees). While it has been suggested that accurate alignment allows for improved joint kinematics and improved outcomes in TKA patients [6], no studies have evaluated the effect of tibial-femoral alignment on tibial plateau loading distribution during gait in the TKA population. Therefore, the purpose of this study was to assess tibial plateau loading following TKA.Copyright

Internal Pressure in Human Meniscal Attachments Subjected to Physiological Loading

Meniscal attachments serve to anchor and transfer loads from menisci to the tibia. These ligamentous tissues are composed of collagen fibers, elastin, ground substance and water. Ligaments have a time- and history-dependent viscoelastic behavior due in part to the interaction of the water and the ground substance [1]. The movement of water within ligamentous tissue is limited because of charged proteoglycan molecules. It has been shown that some exudation of water is present during cyclic loading of ligamentous tissue [2]. The movement and its inhibition could lead to changes of pressure within the meniscal attachments. Therefore, the purpose of this study was to quantify the internal pressure in human meniscal attachments subjected to physiological loading. Since it is thought that the posterior attachment is subjected to both tension and compression, while the anterior attachment is primarily subjected to tension [3–5], we hypothesized that the attachments mechanical environment is dictated by the external loads, and hence, the posterior attachment would elicit higher pressures.Copyright