MRI-Based Knee Joint Laxity Measure in Healthy Individuals

A functional MRI based knee joint laxity device was developed by the current research group to enable three-dimensional (3D) evaluation of change in ligament length as a function of loading [1]. Previous studies have used the knee loading apparatus (KLA) to quantify knee joint laxity in the dominant leg of healthy individuals [1]; however anterior laxity of the knee is reported clinically as a left-right difference, and not absolute values [2]. Therefore, the purpose of this study was to quantify side-to-side differences in knee joint laxity using the KLA in a healthy population. It was hypothesized that there would be no statistically significant differences in knee joint laxity between legs for healthy individuals. One healthy female with an intact anterior cruciate ligament was recruited and tested 3 times during the span of 10 days. Magnetic Resonance (MR) imaging was used in conjunction with the KLA to obtain images of the knee joint geometry during an unloaded state and at an anterior load of 133 N. Sagittal images of the knee were manually digitized using SliceOmatic (Tomovision) to obtain 3D volumes of the femur and tibia. The displacement of the tibia at 133N was obtained from the 3D joint position of the femur relative to the tibia, specifically anterior displacement of the tibia [1]. Due to complications with data collection, results are only available for day 2 for the right leg, and days 1 and 3 for the left leg. The anterior displacement of the tibia under an anterior load of 133N was 1.29 mm for the right leg, and 0.62 ± 0.42 mm for the left leg. Due to the sample size of 1, statistical analysis was not performed. This is preliminary data; future studies will increase the number of subjects and collect data at multiple load levels

Day to Day Variability of Dynamic Knee Joint Stability in Healthy Individuals

The cause of osteoarthritis remains unknown; however abnormal joint mechanics are speculated to be an initiating factor [1]. Relating the Finite Helical Axis (FHA) to joint health may provide a means of predicting risk of joint degeneration [2]. To study dynamic knee joint stability using FHA and electromyography (EMG), it is valuable to quantify the day to day variance of these measures in a healthy population. It was hypothesized that there would be no statistically significant differences in FHA parameters or muscle patterns between days for healthy individuals. Three healthy females with intact anterior cruciate ligaments were recruited and tested 3 times during one week. Three-dimensional data for FHA determination was collected from reflective skin markers placed on each lower extremity (3 markers/segment) using an 8-camera (120 Hz) video motion capture system (Motion Analysis Corp.). A 16-channel EMG system recorded muscle activation patterns from 6 major muscles of the leg. Each subject performed two dynamic tasks: unconstrained knee flexion and extension while seated, and a single leg squat and rise. Data was analyzed using in house programs written in Matlab 7.1 (Mathworks Inc.). Four FHA parameters were described: location, translation, orientation and dispersion [2]. Muscle activity patterns were quantified using a wavelet analysis approach [3]. Due to the small sample size, a non-parametric Friedman’s test was used to detect differences in dynamic knee joint stability between days (p=0.05). Significant differences (p=0.028) were found for the extension phase of the squat in the contra lateral legs for location y, which describes the anterior/posterior location of the FHA in the knee. No significant differences were detected for any other FHA or EMG parameters. This finding suggests that the y location of the FHA during the extension phase of the squat task changes across days, and must be carefully interpreted in future studies

MODELLING ERRORS IN X-RAY FLUOROSCOPIC IMAGING SYSTEMS USING PHOTOGRAMMETRIC BUNDLE ADJUSTMENT WITH A DATA-DRIVEN SELF-CALIBRATION APPROACH

X-ray imaging is a fundamental tool of routine clinical diagnosis. Fluoroscopic imaging can further acquire X-ray images at video frame rates, thus enabling non-invasive in-vivo motion studies of joints, gastrointestinal tract, etc. For both the qualitative and quantitative analysis of static and dynamic X-ray images, the data should be free of systematic biases. Besides precise fabrication of hardware, software-based calibration solutions are commonly used for modelling the distortions. In this primary research study, a robust photogrammetric bundle adjustment was used to model the projective geometry of two fluoroscopic X-ray imaging systems. However, instead of relying on an expert photogrammetrist’s knowledge and judgement to decide on a parametric model for describing the systematic errors, a self-tuning data-driven approach is used to model the complex non-linear distortion profile of the sensors. Quality control from the experiment showed that 0.06 mm to 0.09 mm 3D reconstruction accuracy was achievable post-calibration using merely 15 X-ray images. As part of the bundle adjustment, the location of the virtual fluoroscopic system relative to the target field can also be spatially resected with an RMSE between 3.10 mm and 3.31 mm

Establishing outcome measures in early knee osteoarthritis

The classification and monitoring of individuals with early knee osteoarthritis (OA) are important considerations for the design and evaluation of therapeutic interventions and require the identification of appropriate outcome measures. Potential outcome domains to assess for early OA include patient-reported outcomes (such as pain, function and quality of life), features of clinical examination (such as joint line tenderness and crepitus), objective measures of physical function, levels of physical activity, features of imaging modalities (such as of magnetic resonance imaging) and biochemical markers in body fluid. Patient characteristics such as adiposity and biomechanics of the knee could also have relevance to the assessment of early OA. Importantly, research is needed to enable the selection of outcome measures that are feasible, reliable and validated in individuals at risk of knee OA or with early knee OA. In this Perspectives article, potential outcome measures for early symptomatic knee OA are discussed, including those measures that could be of use in clinical practice and/or the research setting

Estimation of Ground Reaction Forces in Bucking Rodeo Bulls

Ye

Toward an Automatic Calibration of Dual Fluoroscopy Imaging Systems

High-speed dual fluoroscopy (DF) imaging provides a novel, in-vivo solution to quantify the six-degree-of-freedom skeletal kinematics of humans and animals with sub-millimetre accuracy and high temporal resolution. A rigorous geometric calibration of DF system parameters is essential to ensure precise bony rotation and translation measurements. One way to achieve the system calibration is by performing a bundle adjustment with self-calibration. A first-time bundle adjustment-based system calibration was recently achieved. The system calibration through the bundle adjustment has been shown to be robust, precise, and straightforward. Nevertheless, due to the inherent absence of colour/semantic information in DF images, a significant amount of user input is needed to prepare the image observations for the bundle adjustment. This paper introduces a semi-automated methodology to minimise the amount of user input required to process calibration images and henceforth to facilitate the calibration task. The methodology is optimized for processing images acquired over a custom-made calibration frame with radio-opaque spherical targets. Canny edge detection is used to find distinct structural components of the calibration images. Edge-linking is applied to cluster the edge pixels into unique groups. Principal components analysis is utilized to automatically detect the calibration targets from the groups and to filter out possible outliers. Ellipse fitting is utilized to achieve the spatial measurements as well as to perform quality analysis over the detected targets. Single photo resection is used together with a template matching procedure to establish the image-to-object point correspondence and to simplify target identification. The proposed methodology provided 56,254 identified-targets from 411 images that were used to run a second-time bundle adjustment-based DF system calibration. Compared to a previous fully manual procedure, the proposed methodology has significantly reduced the amount of user input needed for processing the calibration images. In addition, the bundle adjustment calibration has reported a 50% improvement in terms of image observation residuals