Automatic generation of statistical pose and shape models for articulated joints

Statistical analysis of motion patterns of body joints is potentially useful for detecting and quantifying pathologies. However, building a statistical motion model across different subjects remains a challenging task, especially for a complex joint like the wrist. We present a novel framework for simultaneous registration and segmentation of multiple 3-D (CT or MR) volumes of different subjects at various articulated positions. The framework starts with a pose model generated from 3-D volumes captured at different articulated positions of a single subject (template). This initial pose model is used to register the template volume to image volumes from new subjects. During this process, the Grow-Cut algorithm is used in an iterative refinement of the segmentation of the bone along with the pose parameters. As each new subject is registered and segmented, the pose model is updated, improving the accuracy of successive registrations. We applied the algorithm to CT images of the wrist from 25 subjects, each at five different wrist positions and demonstrated that it performed robustly and accurately. More importantly, the resulting segmentations allowed a statistical pose model of the carpal bones to be generated automatically without interaction. The evaluation results show that our proposed framework achieved accurate registration with an average mean target registration error of mm. The automatic segmentation results also show high consistency with the ground truth obtained semi-automatically. Furthermore, we demonstrated the capability of the resulting statistical pose and shape models by using them to generate a measurement tool for scaphoid-lunate dissociation diagnosis, which achieved 90% sensitivity and specificity

The Effect of Joint Alignment After a Wrist Injury on Joint Mechanics and Osteoarthritis Development

Wrist injuries are common and can lead to the development of post-traumatic osteoarthritis. For example, one major complication after a wrist fracture, is when the fractured bone heals in a mal-aligned position, called malunion. It has been assumed that a malunion after wrist fractures alters joint congruency and mechanics leading to the development of post-traumatic osteoarthritis and poor functional outcomes. It is unclear whether anatomical restoration is a key component for the management of wrist injuries and to limit the progression of post-traumatic osteoarthritis. However, the mechanistic pathways between joint structure (and mal-alignment) and patient outcomes, such as the development of osteoarthritis and joint function, are not clearly understood due to the limitations in current techniques. The present work advances our understanding of the relationship between joint structure (and mal-alignment) and joint contact mechanics using image-based 3D measurement tools. The purpose of the present work was to employ CT imaging and inter-bone distance mapping to determine the 3D implications of a wrist fracture on 3D joint space area (a measure of joint congruency). This image-based tool was then extended to 4DCT (3DCT and time) to examine the dynamic effects of wrist movement on joint contact mechanics, in the presence of a wrist injury. This research is an important step in the quest to determine a causal relationship between joint structure and patient function

Inferring 3D kinematics of carpal bones from single view fluoroscopic sequences

We present a novel framework for inferring 3D carpal bone kinematics and bone shapes from a single view fluoroscopic sequence. A hybrid statistical model representing both the kinematics and shape variation of the carpal bones is built, based on a number of 3D CT data sets obtained from different subjects at different poses. Given a fluoroscopic sequence, the wrist pose, carpal bone kinematics and bone shapes are estimated iteratively by matching the statistical model with the 2D images. A specially designed cost function enables smoothed parameter estimation across frames. We have evaluated the proposed method on both simulated data and real fluoroscopic sequences. It was found that the relative positions between carpal bones can be accurately estimated, which is potentially useful for detection of conditions such as scapholunate dissociation

Reducing risk factors which impact dog welfare through injury in flyball in the UK

To date only two studies have sought to understand the frequency of injury in canine flyball, and no experimental data exists regarding the biomechanical demands placed upon competitors. Uniquely, competitors may use different angulations of flyball box in both training and competition, but no investigation has been conducted as to which may be safer for participants. This thesis therefore aimed to understand current injury risk and frequency in UK flyball and how the kinematics or kinetics of the flyball box turn might influence competitor welfare. We initially conducted two surveys to determine current injury rates and compare data between injured and uninjured flyball participants. Results indicate that faster dogs, those aged over 10 years, and those using a 45° angle of flyball box had the highest risk of injury. Furthermore, we established that injury is associated with the use of support bandaging on the carpus and metatarsus, and dogs are more likely to suffer an injury to the forelimb situated on the inside of a box turn, as well as to the hindlimb on the outside of the box turn. Subsequently, we undertook an investigation into the kinematics of turning in flyball across five different angulations of flyball box, using 2D and 3D motion capture. We determined that although a 45° box angle is more challenging for competitors, there is no evidence to suggest that it carries a greater risk of injury. An additional investigation carried out into the kinetics of the flyball turn also determined that both peak forces and PIP forces were not statistically significant across box angles. However, both our kinematics and kinetics data did confirm that the inner forelimb and outer hindlimb are subjected to patterns of repetitive, asymmetrical loading which would create a significant injury risk, in line with the data collected from our initial surveys. This thesis represents new and significant information regarding our understanding of injury within the sport, and it is hoped this knowledge will be used to enhance competitor welfare and increase competitor safety

Low Back Pain (LBP)

Low back pain (LBP) is a major public health problem, being the most commonly reported musculoskeletal disorder (MSD) and the leading cause of compromised quality of life and work absenteeism. Indeed, LBP is the leading worldwide cause of years lost to disability, and its burden is growing alongside the increasing and aging population. The etiology, pathogenesis, and occupational risk factors of LBP are still not fully understood. It is crucial to give a stronger focus to reducing the consequences of LBP, as well as preventing its onset. Primary prevention at the occupational level remains important for highly exposed groups. Therefore, it is essential to identify which treatment options and workplace-based intervention strategies are effective in increasing participation at work and encouraging early return-to-work to reduce the consequences of LBP. The present Special Issue offers a unique opportunity to update many of the recent advances and perspectives of this health problem. A number of topics will be covered in order to attract high-quality research papers, including the following major areas: prevalence and epidemiological data, etiology, prevention, assessment and treatment approaches, and health promotion strategies for LBP. We have received a wide range of submissions, including research on the physical, psychosocial, environmental, and occupational perspectives, also focused on workplace interventions