Computational and experimental assessment of pelvic stability and optimization of technology to guide reconstruction

点击翻译按钮获取中文摘要

The mechanical stability of the skeleton is critical to allow the transmission of physiologic loads. Damage to musculoskeletal structures can lead to the loss of stability including fracture. This proposal extends the research I have been undertaking on computer modeling of the spine and thin bone structures and extends it to understand damage and stability post fracture, with a specific focus on the pelvis. The human pelvis is a complex structure which includes areas of thin bone, varying material property distributions and multiple articulations. The pelvis transmits the loads of the upper body to the lower extremities and its integrity is essential for locomotion. This research will evaluate stability of the pelvis utilizing image analysis, computational modeling and experimental testing to generate validated models that can represent failure behaviour as damage is initiated in the bone and progresses to fracture. To better understand how features, such as bone density, pelvic shape, fracture location, damage extent, age and sex interact to affect pelvic stability, we will use large datasets and powerful computer vision (machine learning) techniques. Data from intact pelvises (available from open access archives and through medical imaging at Sunnybrook) will be used along with the Marvin Tile Acetabular & Pelvic Fractures Registry at Sunnybrook, which includes detailed data and post fracture imaging from 1695 individuals. Finally, we will extend the breadth of our mechanical research to the design of tools to facilitate stabilization of pelvic fractures. This program will yield a robust and experimentally validated design platform that provides accurate representations of the mechanical behaviour of the pelvis and tools to address specific barriers in reconstruction. Biomechanical analysis, combining computer methods, experimental testing and real-world data, has the potential to greatly advance our understanding of skeletal stability. It provides an exceptional opportunity for HQP to advance their skills, with mentorship from a multidisciplinary team of highly qualified staff (in engineering, physics, computer science, medicine and design). Combining computational mechanical modeling with advances in deep learning and large data sets may allow for improved and novel insights into the mechanical stability of complex bony structures. This work is fundamentally important to the biomechanics community and can ultimately form the basis for a translational pipeline to extend these engineering advances to commercial and clinical application. Key to this work in translating mechanical stability assessments to ultimate guide pelvic reconstruction is a platform that not only acknowledges and addresses differences in injury, but the implications of sex and age, to ensure its relevance for all Canadians.