Lowering Bone Stress Injury Risk by Understanding Loading Angle, Bone Strength, and Training Load
Bryhannah Young, Masters Thesis Defense
Bone stress injuries (BSI) lead to structural fatigue, localized bone pain, and in severe cases loss of bone function. Currently there is minimal research in understanding how foot loading and biomechanics contribute to high metatarsal strain and damage accumulation within the metatarsals of runners. Utilizing computed tomographic images of the feet of 28 long distance runners (7 injured and 21 healthy) three-dimensional orthotropic models of the metatarsals were fabricated to simulate different loading conditions in the second, third, and fourth metatarsals from each foot. We compared the effect of loading angle and injury status, and a bone cumulative loading ratio (BCLR) from this analysis to understand how different associated risk factors affect the mechanical behavior of the metatarsals.
Our evaluation of the effect of metatarsal loading angle concluded that by modifying our running biomechanics from a bending to a more axial loading angle, there would be a 70% reduction in strain in metatarsals (p<0.001). There is an excess amount of strained volume within the healthy feet of the injured runners (>17%) which, translates to a large amount of damage accumulation within the metatarsal. Injured runners surpassed the theoretical loading capacities of their bone by running more than 30 miles a week, and we found that biomechanical and demographic data are important factors used when understanding the risk factors associated with BSI. This study uses an integrated approach in understanding BSI by understanding biomechanics of metatarsal loading through changes in loading angle, the structural mechanics of bone in injured and healthy runners and created bone cumulative loading ratio to understand the possible modifications plausible in lower the risk of BSI. The BCLR represents a promising concept to assess BSI risk, relative to the training load and individual bone structure. In the future, predictive models such as the ones developed here could help reduce the risk of BSI through managing biomechanics, training load, and personal risk factors.
For a zoom link, please contact Kate Harrison (kharrison@wpi.edu) or June Norton (jnorton@wpi.edu).