1. Ellen Vanderburgh HSS 409 4/21/10

2. Stress Fractures: What are They?  Over-use injury  Cumulative mechanical trauma to bone or muscle  Muscle strain causes bone damage  Small crack within bone  Starts as microcrack and becomes macrocrack  “crack driving force” is greater than crack resistance  Cannot repair damage  In lower extremities- occur in load bearing bones  Metatarslas, femur, fibula and tibia  15-20% overuse injuries tibial

3. Who is at Risk?  Athletes involved in repetitive, weight bearing, lower body activity  Ex: Runners  Low bone density  Bone cannot repair  Common in women  Female triad: abnormal eating, excessive exercising, amenorrhea  Poor footwear  Abrupt training increase

4. Predicting Tibial Stress Fracture Probability with Biomechanics  Crack driving force increases with loading magnitude (intensity) and crack length  Increases in speed  Increases in running cycles (aka strides)  High magnitude loading increases rate of microcracks- bone repair process cannot “catch up”  Crack resistance is less than crack driving force  Must identify loading patterns that cause bone strain  Loading magnitude, loading cycles, bone repair process, ground reaction forces, adaptation to activity

5. Purpose and Hypothesis of Study  Determine influence of running speed on the probability of tibial stress fracture during a new running regimen  Approximately 100 days  “Reducing running speed would decrease tibial strain enough to negate detrimental increased number of loading cycles associated with the reduction”  Prediction model!!  Use tibial strain measurement to predict relative risk for tibial fracture  Strain = Fracture risk

6. Subjects  10 males  Mean age=24.9  Mean mass=70.1  All participated in running or athletic activity on weekly basis  Injury free  Prior to study, no physical activity for 3 months

7. Methods  Established joint center locations  Anthropometric measurements and retroreflective markers on anatomical landmarks  Static motion capture trial, while standing in anatomical position  For each joint, x axis was anterior to posterior, y axis in axial direction, z axis was medial to lateral

8. Methods  Subjects ran over-ground at 2.5, 3.5 and 4.5 m/s (5.6, 7.8 and 10.1 mph)  Speed measured using motion capture of the horizontal component of L5S1 anatomical marker  10 trials performed for each speed  Researcher measured time for 3 strides  Used to find subjects average stride frequency and stride length for each speed

9. Data Processing  Measured and averaged stride frequency for each speed  2.5=20.3 Hz, 3.5=26.6 Hz, 4.5=32.8 Hz  Took three dimensional joint and segment angles  Used flexion/extension, abduction/adduction, internal/external rotation sequence  Joint reaction forces and net internal joint moments were determined using inverse dynamics  Body segment masses, moments of inertia and center of gravity locations were also calculated

10. Data Processing: Musculoskeletal Modeling  Joint angles were interpolated to 101 points into a musculo skeletal model (SIMM model) and scaled to each subjects segment lengths http://www.musculographics.com/products/si mm.html

11. Developing the Probalistic Model for Tibial Stress Fracture  Probability for Fracture=  Contact force – Reaction force  Contact force:  Ground reaction force due to loading intensity, speed and body weight  Reaction force:  Tibial strain damage, bone repair and bone adaptation

12. Probalistic Model for Stress Fracture: Tibial Contact Force  Used musculoskeletal data to determine contact force acting on tibia-cannot be directly calculated  Ankle joint contact force calculated as vector sum of reaction force and muscle forces crossing talocrural joint  Fibula absorbs 10% of ankle joint contact force  Therefore, contact force for tibia:

13. Probalistic Model of Stress Fracture: Bone Damage, Fatigue Life and Adaptation  Used probalistic model of bone damage, repair and adaptation  Due to scatter in the fatigue life of bone, probability of failure when there is scatter was calculated using  The cumulative probability for bone repair, taking into account for failure, repair and adaptation with respect to time was determined as

14. Results  Joint contact force acting on distal tibia increased with running speed  Axial component across longitudinal axis of tibia was the dominant force  Mean peak instantaneous tibial contact forces were used to determine the instant of peak resultant force Tibial Contact Force (BW) Speed (m/s)Anterior- Posterior AxialMedial-Lateral 2.5-.5310.73.51 3.5-.6212.63.61 4.5-.6613.80.68

15. Results  The number of loading exposures decreased with a decrease in running speed due to positive relationship between speed and stride length  For 4.8 km/day, loading exposure (strides)for each speed:  2.5 m/s=2435  3.5 m/s=1829  4.5 m/s=1549

16. Results  Probability of failure peaked and leveled off after 40 days of training (within the 100 day new training regimen)  Decrease in speed resulted in a decrease in probability for fracture  From 4.5-3.5 m/s=7% decrease  From 3.5-2.5 m/s=10% decrease Speed (m/s) 2.53.54.5 Probability for Failure.09.19.26

17. Discussion  Hypothesis of article was supported in that the probability for tibial stress fracture was decreased with a decrease in speed  This also supports the idea that a decrease in speed will negate the damage done by the increase in loading cycles with the decrease in speed  A decrease in run speed may reduce risk for tibial stress fracturing  Risk for fracturing plateaus after 40 days of new regimen  **Note: Does not consider biomechanical misalignments or abnormalities

18. Significance to HSS 409  Complexity of dynamic muscle equations and forces  Dealt only with single joints in static, non-weight bearing positions  Need to incorporate numerous angles, centers of gravity, limb lengths to characterize dynamic movements  Also not just x and y, but also z (3D)

19. Significance to HSS 409  BIO+MECHANICS  Physiological component + engineering component  Prediction modeling  In class- military scaling, back-pack equation  Development of derived constants  Based on anthropometric analysis, but needs to actually be tested

20. Practical Implications  Speed is big factor in recovery and bone adaption  Important to consider gradual period during beginning of training  First time race: marathon, etc.  Recovering from injury: basically starting over  Injury potential= very fine line  Military  Extremely intense training  High risk and incidence of stress fracture