In this work, we propose a new quantitative way of evaluating acute compartment syndrome (ACS) by dynamic mechanical assessment of soft tissue changes. First, we have developed an animal model of ACS to replicate the physiological changes during the condition. Secondly, we have developed a mechanical assessment tool for quantitative pre-clinical assessment of ACS. Our hand-held indentation device provides an accurate method for investigations into the local dynamic mechanical properties of soft tissue and for in-situ non-invasive assessment and monitoring of ACS. Our compartment syndrome model was developed on the cranial tibial and the peroneus tertius muscles of a pig's leg (postmortem). The compartment syndrome pressure values were obtained by injecting blood from the bone through the muscle. To enable ACS assessment by a hand-held indentation device we combined three main components: a load cell, a linear actuator and a 3-axis accelerometer. Dynamic tests were performed at a frequency of 0.5 Hz and by applying an amplitude of 0.5 mm. Another method used to observe the differences in the mechanical properties inside the leg was a 3D Digital Image Correlation (3D-DIC). Videos were taken from two different positions of the pig's leg at different pressure values: 0 mmHg, 15 mmHg and 40 mmHg. Two strains along the x axis (Exx) and y axis (Eyy) were measured. Between the two pressure cases (15 mmHg and 40 mmHg) a clear deformation of the model is visible. In fact, the bigger the pressure, the more visible the increase in strain is. In our animal model, local muscle pressures reached values higher than 40 mmHg, which correlate with observed human physiology in ACS. In our presentation we will share our dynamic indentation results on this model to demonstrate the sensitivity of our measurement techniques. Compartment syndrome is recognised as needing improved clinical management tools. Our approach provides both a model that reflects physiological behaviour of ACS, and a method for in-situ non-invasive assessment and monitoring.
