Development of a FPGA-based quantitative ultrasound system for assessing stress-strain properties of Achilles tendon

Achilles tendon (AT) is the most fragile and vulnerable part in human body. Stress-strain properties and shape changing such as cross-sectional area variations of this tendon are important biomechanical properties used clinically for assessing and monitoring surgical repair or postoperative healing progress. However, so far, there are few methods for non-invasively, precisely and quantitatively assessing in vivo AT mechanism. In this study, we develop a quantitative ultrasound system (QUS) based on FPGA aiming at estimating stress-strain properties of AT via evaluating the broadband ultrasound attenuation (BUA) parameter upon different levels of applied stress on the AT. Twenty fresh ATs of hind porcine trotters were procured from a local abattoir, and were preloaded for 30 cycles with a cyclic loading ranging from 0 to 300 N. The loading force pulled along the tendon fibers, and the changes of AT cross-sectional area were acquired by ultrasound transducer implemented in the palmardorsal direction which was perpendicular to the tendon fibers. BUA has been widely used to estimate the broadband ultrasonic attenuation (dB MHz-1) by calculating the slope of a linear regression fit to the attenuation against frequency plot within a frequency range. The tendons were then strained from 1 to 400 N with single steps of 50 N, and the measurements were repeated for ten times following calculating the average slope of BUA to reduce the interference of noise. Results showed that as the tendon tissue was stretched orthogonally to the beam axis, BUA coefficient decreased linearly with increasing stress (R-square =0.89). This indicated that the BUA coefficient is a potentially useful parameter for quantitative characterization of ATs. The FPGA system proposed for measuring tendon thickness using QUS technique is an easy and objective method to precisely evaluate the tissue thickness, providing a new way for AT to implement high-speed online diagnosis.