Numerical analysis of uncertainties in dual frequency bone ultrasound technique.

Quantitative ultrasound (QUS) measurements are used in the diagnostics of osteoporosis. However, the variation in the thickness and composition of the overlying soft tissue causes significant errors to the bone QUS parameters and diminishes the reliability of the technique in vivo. Recently, the dual frequency ultrasound (DFUS) technique was introduced to minimize the errors related to soft tissue effects. In this study, the significance of soft tissue induced errors and their elimination with the DFUS technique were simulated using the finite difference time domain technique. Furthermore, we investigated the potential of the DFUS corrected integrated reflection coefficient (IRC) of bone to detect changes in the cortical bone density. The effects of alterations in the thickness of fat and lean tissue layers and the inclination between the soft-tissues and between the soft tissue-bone layers were simulated. When the angle of the soft tissue interface was zero, i.e., perpendicular to the incident ultrasound beam, the DFUS-calculated soft tissue composition correlated highly linearly with the true soft tissue composition. The inclination between the soft tissue-bone layers was found to be critical. Even a 2-degree inclination between the soft tissue and the bone surface induced an almost 18% relative error in the corrected IRC. Increasing the inclination between the soft tissue layers increased the error in the DFUS-calculated lean and fat tissue thickness. This error was especially significant at inclination angles greater than 20 degrees. The significant soft tissue induced errors in IRC values (>300 %) could be effectively minimized (<10%) by means of the DFUS correction. Importantly, after the DFUS correction, physiologically relevant variation in the cortical bone density could be detected (p<0.05).