INVESTIGADORES
CISILINO Adrian Pablo
congresos y reuniones científicas
Título:
ESTIMATION OF TRABECULAR BONE SOLID FRACTION THROUGH ULTRASONIC TRANSMISSION TESTS
Autor/es:
L. AMATO; A. P. CISILINO; G. MESSINEO
Lugar:
Mar del Plata
Reunión:
Congreso; XII Latin-American Congress of Artificial Organs and Biomaterials; 2023
Institución organizadora:
Univ. Mar del Plata, Univ. Rosario, CONICET
Resumen:
Introduction and objective: Estimation of the trabecular bone's solid fraction (BV/TV) is achieved through an inverse problem approach, utilizing ultrasonic wave velocity (SOS) measurements obtained from quantitative ultrasound (QUS) tests. The one-dimensional analytical model developed by Nguyen et al. [1] is employed, establishing correlations between six essential bone properties (porosity, trabecular thickness, tortuosity, permeability, stiffness, and microstructural anisotropy) and SOS measurements. The objective of this research is to streamline the Nguyen et al. model by reducing the number of variables involved, thereby simplifying the inverse analysis.Methodology: An analysis of sensitivity based on variance [2] of SOS predictions was conducted on a dataset of 20 million quasi-random samples generated through quasi-Monte Carlo method with Sobol sequences, aiming to evaluate the influence of input variables in the analytical model. Properties with minimal sensitivity were replaced with constant values, while highly sensitive properties were retained as optimization variables. The precision of the simplified model was evaluated by comparing SOS values obtained from simulated QUS using the SimSonic software.Conclusions: By focusing on the most influential parameters (elastic constants and tortuosity) and neglecting the those with marginal or negligible impact, the model becomes more efficient and easier to work with, without degrading its performance. This streamlined approach not only is a valuable step in optimizing the inverse analysis, making it more practical and reliable for estimating the solid fraction, but also saves time and effort in data collection and analysis of related correlations.