In-vitro study of human proximal femur microstructure: analysis of the relationship between micro-computed tomography data and quantitative ultrasound parameters PROJECT TITLE :In-vitro study of human proximal femur microstructure: analysis of the relationship between micro-computed tomography data and quantitative ultrasound parametersABSTRACT:The aim of this study was to research the relationships between selected quantitative ultrasound (QUS) parameters and human femur microstructure properties, as quantified by micro-computed tomography (micro-CT). The authors employed an innovative custom-designed experimental set-up, which allowed the insonification of each portion of an excised femoral head sample, simultaneously including trabecular region, cortical layer and cartilage in their physiologic morphological configuration. Thirty completely different, uniformly distributed, regions of interest were analysed for the calculation of apparent integrated backscatter (AIB), integrated reflection coefficient (IRC) and many micro-CT parameters. QUS data acquisitions were performed through both single-part ultrasound transducers at two completely different frequencies (a pair of.25 and three.five MHz) and a clinically offered 128-part echographic probe. Obtained results showed that AIB was strongly correlated with trabecular network properties (|r| up to zero.80) and IRC had appreciable linear correlations with cortical bone density (|r| up to zero.fifty seven). The agreement between single-part transducers and echographic probe, combined with the innovative approach of considering the complete femoral head in its physiological shape with all its parts (cartilage, cortical layer, trabecular region), encourages the clinical translation of the proposed approach as a potential new method for early osteoporosis diagnosis. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Steering of Multisegment Continuum Manipulators Using Rigid-Link Modeling and FBG-Based Shape Sensing Joint Optimal Design and Operation of Hybrid Energy Storage Systems