Author : Bino Abel Varghese
Publisher :
ISBN 13 :
Total Pages : 85 pages
Book Rating : 4.:/5 (11 download)
Book Synopsis Quantitative Computed-tomography Based Bone-strength Indicators for the Identification of Low Bone-strength Individuals in a Clinical Environment by : Bino Abel Varghese
Download or read book Quantitative Computed-tomography Based Bone-strength Indicators for the Identification of Low Bone-strength Individuals in a Clinical Environment written by Bino Abel Varghese and published by . This book was released on 2011 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of the current study was to develop quantitative computed-tomography (QCT)-based bone-strength indicators that highly correlate with finite-element (FE)-based strength. We perform a combined numerical-experimental study, comparing FE-predicted surface strains with strain gauge measurements, to validate the FE models of 36 long bones (humerus, radius, femur and tibia) under three-point bending and torsion. The FE models were constructed from trans-axial volumetric CT scans, and the segmented bone images were corrected for partial-volume effects. The material properties (Young's modulus for cortex, density-modulus relationship for trabecular bone and Poisson's ratio) were calibrated by minimizing the error between experiments and simulations among all bones. The resultant R2 values of the measured strains versus load under three-point bending and torsion were 0.96-0.99 and 0.61-0.99, respectively, for all bones in our data set. The errors of the calculated FE strains in comparison to those measured using strain gauges in the mechanical tests ranged from -6% to 7% under bending and from -37% to 19% under torsion. The observation of comparatively low errors and high correlations between the FE-predicted strains and the experimental strains, across the various types of bones and loading conditions (bending and torsion), validates our approach to bone segmentation and our choice of material properties. Based on the analysis of the various FE models of the long bones, the location of the CT slice on the bone that showed the highest propensity to fracture was identified for four loading conditions (compression, three-point bending, cantilever bending and torsion). The identified CT slice was then used to derive novel and improved bone-strength indicators. We evaluated the performance of area-weighted (AW), density-weighted (DW) and modulus-weighted (MW) rigidity measures as well as popular strength indicators like section modulus and stress-strain index. We have also developed a novel strength metric, the centroid deviation, which takes into consideration the spatial distribution of the centroids. Here, we observed that the MW polar moment of inertia and the MW moment of inertia were the two top-performers (average r