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Finite Element Modelling of Trabecular Bone Microstructure using Emerging CT Images
Conference proceeding

Finite Element Modelling of Trabecular Bone Microstructure using Emerging CT Images

Indranil Guha, Chamith S Rajapakse, Xiaoliu Zhang, Gregory Chang and Punam Saha
MEDICAL IMAGING 2021: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING, Vol.11600
2021
DOI: 10.1117/12.2580788

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Abstract

Osteoporosis is a common age-related disease associated with increased bone loss causing reduced bone strength and enhanced fracture-risk. Finite element (FE) modelling is used to estimate bone strength from high-resolution three-dimensional (3-D) imaging modalities including micro-CT, MRI, and HR-pQCT. Emerging technologies of multi-row detector CT (MDCT) imaging offer spatial image resolution comparable to human trabecular thickness. However, at the current MDCT resolution regime, FE modelling based on segmented trabecular bone (Tb) microstructure suffers from noise and other imaging artifacts. In this paper, we present a bone mineral density (BMD)-adjusted FE modeling method of Tb microstructure from MDCT imaging without requiring Tb segmentation. The method spatially varies mechanical stiffness based on local ash-density estimated from MDCT-derived calcium hydroxyapatite (CHA) density and, thus, models the hypothesis that stress-flow is primarily absorbed by Tb microstructure as compared to marrow space under mechanical compression. Specifically, an MDCT-based linear FE analysis method was developed using a voxel-mesh and the above model of space-varying stiffness, and the performance of the method was examined. For FE analysis, an axial cylindrical image core of 8mm diameter from 4-6% of distal tibia was extracted after aligning the tibial bone axis with the coordinate z-axis of the image space. Intra-class correlation coefficient (ICC) of 0.98 was observed in a repeat MDCT scan reproducibility experiment using cadaveric distal tibia specimens (n = 10). Also, high linear correlation (r = 0.87) was found between von Mises stress values and MDCT based CHA at individual voxels supporting the central hypothesis of our method.

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