Research Papers

Effect of Intraspecimen Spatial Variation in Tissue Mineral Density on the Apparent Stiffness of Trabecular Bone

[+] Author and Article Information
Narges Kaynia

Department of Mechanical Engineering,
Massachusetts Institute of Technology,
Cambridge, MA 02139
e-mail: nkaynia@mit.edu

Elaine Soohoo

Departments of Mechanical
Engineering and Bioengineering,
University of California,
Berkeley, CA 94720
e-mail: soohoo.elaine@gmail.com

Tony M. Keaveny

Departments of Mechanical
Engineering and Bioengineering,
University of California,
Berkeley, CA 94720
e-mail: tmk@me.berkeley.edu

Galateia J. Kazakia

Department of Radiology and
Biomedical Imaging,
University of California San Francisco,
185 Berry Street, Suite 350,
San Francisco, CA 94107
e-mail: galateia.kazakia@ucsf.edu

1Corresponding author.

Manuscript received August 5, 2014; final manuscript received November 17, 2014; accepted manuscript posted December 10, 2014; published online December 10, 2014. Assoc. Editor: Blaine A. Christiansen.

J Biomech Eng 137(1), 011010 (Jan 01, 2015) (6 pages) Paper No: BIO-14-1366; doi: 10.1115/1.4029178 History: Received August 05, 2014; Revised November 17, 2014; Accepted December 10, 2014; Online December 10, 2014

This study investigated the effects of intraspecimen variations in tissue mineral density (TMD) on the apparent-level stiffness of human trabecular bone. High-resolution finite element (FE) models were created for each of 12 human trabecular bone specimens, using both microcomputed tomography (μCT) and “gold-standard” synchrotron radiation μCT (SRμCT) data. Our results confirm that incorporating TMD spatial variation reduces the calculated apparent stiffness compared to homogeneous TMD models. This effect exists for both μCT- and SRμCT-based FE models, but is exaggerated in μCT-based models. This study provides a direct comparison of μCT to SRμCT data and is thereby able to conclude that the influence of including TMD heterogeneity is overestimated in μCT-based models.

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Grahic Jump Location
Fig. 1

Schematic representation of the three material models evaluated for each specimen

Grahic Jump Location
Fig. 2

Mean Etissue plotted against mean TMD for each specimen as calculated from μCT and SRμCT images (n = 12)

Grahic Jump Location
Fig. 6

Bland-Altman plot comparing μCT to SRμCT results for the normalized apparent modulus EHET/EHOM. Dark dashed line is the mean, light dashed lines are the 95% CI. Empty and filled markers represent low and high BV/TV samples, respectively.

Grahic Jump Location
Fig. 5

Normalized apparent modulus of the μCT and SRμCT images. *p = 0.0005

Grahic Jump Location
Fig. 4

Apparent modulus for the μCT and SRμCT images, stratified by low (n = 8) versus high (n = 4) BV/TV. *p = 0.008, + p = 0.125. Combined analysis (low and high BV/TV groups together) results in p = 0.0005.

Grahic Jump Location
Fig. 3

Regressions and Bland–Altman analyses of EHET, EHOM, and EREF demonstrate that the μCT-based FE analysis underestimates apparent modulus when models are specimen-specific. Regression results follow: EHETy = 1.42 x − 32 R2= 0.99; EHOMy = 1.34 x − 27 R2= 0.99; EREFy = 0.90 x + 28 R2= 0.99. In the Bland–Altman plots, empty and filled markers represent low and high BV/TV samples, respectively.



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