Voxel size dependency, reproducibility and sensitivity of an in vivo bone loading estimation algorithm

Patrik Christen, Friederike A. Schulte, Alexander Zwahlen, Bert Van Rietbergen, Stephanie Boutroy, L. Joseph Melton, Shreyasee Amin, Sundeep Khosla, Jörg Goldhahn, Ralph Müller

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

A bone loading estimation algorithm was previously developed that provides in vivo loading conditions required for in vivo bone remodelling simulations. The algorithm derives a bone's loading history from its microstructure as assessed by high-resolution (HR) computed tomography (CT). This reverse engineering approach showed accurate and realistic results based on micro-CT and HR-peripheral quantitative CT images. However, its voxel size dependency, reproducibility and sensitivity still need to be investigated, which is the purpose of this study. Voxel size dependency was tested on cadaveric distal radii with micro-CT images scanned at 25 mm and downscaled to 50, 61, 75, 82, 100, 125 and 150 mm. Reproducibility was calculated with repeated in vitro as well as in vivo HR-pQCT measurements at 82 mm. Sensitivity was defined using HR-pQCT images from women with fracture versus non-fracture, and low versus high bone volume fraction, expecting similar and different loading histories, respectively. Our results indicate that the algorithm is voxel size independent within an average (maximum) error of 8.2% (32.9%) at 61 mm, but that the dependency increases considerably at voxel sizes bigger than 82 mm. In vitro and in vivo reproducibility are up to 4.5% and 10.2%, respectively, which is comparable to other in vitro studies and slightly higher than in other in vivo studies. Subjects with different bone volume fraction were clearly distinguished but not subjects with and without fracture. This is in agreement with bone adapting to customary loading but not to fall loads. We conclude that the in vivo bone loading estimation algorithm provides reproducible, sensitive and fairly voxel size independent results at up to 82 mm, but that smaller voxel sizes would be advantageous.

Original languageEnglish (US)
Article number20150991
JournalJournal of the Royal Society Interface
Volume13
Issue number114
DOIs
StatePublished - Jan 1 2016

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Bone
Bone and Bones
Tomography
Volume fraction
Bone Remodeling
Reverse engineering
Image resolution
History
Microstructure
In Vitro Techniques

Keywords

  • Bone loading estimation
  • HR-pQCT
  • Human distal radius
  • Reproducibility
  • Sensitivity
  • Voxel size dependency

ASJC Scopus subject areas

  • Biophysics
  • Biotechnology
  • Bioengineering
  • Biomedical Engineering
  • Biomaterials
  • Biochemistry

Cite this

Christen, P., Schulte, F. A., Zwahlen, A., Van Rietbergen, B., Boutroy, S., Melton, L. J., ... Müller, R. (2016). Voxel size dependency, reproducibility and sensitivity of an in vivo bone loading estimation algorithm. Journal of the Royal Society Interface, 13(114), [20150991]. https://doi.org/10.1098/rsif.2015.0991

Voxel size dependency, reproducibility and sensitivity of an in vivo bone loading estimation algorithm. / Christen, Patrik; Schulte, Friederike A.; Zwahlen, Alexander; Van Rietbergen, Bert; Boutroy, Stephanie; Melton, L. Joseph; Amin, Shreyasee; Khosla, Sundeep; Goldhahn, Jörg; Müller, Ralph.

In: Journal of the Royal Society Interface, Vol. 13, No. 114, 20150991, 01.01.2016.

Research output: Contribution to journalArticle

Christen, P, Schulte, FA, Zwahlen, A, Van Rietbergen, B, Boutroy, S, Melton, LJ, Amin, S, Khosla, S, Goldhahn, J & Müller, R 2016, 'Voxel size dependency, reproducibility and sensitivity of an in vivo bone loading estimation algorithm', Journal of the Royal Society Interface, vol. 13, no. 114, 20150991. https://doi.org/10.1098/rsif.2015.0991
Christen, Patrik ; Schulte, Friederike A. ; Zwahlen, Alexander ; Van Rietbergen, Bert ; Boutroy, Stephanie ; Melton, L. Joseph ; Amin, Shreyasee ; Khosla, Sundeep ; Goldhahn, Jörg ; Müller, Ralph. / Voxel size dependency, reproducibility and sensitivity of an in vivo bone loading estimation algorithm. In: Journal of the Royal Society Interface. 2016 ; Vol. 13, No. 114.
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