Table of Contents
Journal of Medical Engineering
Volume 2014, Article ID 946574, 13 pages
http://dx.doi.org/10.1155/2014/946574
Research Article

A Digital Model to Simulate Effects of Bone Architecture Variations on Texture at Spatial Resolutions of CT, HR-pQCT, and μCT Scanners

1Institute of Medical Physics, University of Erlangen-Nürnberg, Henkestraße 91, 91052 Erlangen, Germany
2Service de Radiologie Ostéo-Articulaire, Hôpital Lariboisière, Assistance Publique-Hôpitaux de Paris, 2 rue Ambroise Paré, 75010 Paris, France
3Université Paris VII-Denis Diderot, 5 rue Thomas Mann, 75205 Paris, France

Received 25 October 2013; Accepted 30 January 2014; Published 18 May 2014

Academic Editor: Sarah Cartmell

Copyright © 2014 T. Lowitz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. K. Engelke, C. Libanati, T. Fuerst, P. Zysset, and H. K. Genant, “Advanced CT based in vivo methods for the assessment of bone density, structure, and strength,” Current Osteoporosis Reports, vol. 11, no. 3, pp. 246–255, 2013. View at Publisher · View at Google Scholar
  2. A. J. Burghardt, T. M. Link, and S. Majumdar, “High-resolution computed tomography for clinical imaging of bone microarchitecture,” Clinical Orthopaedics and Related Research, vol. 469, no. 8, pp. 2179–2193, 2011. View at Publisher · View at Google Scholar · View at Scopus
  3. J. Pialat, A. J. Burghardt, M. Sode, T. M. Link, and S. Majumdar, “Visual grading of motion induced image degradation in high resolution peripheral computed tomography: impact of image quality on measures of bone density and micro-architecture,” Bone, vol. 50, no. 1, pp. 111–118, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Sode, A. J. Burghardt, J.-B. Pialat, T. M. Link, and S. Majumdar, “Quantitative characterization of subject motion in HR-pQCT images of the distal radius and tibia,” Bone, vol. 48, no. 6, pp. 1291–1297, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. C. Showalter, B. D. Clymer, B. Richmond, and K. Powell, “Three-dimensional texture analysis of cancellous bone cores evaluated at clinical CT resolutions,” Osteoporosis International, vol. 17, no. 2, pp. 259–266, 2006. View at Publisher · View at Google Scholar · View at Scopus
  6. C. M. Phan, E. A. MacKlin, M. A. Bredella et al., “Trabecular structure analysis using C-arm CT: comparison with MDCT and flat-panel volume CT,” Skeletal Radiology, vol. 40, no. 8, pp. 1065–1072, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. S. Hansen, J.-E. B. Jensen, L. Rasmussen, E. M. Hauge, and K. Brixen, “Effects on bone geometry, density, and microarchitecture in the distal radius but not the tibia in women with primary hyperparathyroidism: a case-control study using HR-pQCT,” Journal of Bone and Mineral Research, vol. 25, no. 9, pp. 1941–1947, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. R. B. Martin, D. B. Burr, and N. A. Sharkey, Skeletal Tissue Mechanics, Springer, New York, NY, USA, 1998.
  9. M. J. Turunen, V. Prantner, J. S. Jurvelin, H. Kroger, and H. Isaksson, “Composition and microarchitecture of human trabecular bone changes with age and differs between anatomical locations,” Bone, vol. 54, no. 1, pp. 118–125, 2013. View at Publisher · View at Google Scholar
  10. T. Hildebrand, A. Laib, R. Müller, J. Dequeker, and P. Rüegsegger, “Direct three-dimensional morphometric analysis of human cancellous bone: microstructural data from spine, femur, iliac crest, and calcaneus,” Journal of Bone and Mineral Research, vol. 14, no. 7, pp. 1167–1174, 1999. View at Publisher · View at Google Scholar · View at Scopus
  11. T. Woloszynski, P. Podsiadlo, G. W. Stachowiak, M. Kurzynski, L. S. Lohmander, and M. Englund, “Prediction of progression of radiographic knee osteoarthritis using tibial trabecular bone texture,” Arthritis and Rheumatism, vol. 64, no. 3, pp. 688–695, 2012. View at Publisher · View at Google Scholar · View at Scopus
  12. T. Baum, J. Carballido-Gamio, M. B. Huber et al., “Automated 3D trabecular bone structure analysis of the proximal femur-prediction of biomechanical strength by CT and DXA,” Osteoporosis International, vol. 21, no. 9, pp. 1553–1564, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. E. A. Messent, J. C. Buckland-Wright, and G. M. Blake, “Fractal analysis of trabecular bone in knee osteoarthritis (OA) is a more sensitive marker of disease status than bone mineral density (BMD),” Calcified Tissue International, vol. 76, no. 6, pp. 419–425, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. W. Tjong, G. J. Kazakia, A. J. Burghardt, and S. Majumdar, “The effect of voxel size on high-resolution peripheral computed tomography measurements of trabecular and cortical bone microstructure,” Medical Physics, vol. 39, no. 4, pp. 1893–1903.
  15. N. Kim, J.-G. Lee, Y. Song, H. J. Kim, J. S. Yeom, and G. Cho, “Evaluation of MRI resolution affecting trabecular bone parameters: determination of acceptable resolution,” Magnetic Resonance in Medicine, vol. 67, no. 1, pp. 218–225, 2012. View at Publisher · View at Google Scholar · View at Scopus
  16. M. Sode, A. J. Burghardt, R. A. Nissenson, and S. Majumdar, “Resolution dependence of the non-metric trabecular structure indices,” Bone, vol. 42, no. 4, pp. 728–736, 2008. View at Publisher · View at Google Scholar · View at Scopus
  17. J. B. Pialat, N. Vilayphiou, S. Boutroy et al., “Local topological analysis at the distal radius by HR-pQCT: application to in vivo bone microarchitecture and fracture assessment in the OFELY study,” Bone, vol. 51, no. 3, pp. 362–368, 2012. View at Publisher · View at Google Scholar
  18. R. Rajamanohara, J. Robinson, J. Rymer, R. Patel, I. Fogelman, and G. M. Blake, “The effect of weight and weight change on the long-term precision of spine and hip DXA measurements,” Osteoporosis International, vol. 22, no. 5, pp. 1503–1512, 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. L. Forsén, G. K. R. Berntsen, H. E. Meyer, G. S. Tell, and V. Fønnebø, “Differences in precision in bone mineral density measured by SXA and DXA: the NOREPOS study,” European Journal of Epidemiology, vol. 23, no. 9, pp. 615–624, 2008. View at Publisher · View at Google Scholar · View at Scopus
  20. P. K. Commean, J. A. Kennedy, K. A. Bahow et al., “Volumetric quantitative computed tomography measurement precision for volumes and densities of tarsal and metatarsal bones,” Journal of Clinical Densitometry, vol. 14, no. 3, pp. 313–320, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. P. Zerfass, T. Lowitz, O. Museyko et al., “An integrated segmentation and analysis approach for QCT of the knee to determine subchondral bone mineral density and texture,” IEEE Transactions on Biomedical Engineering, vol. 59, no. 9, pp. 2449–2458, 2012. View at Publisher · View at Google Scholar
  22. K. Engelke, C. Libanati, Y. Liu et al., “Quantitative computed tomography (QCT) of the forearm using general purpose spiral whole-body CT scanners: accuracy, precision and comparison with dual-energy X-ray absorptiometry (DXA),” Bone, vol. 45, no. 1, pp. 110–118, 2009. View at Publisher · View at Google Scholar · View at Scopus
  23. W. A. Kalender, Computed Tomography, Fundamentals, System Technology, Image Quality, Applications, Publicis, Erlangen, Germany, 3rd edition, 2011.
  24. I. Singh, “The architecture of cancellous bone,” Journal of Anatomy, vol. 127, part 2, pp. 305–310, 1978. View at Google Scholar · View at Scopus
  25. V. Patel, A. S. Issever, A. Burghardt, A. Laib, M. Ries, and S. Majumdar, “MicroCT evaluation of normal and osteoarthritic bone structure in human knee specimens,” Journal of Orthopaedic Research, vol. 21, no. 1, pp. 6–13, 2003. View at Publisher · View at Google Scholar · View at Scopus
  26. M. Ding, A. Odgaard, F. Linde, and I. Hvid, “Age-related variations in the microstructure of human tibial cancellous bone,” Journal of Orthopaedic Research, vol. 20, no. 3, pp. 615–621, 2002. View at Publisher · View at Google Scholar · View at Scopus
  27. W. S. Rasband, “ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA,” 1997–2012, http://imagej.nih.gov/ij/.
  28. P. McDonnell, P. E. McHugh, and D. O'Mahoney, “Vertebral osteoporosis and trabecular bone quality,” Annals of Biomedical Engineering, vol. 35, no. 2, pp. 170–189, 2007. View at Publisher · View at Google Scholar · View at Scopus
  29. C. Chappard, F. Peyrin, A. Bonnassie et al., “Subchondral bone micro-architectural alterations in osteoarthritis: a synchrotron micro-computed tomography study,” Osteoarthritis and Cartilage, vol. 14, no. 3, pp. 215–223, 2006. View at Publisher · View at Google Scholar · View at Scopus
  30. J. Wolff, The Law of Bone Remodeling, Springer, Berlin, Germany, 1986.
  31. S. Ihara, Information Theory for Continuous Systems, World Scientific, 1993.
  32. J. J. Gough, J. T. Kent, P. O'Higgins, and L. T. Ellison, “Variogram methods for the analysis of bony trabecular shadows in plain radiographs,” International Journal of Bio-Medical Computing, vol. 35, no. 2, pp. 141–153, 1994. View at Google Scholar · View at Scopus
  33. L. G. E. Cox, B. Van Rietbergen, C. C. van Donkelaar, and K. Ito, “Bone structural changes in osteoarthritis as a result of mechanoregulated bone adaptation: a modeling approach,” Osteoarthritis and Cartilage, vol. 19, no. 6, pp. 676–682, 2011. View at Publisher · View at Google Scholar · View at Scopus
  34. K. Kuroki, C. R. Cook, and J. L. Cook, “Subchondral bone changes in three different canine models of osteoarthritis,” Osteoarthritis and Cartilage, vol. 19, no. 9, pp. 1142–1149, 2011. View at Publisher · View at Google Scholar · View at Scopus
  35. Z.-M. Zhang, Z.-C. Li, L.-S. Jiang, S.-D. Jiang, and L.-Y. Dai, “Micro-CT and mechanical evaluation of subchondral trabecular bone structure between postmenopausal women with osteoarthritis and osteoporosis,” Osteoporosis International, vol. 21, no. 8, pp. 1383–1390, 2010. View at Publisher · View at Google Scholar · View at Scopus
  36. T. Y. Zhu, J. F. Griffith, L. Qin et al., “Structure and strength of the distal radius in female patients with rheumatoid arthritis: a case-control study,” Journal of Bone and Mineral Research, vol. 28, no. 4, pp. 794–806, 2012. View at Publisher · View at Google Scholar
  37. P. Roschger, E. P. Paschalis, P. Fratzl, and K. Klaushofer, “Bone mineralization density distribution in health and disease,” Bone, vol. 42, no. 3, pp. 456–466, 2008. View at Publisher · View at Google Scholar · View at Scopus
  38. K. Nawrot-Wawrzyniak, F. Varga, A. Nader et al., “Effects of tumor-induced osteomalacia on the bone mineralization process,” Calcified Tissue International, vol. 84, no. 4, pp. 313–323, 2009. View at Publisher · View at Google Scholar · View at Scopus