Skip to main content

Advertisement

Log in

Feasibility of Measuring Trabecular Bone Structure of the Proximal Femur Using 64-Slice Multidetector Computed Tomography in a Clinical Setting

  • Published:
Calcified Tissue International Aims and scope Submit manuscript

Abstract

We studied the feasibility of cancellous bone structure assessment of the proximal femur using multidetector computed tomography (MDCT) in an simulated in vivo experimental model. The proximal femur of 15 intact human cadavers was examined using 64-row MDCT using a thin-section protocol with an in-plane spatial resolution of 273 μm. High-resolution peripheral quantitative computed tomography (HR-pQCT) of the isolated specimens with a voxel size of 82 μm served as a standard of reference. Trabecular bone structure and optimized textural parameters were calculated in MDCT images and compared to measures obtained by HR-pQCT. Significant correlations between MDCT- and HR-pQCT-derived values for bone fraction (r = 0.87), trabecular separation (r = 0.66), and number (r = 0.53) were found. Parameters derived from textural analysis performed better in predicting trabecular separation (up to r = 0.86) and number (up to r = 0.83). Trabecular thickness could not be quantified correctly using MDCT, most likely due to its limited resolution. Individual parameters for assessement of trabecular microarchitecture can be measured using MDCT-derived imaging studies and a simulated in vivo setup. Thus, in vivo assessment of bone architecture in addition to BMD may be feasible in clinical practice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Consensus Development Conference (1991) Prophylaxis and treatment of osteoporosis. Am J Med 90:107–110

    Article  Google Scholar 

  2. Cummings SR, Nevitt MC, Browner WS et al (1995) Risk factors for hip fracture in white women. Study of Osteoporotic Fractures Research Group. N Engl J Med 332:767–773

    Article  PubMed  CAS  Google Scholar 

  3. Kanis JA, Borgstrom F, De Laet C et al (2005) Assessment of fracture risk. Osteoporos Int 16:581–589

    Article  PubMed  Google Scholar 

  4. Taylor BC, Schreiner PJ, Stone KL et al (2004) Long-term prediction of incident hip fracture risk in elderly white women: study of osteoporotic fractures. J Am Geriatr Soc 52:1479–1486

    Article  PubMed  Google Scholar 

  5. Mundinger A, Wiesmeier B, Dinkel E, Helwig A, Beck A, Schulte Moenting J (1993) Quantitative image analysis of vertebral body architecture—improved diagnosis in osteoporosis based on high-resolution computed tomography. Br J Radiol 66:209–213

    Article  PubMed  CAS  Google Scholar 

  6. Ammann P, Rizzoli R (2003) Bone strength and its determinants. Osteoporos Int 14(Suppl 3):S13–S18

    PubMed  Google Scholar 

  7. Goldstein SA, Goulet R, McCubbrey D (1993) Measurement and significance of three-dimensional architecture to the mechanical integrity of trabecular bone. Calcif Tissue Int 53(Suppl 1):S127–S132

    Article  PubMed  Google Scholar 

  8. Mosekilde L (1993) Vertebral structure and strength in vivo and in vitro. Calcif Tissue Int 53(Suppl 1):S121–S126

    Article  PubMed  Google Scholar 

  9. Link TM, Majumdar S, Lin JC et al (1998) Assessment of trabecular structure using high resolution CT images and texture analysis. J Comput Assist Tomogr 22:15–24

    Article  PubMed  CAS  Google Scholar 

  10. Link TM, Majumdar S, Lin JC et al (1998) A comparative study of trabecular bone properties in the spine and femur using high resolution MRI and CT. J Bone Miner Res 13:122–132

    Article  PubMed  CAS  Google Scholar 

  11. Tabor Z, Rokita E (2007) Quantifying anisotropy of trabecular bone from gray-level images. Bone 40:966–972

    Article  PubMed  Google Scholar 

  12. Wigderowitz CA, Paterson CR, Dashti H, McGurty D, Rowley DI (2000) Prediction of bone strength from cancellous structure of the distal radius: can we improve on DXA? Osteoporos Int 11:840–846

    Article  PubMed  CAS  Google Scholar 

  13. Gordon CL, Lang TF, Augat P, Genant HK (1998) Image-based assessment of spinal trabecular bone structure from high-resolution CT images. Osteoporos Int 8:317–325

    Article  PubMed  CAS  Google Scholar 

  14. Ito M, Ikeda K, Nishiguchi M et al (2005) Multi-detector row CT imaging of vertebral microstructure for evaluation of fracture risk. J Bone Miner Res 20:1828–1836

    Article  PubMed  Google Scholar 

  15. Ito M, Ohki M, Hayashi K, Yamada M, Uetani M, Nakamura T (1997) Relationship of spinal fracture to bone density, textural, and anthropometric parameters. Calcif Tissue Int 60:240–244

    Article  PubMed  CAS  Google Scholar 

  16. Bauer JS, Issever AS, Fischbeck M et al (2004) Multislice-CT for structure analysis of trabecular bone—a comparison with micro-CT and biomechanical strength [in German]. Rofo 176:709–718

    PubMed  CAS  Google Scholar 

  17. Issever AS, Vieth V, Lotter A et al (2002) Local differences in the trabecular bone structure of the proximal femur depicted with high-spatial-resolution MR imaging and multisection CT. Acad Radiol 9:1395–1406

    Article  PubMed  Google Scholar 

  18. Bauer JS, Kohlmann S, Eckstein F, Mueller D, Lochmuller EM, Link TM (2006) Structural analysis of trabecular bone of the proximal femur using multislice computed tomography: a comparison with dual X-ray absorptiometry for predicting biomechanical strength in vitro. Calcif Tissue Int 78:78–89

    Article  PubMed  CAS  Google Scholar 

  19. Link TM, Vieth V, Langenberg R et al (2003) Structure analysis of high resolution magnetic resonance imaging of the proximal femur: in vitro correlation with biomechanical strength and BMD. Calcif Tissue Int 72:156–165

    Article  PubMed  CAS  Google Scholar 

  20. Bauer JS, Link TM, Burghardt A et al (2007) Analysis of trabecular bone structure with multidetector spiral computed tomography in a simulated soft-tissue environment. Calcif Tissue Int 80:366–373

    Article  PubMed  CAS  Google Scholar 

  21. Boutroy S, Bouxsein ML, Munoz F, Delmas PD (2005) In vivo assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography. J Clin Endocrinol Metab 90:6508–6515

    Article  PubMed  CAS  Google Scholar 

  22. Laib A, Hildebrand T, Hauselmann HJ, Ruegsegger P (1997) Ridge number density: a new parameter for in vivo bone structure analysis. Bone 21:541–546

    Article  PubMed  CAS  Google Scholar 

  23. Muller R, Hildebrand T, Ruegsegger P (1994) Non-invasive bone biopsy: a new method to analyse and display the three-dimensional structure of trabecular bone. Phys Med Biol 39:145–164

    Article  PubMed  CAS  Google Scholar 

  24. Laib A, Ruegsegger P (1999) Calibration of trabecular bone structure measurements of in vivo three-dimensional peripheral quantitative computed tomography with 28-microm-resolution microcomputed tomography. Bone 24:35–39

    Article  PubMed  CAS  Google Scholar 

  25. Link TM, Majumdar S, Augat P et al (1998) In vivo high resolution MRI of the calcaneus: differences in trabecular structure in osteoporosis patients. J Bone Miner Res 13:1175–1182

    Article  PubMed  CAS  Google Scholar 

  26. Haralick RM, Shanmugam K, Dinstein I (1973) Textural features for image classification. EEE Trans Syst Man Cybernet 3:610–621

    Article  Google Scholar 

  27. Anys H, He C (1995) Evaluation of textural and multipolarization radar features for crop classification. IEEE 33:1170–1181

    Google Scholar 

  28. Jiang C, Pitt RE, Bertram JE, Aneshansley DJ (1999) Fractal-based image texture analysis of trabecular bone architecture. Med Biol Eng Comput 37:413–418

    Article  PubMed  CAS  Google Scholar 

  29. Boehm H, Link T, Monetti R (2006) Analysis of the topological properties of the proximal femur on a regional scale: evaluation of multi-detector CT-scans for the assessment of biomechanical strength using local Minkowski functionals in 3D. In: SPIE Medical Imaging. San Diego, pp 6144–6254

  30. Boehm HF, Raeth C, Monetti RA et al (2003) Local 3D scaling properties for the analysis of trabecular bone extracted from high-resolution magnetic resonance imaging of human trabecular bone: comparison with bone mineral density in the prediction of biomechanical strength in vitro. Invest Radiol 38:269–280

    Article  PubMed  CAS  Google Scholar 

  31. Wachter NJ, Augat P, Mentzel M et al (2001) Predictive value of bone mineral density and morphology determined by peripheral quantitative computed tomography for cancellous bone strength of the proximal femur. Bone 28:133–139

    Article  PubMed  CAS  Google Scholar 

  32. Link TM, Vieth V, Stehling C et al (2003) High-resolution MRI vs multislice spiral CT: which technique depicts the trabecular bone structure best? Eur Radiol 13:663–671

    PubMed  Google Scholar 

  33. Cortet B, Chappard D, Boutry N, Dubois P, Cotten A, Marchandise X (2004) Relationship between computed tomographic image analysis and histomorphometry for microarchitectural characterization of human calcaneus. Calcif Tissue Int 75:23–31

    Article  PubMed  CAS  Google Scholar 

  34. Patel PV, Prevrhal S, Bauer JS et al (2005) Trabecular bone structure obtained from multislice spiral computed tomography of the calcaneus predicts osteoporotic vertebral deformities. J Comput Assist Tomogr 29:246–253

    Article  PubMed  Google Scholar 

  35. Graeff C, Timm W, Nickelsen TN et al (2007) Monitoring teriparatide-associated changes in vertebral microstructure by high-resolution CT in vivo: results from the EUROFORS study. J Bone Miner Res 22:1426–1433

    Article  PubMed  CAS  Google Scholar 

  36. Hipp JA, Jansujwicz A, Simmons CA, Snyder BD (1996) Trabecular bone morphology from micro-magnetic resonance imaging. J Bone Miner Res 11:286–297

    Article  PubMed  CAS  Google Scholar 

  37. Vieth V, Link TM, Lotter A et al (2001) Does the trabecular bone structure depicted by high-resolution MRI of the calcaneus reflect the true bone structure? Invest Radiol 36:210–217

    Article  PubMed  CAS  Google Scholar 

  38. Kazakia GJ, Hyun B, Burghardt AJ et al (2008) In vivo determination of bone structure in postmenopausal women: a comparison of HR-pQCT and high-field MR imaging. J Bone Miner Res 23:463–474

    Article  PubMed  Google Scholar 

  39. Krug R, Carballido-Gamio J, Banerjee S, Burghardt AJ, Link TM, Majumdar S (2008) In vivo ultra-high-field magnetic resonance imaging of trabecular bone microarchitecture at 7 T. J Magn Reson Imaging 27:854–859

    Article  PubMed  Google Scholar 

  40. Eckstein F, Lochmuller EM, Lill CA et al (2002) Bone strength at clinically relevant sites displays substantial heterogeneity and is best predicted from site-specific bone densitometry. J Bone Miner Res 17:162–171

    Article  PubMed  Google Scholar 

  41. Muller R, Koller B, Hildebrand T et al (1996) Resolution dependency of microstructural properties of cancellous bone based on three-dimensional mu-tomography. Technol Health Care 4:113–119

    PubMed  CAS  Google Scholar 

  42. MacNeil JA, Boyd SK (2007) Accuracy of high-resolution peripheral quantitative computed tomography for measurement of bone quality. Med Eng Phys 29:1096–1105

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gerd Diederichs.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Diederichs, G., Link, T., Marie, K. et al. Feasibility of Measuring Trabecular Bone Structure of the Proximal Femur Using 64-Slice Multidetector Computed Tomography in a Clinical Setting. Calcif Tissue Int 83, 332–341 (2008). https://doi.org/10.1007/s00223-008-9181-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00223-008-9181-y

Keywords

Navigation