Osteoporosis International

, Volume 24, Issue 4, pp 1379–1388 | Cite as

A comparison of DXA and CT based methods for estimating the strength of the femoral neck in post-menopausal women

  • M. E. Danielson
  • T. J. Beck
  • A. S. Karlamangla
  • G. A. Greendale
  • E. J. Atkinson
  • Y. Lian
  • A. S. Khaled
  • T. M. Keaveny
  • D. Kopperdahl
  • K. Ruppert
  • S. Greenspan
  • M. Vuga
  • J. A. Cauley
Original Article



The study goal was to compare simple two-dimensional (2D) analyses of bone strength using dual energy x-ray absorptiometry (DXA) data to more sophisticated three-dimensional (3D) finite element analyses using quantitative computed tomography (QCT) data. DXA- and QCT-derived femoral neck geometry, simple strength indices, and strength estimates were well correlated.


Simple 2D analyses of bone strength can be done with DXA data and applied to large data sets. We compared 2D analyses to 3D finite element analyses (FEA) based on QCT data.


Two hundred thirteen women participating in the Study of Women's Health Across the Nation (SWAN) received hip DXA and QCT scans. DXA BMD and femoral neck diameter and axis length were used to estimate geometry for composite bending (BSI) and compressive strength (CSI) indices. These and comparable indices computed by Hip Structure Analysis (HSA) on the same DXA data were compared to indices using QCT geometry. Simple 2D engineering simulations of a fall impacting on the greater trochanter were generated using HSA and QCT femoral neck geometry; these estimates were benchmarked to a 3D FEA of fall impact.


DXA-derived CSI and BSI computed from BMD and by HSA correlated well with each other (R = 0.92 and 0.70) and with QCT-derived indices (R = 0.83–0.85 and 0.65–0.72). The 2D strength estimate using HSA geometry correlated well with that from QCT (R = 0.76) and with the 3D FEA estimate (R = 0.56).


Femoral neck geometry computed by HSA from DXA data corresponds well enough to that from QCT for an analysis of load stress in the larger SWAN data set. Geometry derived from BMD data performed nearly as well. Proximal femur breaking strength estimated from 2D DXA data is not as well correlated with that derived by a 3D FEA using QCT data.


Bone mineral density DXA Fracture Hip Structure Analysis QCT Women 


  1. 1.
    Burge R, Dawson-Hughes B, Solomon DH, Wong JB, King A, Tosteson A (2007) Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025. J Bone Miner Res 22(3):465–475. doi:10.1359/jbmr.061113 PubMedCrossRefGoogle Scholar
  2. 2.
    Keaveny TM, Hoffmann PF, Singh M, Palermo L, Bilezikian JP, Greenspan SL, Black DM (2008) Femoral bone strength and its relation to cortical and trabecular changes after treatment with PTH, alendronate, and their combination as assessed by finite element analysis of quantitative CT scans. J Bone Miner Res 23(12):1974–1982. doi:10.1359/jbmr.080805 PubMedCrossRefGoogle Scholar
  3. 3.
    Keaveny TM, Kopperdahl DL, Melton LJ, Hoffmann PF, Amin S, Riggs BL, Khosla S (2010) Age-dependence of femoral strength in white women and men. J Bone Miner Res 25(5):994–1001. doi:10.1359/jbmr.091033 PubMedGoogle Scholar
  4. 4.
    Beck TJ, Looker AC, Mourtada F, Daphtary MM, Ruff CB (2006) Age trends in femur stresses from a simulated fall on the hip among men and women: evidence of homeostatic adaptation underlying the decline in hip BMD. J Bone Miner Res 21(9):1425–1432. doi:10.1359/jbmr.060617 PubMedCrossRefGoogle Scholar
  5. 5.
    Karlamangla A, Barrett-Connor E, Young J, Greendale G (2004) Hip fracture risk assessment using composite indices of femoral neck strength: the Rancho Bernardo study. Osteoporos Int 15(1):62–70PubMedCrossRefGoogle Scholar
  6. 6.
    Martin RB, Burr DB (1984) Non-invasive measurement of long bone cross-sectional moment of inertia by photon absorptiometry. J Biomech 17(3):195–201. doi:10.1016/0021-9290(84)90010-1 PubMedCrossRefGoogle Scholar
  7. 7.
    Camp JJ, Karwoski RA, Stacy MC, Atkinson EJ, Khosla S, Melton LJ, Riggs BL, Robb RA (2004) System for the analysis of whole-bone strength from helical CT images. In: Medical imaging 2004: physiology, function, and structure from medical images. SPIE, San Diego, pp 74–88Google Scholar
  8. 8.
    Keyak JH, Rossi SA, Jones KA, Skinner HB (1998) Prediction of femoral fracture load using automated finite element modeling. J Biomech 31(2):125–133. doi:S0021929097001231 PubMedCrossRefGoogle Scholar
  9. 9.
    Orwoll ES, Marshall LM, Nielson CM, Cummings SR, Lapidus J, Cauley JA, Ensrud K, Lane N, Hoffmann PR, Kopperdahl DL, Keaveny TM (2009) Finite element analysis of the proximal femur and hip fracture risk in older men. J Bone Miner Res 24(3):475–483. doi:10.1359/jbmr.081201 PubMedCrossRefGoogle Scholar
  10. 10.
    Sowers MR, Greendale GA, Bondarenko I, Finkelstein JS, Cauley JA, Neer RM, Ettinger B (2003) Endogenous hormones and bone turnover markers in pre- and perimenopausal women: SWAN. Osteoporos Int 14(3):191–197PubMedGoogle Scholar
  11. 11.
    Finkelstein JS, Lee M-LT, Sowers M, Ettinger B, Neer RM, Kelsey JL, Cauley JA, Huang M-H, Greendale GA (2002) Ethnic variation in bone density in premenopausal and early perimenopausal women: effects of anthropometric and lifestyle factors. J Clin Endocrinol Metab 87(7):3057–3067. doi:10.1210/jc.87.7.3057 PubMedCrossRefGoogle Scholar
  12. 12.
    Beck TJ, Ruff CB, Warden KE, Scott WW, Gopala UR (1990) Predicting femoral neck strength from bone mineral data: a structural approach. Invest Radiol 25(1):6–18PubMedCrossRefGoogle Scholar
  13. 13.
    Beck TJ, Looker AC, Ruff CB, Sievanen H, Wahner HW (2000) Structural trends in the aging femoral neck and proximal shaft: analysis of the third National Health and Nutrition Examination Survey dual-energy x-ray absorptiometry data. J Bone Miner Res 15(12):2297–2304. doi:10.1359/jbmr.2000.15.12.2297 PubMedCrossRefGoogle Scholar
  14. 14.
    Lewiecki EM, Keaveny TM, Kopperdahl DL, Genant HK, Engelke K, Fuerst T, Kivitz A, Davies RY, Fitzpatrick LA (2009) Once-monthly oral ibandronate improves biomechanical determinants of bone strength in women with postmenopausal osteoporosis. J Clin Endocrinol Metab 94(1):171–180. doi:10.1210/jc.2008-1807 PubMedCrossRefGoogle Scholar
  15. 15.
    Morgan EF, Keaveny TM (2001) Dependence of yield strain of human trabecular bone on anatomic site. J Biomech 34(5):569–577PubMedCrossRefGoogle Scholar
  16. 16.
    Morgan EF, Bayraktar HH, Keaveny TM (2003) Trabecular bone modulus–density relationships depend on anatomic site. J Biomech 36(7):897–904PubMedCrossRefGoogle Scholar
  17. 17.
    Bayraktar HH, Morgan EF, Niebur GL, Morris GE, Wong EK, Keaveny TM (2004) Comparison of the elastic and yield properties of human femoral trabecular and cortical bone tissue. J Biomech 37(1):27–35PubMedCrossRefGoogle Scholar
  18. 18.
    Ramamurthi K, Ahmad O, Engelke K, Taylor R, Zhu K, Gustafsson S, Prince R, Wilson K (2011) An in vivo comparison of hip structure analysis (HSA) with measurements obtained by QCT. Osteoporos Int March 11:1–9. doi:10.1007/s00198-011-1578-1 Google Scholar
  19. 19.
    Khoo BCC, Beck TJ, Qiao Q-H, Parakh P, Semanick L, Prince RL, Singer KP, Price RI (2005) In vivo short-term precision of hip structure analysis variables in comparison with bone mineral density using paired dual-energy X-ray absorptiometry scans from multi-center clinical trials. Bone 37(1):112–121. doi:10.1016/j.bone.2005.03.007 PubMedCrossRefGoogle Scholar
  20. 20.
    Verhulp E, van Rietbergen B, Huiskes R (2008) Load distribution in the healthy and osteoporotic human proximal femur during a fall to the side. Bone 42(1):30–35. doi:10.1016/j.bone.2007.08.039 PubMedCrossRefGoogle Scholar
  21. 21.
    Mayhew PM, Thomas CD, Clement JG, Loveridge N, Beck TJ, Bonfield W, Burgoyne CJ, Reeve J (2005) Relation between age, femoral neck cortical stability, and hip fracture risk. Lancet 366(9480):129–135. doi:10.1016/s0140-6736(05)66870-5 PubMedCrossRefGoogle Scholar
  22. 22.
    de Bakker PM, Manske SL, Ebacher V, Oxland TR, Cripton PA, Guy P (2009) During sideways falls proximal femur fractures initiate in the superolateral cortex: evidence from high-speed video of simulated fractures. J Biomech 42(12):1917–1925. doi:10.1016/j.jbiomech.2009.05.001 PubMedCrossRefGoogle Scholar
  23. 23.
    Schafer BW (2002) Local, Distortional, and Euler Buckling of Thin-Walled Columns. J Struct Eng 128(3):289–299CrossRefGoogle Scholar
  24. 24.
    Lee T, Choi JB, Schafer BW, Segars WP, Eckstein F, Kuhn V, Beck TJ (2009) Assessing the susceptibility to local buckling at the femoral neck cortex to age-related bone loss. Ann Biomed Eng 37(9):1910–1920. doi:10.1007/s10439-009-9751-9 PubMedCrossRefGoogle Scholar
  25. 25.
    Treece GM, Gee AH, Mayhew PM, Poole KES (2010) High resolution cortical bone thickness measurement from clinical CT data. Med Image Anal 14(3):276–290. doi:10.1016/j.media.2010.01.003 PubMedCrossRefGoogle Scholar
  26. 26.
    McLeish R, Charnley J (1970) Abduction forces in the one-legged stance. J Biomech 3(2):191–209PubMedCrossRefGoogle Scholar
  27. 27.
    Carter DR, Wilson CH (1976) Bone compressive strength: the influence of density and strain rate. Science 194(4270):1174–1176PubMedCrossRefGoogle Scholar

Copyright information

© International Osteoporosis Foundation and National Osteoporosis Foundation 2012

Authors and Affiliations

  • M. E. Danielson
    • 1
  • T. J. Beck
    • 2
  • A. S. Karlamangla
    • 3
  • G. A. Greendale
    • 3
  • E. J. Atkinson
    • 4
  • Y. Lian
    • 1
  • A. S. Khaled
    • 5
  • T. M. Keaveny
    • 6
  • D. Kopperdahl
    • 6
  • K. Ruppert
    • 1
  • S. Greenspan
    • 7
  • M. Vuga
    • 8
  • J. A. Cauley
    • 1
  1. 1.Department of EpidemiologyUniversity of PittsburghPittsburghUSA
  2. 2.Beck Radiological Innovations, Inc.CatonsvilleUSA
  3. 3.David Geffen School of MedicineUniversity of California, Los AngelesLos AngelesUSA
  4. 4.Division of Biomedical Statistics and InformaticsMayo ClinicRochesterUSA
  5. 5.Department of Electrical and Computer EngineeringJohns Hopkins UniversityBaltimoreUSA
  6. 6.O.N. DiagnosticsBerkeleyUSA
  7. 7.Department of MedicineUniversity of Pittsburgh Medical CenterPittsburghUSA
  8. 8.Department of PediatricsUniversity of PittsburghPittsburghUSA

Personalised recommendations