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Fracture Prediction by Computed Tomography and Finite Element Analysis: Current and Future Perspectives

  • Biomechanics (G Niebur and J Wallace, Section Editors)
  • Published:
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A Correction to this article was published on 03 February 2022

This article has been updated

Abstract

Purpose of Review

This review critiques the ability of CT-based methods to predict incident hip and vertebral fractures.

Recent Findings

CT-based techniques with concurrent calibration all show strong associations with incident hip and vertebral fracture, predicting hip and vertebral fractures as well as, and sometimes better than, dual-energy X-ray absorptiometry areal biomass density (DXA aBMD). There is growing evidence for use of routine CT scans for bone health assessment.

Summary

CT-based techniques provide a robust approach for osteoporosis diagnosis and fracture prediction. It remains to be seen if further technical advances will improve fracture prediction compared to DXA aBMD. Future work should include more standardization in CT analyses, establishment of treatment intervention thresholds, and more studies to determine whether routine CT scans can be efficiently used to expand the number of individuals who undergo evaluation for fracture risk.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. Burge R, Dawson-Hughes B, Solomon DH, Wong JB, King A, Tosteson A. Incidence and economic burden of osteoporosis-related fractures in the United States, 2005-2025. J Bone Miner Res. 2007;22(3):465–75.

    Article  PubMed  Google Scholar 

  2. Cooper C, et al. Secular trends in the incidence of hip and other osteoporotic fractures. Osteoporos Int. 2011;22(5):1277–88.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Johnell O, Kanis JA. An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int. 2006;17(12):1726–33.

    Article  PubMed  CAS  Google Scholar 

  4. Sernbo I, Johnell O. Consequences of a hip fracture: a prospective study over 1 year. Osteoporos Int. 1993;3(3):148–53.

    Article  PubMed  CAS  Google Scholar 

  5. Binkley N, Blank RD, Leslie WD, Lewiecki EM, Eisman JA, Bilezikian JP. Osteoporosis in crisis: it’s time to focus on fracture. J Bone Miner Res. 2017;32(7):1391–4.

    Article  PubMed  Google Scholar 

  6. Khosla S, Shane E. A crisis in the treatment of osteoporosis. J Bone Miner Res. 2016;31(8):1485–7.

    Article  PubMed  Google Scholar 

  7. Curtis JR, Carbone L, Cheng H, Hayes B, Laster A, Matthews R, et al. Longitudinal trends in use of bone mass measurement among older Americans, 1999-2005. J Bone Miner Res. 2008;23(7):1061–7.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Warriner AH, Outman RC, Feldstein AC, Roblin DW, Allison JJ, Curtis JR, et al. Effect of self-referral on bone mineral density testing and osteoporosis treatment. Med Care. 2014;52(8):743–50.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Schuit SC, et al. Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam Study. Bone. 2004;34(1):195–202.

    Article  PubMed  CAS  Google Scholar 

  10. Wainwright SA, Marshall LM, Ensrud KE, Cauley JA, Black DM, Hillier TA, et al. Hip fracture in women without osteoporosis. J Clin Endocrinol Metab. 2005;90(5):2787–93.

    Article  PubMed  CAS  Google Scholar 

  11. Oden A, et al. Assessing the impact of osteoporosis on the burden of hip fractures. Calcif Tissue Int. 2013;92(1):42–9.

    Article  PubMed  CAS  Google Scholar 

  12. Black DM, Bouxsein ML, Marshall LM, Cummings SR, Lang TF, Cauley JA, et al. Proximal femoral structure and the prediction of hip fracture in men: a large prospective study using QCT. J Bone Miner Res. 2008;23(8):1326–33.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Borggrefe J, de Buhr T, Shrestha S, Marshall LM, Orwoll E, Peters K, et al. Association of 3D geometric measures derived from quantitative computed tomography with hip fracture risk in older men. J Bone Miner Res. 2016;31(8):1550–8.

    Article  PubMed  Google Scholar 

  14. Bousson VD, Adams J, Engelke K, Aout M, Cohen-Solal M, Bergot C, et al. In vivo discrimination of hip fracture with quantitative computed tomography: results from the prospective European Femur Fracture Study (EFFECT). J Bone Miner Res. 2011;26(4):881–93.

    Article  PubMed  Google Scholar 

  15. • Bredbenner TL, Mason RL, Havill LM, Orwoll ES, Nicolella DP, for the Osteoporotic Fractures in Men (MrOS) Study. Fracture risk predictions based on statistical shape and density modeling of the proximal femur. J Bone Miner Res. 2014;29(9):2090–100. Statistical shape and density modeling predicted incident hip fracture better than DXA aBMD among men in MrOS.

    Article  PubMed  Google Scholar 

  16. • Carballido-Gamio J, Harnish R, Saeed I, Streeper T, Sigurdsson S, Amin S, et al. Proximal femoral density distribution and structure in relation to age and hip fracture risk in women. J Bone Miner Res. 2013;28(3):537–46. Older Icelandic women who sustain incident hip fracture had deficits in the superior and inferior femoral neck cortex and the trabecular bone regions at the superior aspect of the femoral neck and the intertrochanteric region. This structural phenotype cannot be described as an accelerated pattern of normal age-related bone loss.

    Article  PubMed  Google Scholar 

  17. Carballido-Gamio J, Harnish R, Saeed I, Streeper T, Sigurdsson S, Amin S, et al. Structural patterns of the proximal femur in relation to age and hip fracture risk in women. Bone. 2013;57(1):290–9.

    Article  PubMed  Google Scholar 

  18. • Chalhoub D, Orwoll ES, Cawthon PM, Ensrud KE, Boudreau R, Greenspan S, et al. Areal and volumetric bone mineral density and risk of multiple types of fracture in older men. Bone. 2016;92:100–6. Lower aBMD and vBMD in the hip and spine were associated with increased fracture risk in the hip and spine, respectively, in 3301 men from the MrOS study. AUC analysis showed FN aBMD predicted hip fracture better than FN vBMD (0.76 vs. 0.72), but spine vBMD had better predictability of spine fracture than spine aBMD (0.79 vs. 0.72).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Cheng X, Li J, Lu Y, Keyak J, Lang T. Proximal femoral density and geometry measurements by quantitative computed tomography: association with hip fracture. Bone. 2007;40(1):169–74.

    Article  PubMed  CAS  Google Scholar 

  20. Ito M, Wakao N, Hida T, Matsui Y, Abe Y, Aoyagi K, et al. Analysis of hip geometry by clinical CT for the assessment of hip fracture risk in elderly Japanese women. Bone. 2010;46(2):453–7.

    Article  PubMed  Google Scholar 

  21. Johannesdottir F, Poole KES, Reeve J, Siggeirsdottir K, Aspelund T, Mogensen B, et al. Distribution of cortical bone in the femoral neck and hip fracture: a prospective case-control analysis of 143 incident hip fractures; the AGES-REYKJAVIK Study. Bone. 2011;48(6):1268–76.

    Article  PubMed  PubMed Central  Google Scholar 

  22. • Treece, G.M., Gee A.H., Tonkin C., Ewing S.K., Cawthon P.M., Black D.M., Poole K.E.S., for the Osteoporotic Fractures in Men (MrOS) Study, Predicting hip fracture type with cortical bone mapping (CBM) in the osteoporotic fractures in men (MrOS) study. J Bone Miner Res, 2015. 30(11): p. 2067–2077. Using cortical bone mapping, they identified focal regions of thin cortical bone and larger trabecular bone defects that predicted incident hip fracture in men. The fracture prediction performance was slightly better than DXA aBMD.

  23. Yang L, Burton AC, Bradburn M, Nielson CM, Orwoll ES, Eastell R, et al. Distribution of bone density in the proximal femur and its association with hip fracture risk in older men: the osteoporotic fractures in men (MrOS) study. J Bone Miner Res. 2012;27(11):2314–24.

    Article  PubMed  Google Scholar 

  24. Yu A, Carballido-Gamio J, Wang L, Lang TF, Su Y, Wu X, et al. Spatial differences in the distribution of bone between femoral neck and trochanteric fractures. J Bone Miner Res. 2017;32(8):1672–80.

    Article  PubMed  Google Scholar 

  25. Falcinelli C, Schileo E, Balistreri L, Baruffaldi F, Bordini B, Viceconti M, et al. Multiple loading conditions analysis can improve the association between finite element bone strength estimates and proximal femur fractures: a preliminary study in elderly women. Bone. 2014;67(Supplement C):71–80.

    Article  PubMed  Google Scholar 

  26. Keyak JH, Sigurdsson S, Karlsdottir G, Oskarsdottir D, Sigmarsdottir A, Zhao S, et al. Male-female differences in the association between incident hip fracture and proximal femoral strength: a finite element analysis study. Bone. 2011;48(6):1239–45.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Keyak JH, Sigurdsson S, Karlsdottir GS, Oskarsdottir D, Sigmarsdottir A, Kornak J, et al. Effect of finite element model loading condition on fracture risk assessment in men and women: the AGES-Reykjavik study. Bone. 2013;57(1):18–29.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Kopperdahl DL, Aspelund T, Hoffmann PF, Sigurdsson S, Siggeirsdottir K, Harris TB, et al. Assessment of incident spine and hip fractures in women and men using finite element analysis of CT scans. J Bone Miner Res. 2014;29(3):570–80.

    Article  PubMed  Google Scholar 

  29. Nishiyama KK, Ito M, Harada A, Boyd SK. Classification of women with and without hip fracture based on quantitative computed tomography and finite element analysis. Osteoporos Int. 2014;25(2):619–26.

    Article  PubMed  CAS  Google Scholar 

  30. Orwoll ES, Marshall LM, Nielson CM, Cummings SR, Lapidus J, Cauley JA, et al. Finite element analysis of the proximal femur and hip fracture risk in older men. J Bone Miner Res. 2009;24(3):475–83.

    Article  PubMed  Google Scholar 

  31. Wang X, Sanyal A, Cawthon PM, Palermo L, Jekir M, Christensen J, et al. Prediction of new clinical vertebral fractures in elderly men using finite element analysis of CT scans. J Bone Miner Res. 2012;27(4):808–16.

    Article  PubMed  Google Scholar 

  32. Qasim M, Farinella G, Zhang J, Li X, Yang L, Eastell R, et al. Patient-specific finite element estimated femur strength as a predictor of the risk of hip fracture: the effect of methodological determinants. Osteoporos Int. 2016;27(9):2815–22.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Berrington de Gonzalez A, et al. Projected cancer risks from computed tomographic scans performed in the United States in 2007. Arch Intern Med. 2009;169(22):2071–7.

    Article  PubMed  Google Scholar 

  34. Zhang J, Delzell E, Zhao H, Laster AJ, Saag KG, Kilgore ML, et al. Central DXA utilization shifts from office-based to hospital-based settings among Medicare beneficiaries in the wake of reimbursement changes. J Bone Miner Res. 2012;27(4):858–64.

    Article  PubMed  Google Scholar 

  35. Smith KE, Whiting BR, Reiker GG, Commean PK, Sinacore DR, Prior FW. Assessment of technical and biological parameters of volumetric quantitative computed tomography of the foot: a phantom study. Osteoporos Int. 2012;23(7):1977–85.

    Article  PubMed  CAS  Google Scholar 

  36. Kang Y, Engelke K, Fuchs C, Kalender WA. An anatomic coordinate system of the femoral neck for highly reproducible BMD measurements using 3D QCT. Comput Med Imaging Graph. 2005;29(7):533–41.

    Article  PubMed  Google Scholar 

  37. Kang Y, Engelke K, Kalender WA. A new accurate and precise 3-D segmentation method for skeletal structures in volumetric CT data. IEEE Trans Med Imaging. 2003;22(5):586–98.

    Article  PubMed  Google Scholar 

  38. Lang TF, Keyak JH, Heitz MW, Augat P, Lu Y, Mathur A, et al. Volumetric quantitative computed tomography of the proximal femur: precision and relation to bone strength. Bone. 1997;21(1):101–8.

    Article  PubMed  CAS  Google Scholar 

  39. Li N, et al. Comparison of QCT and DXA: osteoporosis detection rates in postmenopausal women. Int J Endocrinol. 2013;2013:895474.

    PubMed  PubMed Central  Google Scholar 

  40. Poole KE, Mayhew PM, Rose CM, Brown JK, Bearcroft PJ, Loveridge N, et al. Changing structure of the femoral neck across the adult female lifespan. J Bone Miner Res. 2010;25(3):482–91.

    Article  PubMed  Google Scholar 

  41. Treece GM, Gee AH, Mayhew PM, Poole KES. High resolution cortical bone thickness measurement from clinical CT data. Med Image Anal. 2010;14(3):276–90.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Treece GM, Poole KE, Gee AH. Imaging the femoral cortex: thickness, density and mass from clinical CT. Med Image Anal. 2012;16(5):952–65.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Yang L, Maric I, McCloskey EV, Eastell R. Shape, structural properties, and cortical stability along the femoral neck: a study using clinical QCT. J Clin Densitom. 2008;11(3):373–82.

    Article  PubMed  Google Scholar 

  44. Davis KA, Burghardt AJ, Link TM, Majumdar S. The effects of geometric and threshold definitions on cortical bone metrics assessed by in vivo high-resolution peripheral quantitative computed tomography. Calcif Tissue Int. 2007;81(5):364–71.

    Article  PubMed  CAS  Google Scholar 

  45. Hangartner TN, Gilsanz V. Evaluation of cortical bone by computed tomography. J Bone Miner Res. 1996;11(10):1518–25.

    Article  PubMed  CAS  Google Scholar 

  46. Prevrhal S, Engelke K, Kalender WA. Accuracy limits for the determination of cortical width and density: the influence of object size and CT imaging parameters. Phys Med Biol. 1999;44(3):751–64.

    Article  PubMed  CAS  Google Scholar 

  47. Prevrhal S, Fox JC, Shepherd JA, Genant HK. Accuracy of CT-based thickness measurement of thin structures: modeling of limited spatial resolution in all three dimensions. Med Phys. 2003;30(1):1–8.

    Article  PubMed  Google Scholar 

  48. Newman DL, Dougherty G, Obaid AA, Hajrasy HA. Limitations of clinical CT in assessing cortical thickness and density. Phys Med Biol. 1998;43(3):619–26.

    Article  PubMed  CAS  Google Scholar 

  49. Adams, J.E., Quantitative computed tomography. Eur J Radiol. 71(3): 415–424, 2009.

  50. Engelke K. Quantitative computed tomography-current status and new developments. J Clin Densitom. 2017;20(3):309–21.

    Article  PubMed  Google Scholar 

  51. Carballido-Gamio J, Nicolella DP. Computational anatomy in the study of bone structure. Curr Osteoporos Rep. 2013;11(3):237–45.

    Article  PubMed  Google Scholar 

  52. Lengsfeld M, Schmitt J, Alter P, Kaminsky J, Leppek R. Comparison of geometry-based and CT voxel-based finite element modelling and experimental validation. Med Eng Phys. 1998;20(7):515–22.

    Article  PubMed  CAS  Google Scholar 

  53. Helgason, B., Perilli E., Schileo E., Taddei F., Brynjólfsson S., Viceconti M., Mathematical relationships between bone density and mechanical properties: a literature review. Clin Biomech (Bristol, Avon), 2008. 23(2): p. 135–146.

  54. Engelke K, Adams JE, Armbrecht G, Augat P, Bogado CE, Bouxsein ML, et al. Clinical use of quantitative computed tomography and peripheral quantitative computed tomography in the management of osteoporosis in adults: the 2007 ISCD Official Positions. J Clin Densitom. 2008;11(1):123–62.

    Article  PubMed  Google Scholar 

  55. Engelke K, Lang T, Khosla S, Qin L, Zysset P, Leslie WD, et al. Clinical use of quantitative computed tomography (QCT) of the hip in the management of osteoporosis in adults: the 2015 ISCD Official Positions—part I. J Clin Densitom. 2015;18(3):338–58.

    Article  PubMed  Google Scholar 

  56. Zysset P, Qin L, Lang T, Khosla S, Leslie WD, Shepherd JA, et al. Clinical use of quantitative computed tomography–based finite element analysis of the hip and spine in the management of osteoporosis in adults: the 2015 ISCD Official Positions—part II. J Clin Densitom. 2015;18(3):359–92.

    Article  PubMed  Google Scholar 

  57. Poole KES, et al. Focal osteoporosis defects play a key role in hip fracture. Bone. 2017;94:124–34.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Johannesdottir F, Turmezei T, Poole KE. Cortical bone assessed with clinical computed tomography at the proximal femur. J Bone Miner Res. 2014;29(4):771–83.

    Article  PubMed  Google Scholar 

  59. Anderson DE, Demissie S, Allaire BT, Bruno AG, Kopperdahl DL, Keaveny TM, et al. The associations between QCT-based vertebral bone measurements and prevalent vertebral fractures depend on the spinal locations of both bone measurement and fracture. Osteoporos Int. 2014;25(2):559–66.

    Article  PubMed  CAS  Google Scholar 

  60. Borggrefe J, Giravent S, Thomsen F, Peña J, Campbell G, Wulff A, et al. Association of QCT bone mineral density and bone structure with vertebral fractures in patients with multiple myeloma. J Bone Miner Res. 2015;30(7):1329–37.

    Article  PubMed  CAS  Google Scholar 

  61. Rianon NJ, Lang TF, Siggeirsdottir K, Sigurdsson G, Eiriksdottir G, Sigurdsson S, et al. Fracture risk assessment in older adults using a combination of selected quantitative computed tomography bone measures: a subanalysis of the Age, Gene/Environment Susceptibility-Reykjavik Study. J Clin Densitom. 2014;17(1):25–31.

    Article  PubMed  Google Scholar 

  62. Cody DD, Gross GJ, J. Hou F, Spencer HJ, Goldstein SA, P. Fyhrie D. Femoral strength is better predicted by finite element models than QCT and DXA. J Biomech. 1999;32(10):1013–20.

    Article  PubMed  CAS  Google Scholar 

  63. Johannesdottir F, Thrall E, Muller J, Keaveny TM, Kopperdahl DL, Bouxsein ML. Comparison of non-invasive assessments of strength of the proximal femur. Bone. 2017;105:93–102.

    Article  PubMed  Google Scholar 

  64. Zysset PK, et al. Finite element analysis for prediction of bone strength. Bonekey Rep. 2013;2:386.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Blank JB, Cawthon PM, Carrion-Petersen ML, Harper L, Johnson JP, Mitson E, et al. Overview of recruitment for the osteoporotic fractures in men study (MrOS). Contemp Clin Trials. 2005;26(5):557–68.

    Article  PubMed  Google Scholar 

  66. Orwoll E, Blank JB, Barrett-Connor E, Cauley J, Cummings S, Ensrud K, et al. Design and baseline characteristics of the osteoporotic fractures in men (MrOS) study—a large observational study of the determinants of fracture in older men. Contemp Clin Trials. 2005;26(5):569–85.

    Article  PubMed  Google Scholar 

  67. Harris TB, Launer LJ, Eiriksdottir G, Kjartansson O, Jonsson PV, Sigurdsson G, et al. Age, Gene/Environment Susceptibility-Reykjavik Study: multidisciplinary applied phenomics. Am J Epidemiol. 2007;165(9):1076–87.

    Article  PubMed  Google Scholar 

  68. Napoli N, et al. Vertebral fracture risk in diabetic elderly men: the MrOS study. J Bone Miner Res. 2017;

  69. Gausden EB, Nwachukwu BU, Schreiber JJ, Lorich DG, Lane JM. Opportunistic use of CT imaging for osteoporosis screening and bone density assessment: a qualitative systematic review. J Bone Joint Surg Am. 2017;99(18):1580–90.

    Article  PubMed  Google Scholar 

  70. Brett AD, Brown JK. Quantitative computed tomography and opportunistic bone density screening by dual use of computed tomography scans. Journal of Orthopaedic Translation. 2015;3(4):178–84.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Habashy AH, Yan X, Brown JK, Xiong X, Kaste SC. Estimation of bone mineral density in children from diagnostic CT images: a comparison of methods with and without an internal calibration standard. Bone. 2011;48(5):1087–94.

    Article  PubMed  Google Scholar 

  72. • Pickhardt PJ, Bodeen G, Brett A, Brown JK, Binkley N. Comparison of femoral neck BMD evaluation obtained using lunar DXA and QCT with asynchronous calibration from CT colonography. J Clin Densitom. 2015;18(1):5–12. QCT-based aBMD by CTXA was highly correlated ( R 2 =0.91) with DXA aBMD in females who underwent computed tomography colonography with asynchronous QCT calibration, evidence that CTXA T -scores may be an option for opportunistic osteoporosis screening in scans without contrast.

    Article  PubMed  Google Scholar 

  73. Boden SD, Goodenough DJ, Stockham CD, Jacobs E, Dina T, Allman RM. Precise measurement of vertebral bone density using computed tomography without the use of an external reference phantom. J Digit Imaging. 1989;2(1):31–8.

    Article  PubMed  CAS  Google Scholar 

  74. Gudmundsdottir H, Jonsdottir B, Kristinsson S, Johannesson A, Goodenough D, Sigurdsson G. Vertebral bone density in Icelandic women using quantitative computed tomography without an external reference phantom. Osteoporos Int. 1993;3(2):84–9.

    Article  PubMed  CAS  Google Scholar 

  75. • Lee DC, Hoffmann PF, Kopperdahl DL, Keaveny TM. Phantomless calibration of CT scans for measurement of BMD and bone strength-inter-operator reanalysis precision. Bone. 2017;103:325–33. Reanalysis precision errors for all phantomless (internal calibration) measurements were as good as or better than those from phantom calibration. Differences in absolute measurements between phantom and phantomless were less than 1%, indicating bone measurements can be obtained from CT scans without calibration phantoms.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Mueller DK, Kutscherenko A, Bartel H, Vlassenbroek A, Ourednicek P, Erckenbrecht J. Phantom-less QCT BMD system as screening tool for osteoporosis without additional radiation. Eur J Radiol. 2011;79(3):375–81.

    Article  PubMed  Google Scholar 

  77. Emohare O, Dittmer A, Morgan RA, Switzer JA, Polly DW Jr. Osteoporosis in acute fractures of the cervical spine: the role of opportunistic CT screening. J Neurosurg Spine. 2015;23(1):1–7.

    Article  PubMed  Google Scholar 

  78. Pickhardt PJ, Pooler BD, Lauder T, del Rio AM, Bruce RJ, Binkley N. Opportunistic screening for osteoporosis using abdominal computed tomography scans obtained for other indications. Ann Intern Med. 2013;158(8):588–95.

    Article  PubMed  PubMed Central  Google Scholar 

  79. • Lee SJ, Anderson PA, Pickhardt PJ. Predicting future hip fractures on routine abdominal CT using opportunistic osteoporosis screening measures: a matched case-control study. AJR Am J Roentgenol. 2017;209(2):395–402. Asynchronously calibrated lumbar spine attenuation and CT-derived FN T-score were associated with future hip fracture in a cohort of 204 hip fracture cases and 204 age-sex matched controls with previous abdominopelvic CT scans.

    Article  PubMed  Google Scholar 

  80. Kaesmacher J, Liebl H, Baum T, Kirschke JS. Bone mineral density estimations from routine multidetector computed tomography: a comparative study of contrast and calibration effects. J Comput Assist Tomogr. 2017;41(2):217–23.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Gruber M, Bauer JS, Dobritz M, Beer AJ, Wolf P, Woertler K, et al. Bone mineral density measurements of the proximal femur from routine contrast-enhanced MDCT data sets correlate with dual-energy X-ray absorptiometry. Eur Radiol. 2013;23(2):505–12.

    Article  PubMed  CAS  Google Scholar 

  82. • Pompe E, Willemink MJ, Dijkhuis GR, Verhaar HJJ, Hoesein FAAM, de Jong PA. Intravenous contrast injection significantly affects bone mineral density measured on CT. Eur Radiol. 2015;25(2):283–9. Contrast injection has a significant influence on direct CT-derived attenuation in the spine, which may lead to an underestimation of osteoporosis—adjustment for injection phase or internal calibration is necessary to account for IV contrast.

    Article  PubMed  Google Scholar 

  83. • Ziemlewicz TJ, Maciejewski A, Binkley N, Brett AD, Brown JK, Pickhardt PJ. Opportunistic quantitative CT bone mineral density measurement at the proximal femur using routine contrast-enhanced scans: direct comparison with DXA in 355 adults. J Bone Miner Res. 2016;31(10):1835–40. Showed high correlation ( r 2 =0.82) between DXA and CTXA in contrast-enhanced CT scans in both men and women. CTXA provided similar T -scores as DXA, which may allow for identification of patients at risk for fracture.

    Article  PubMed  CAS  Google Scholar 

  84. Pickhardt PJ, Lauder T, Pooler BD, Muñoz del Rio A, Rosas H, Bruce RJ, et al. Effect of IV contrast on lumbar trabecular attenuation at routine abdominal CT: correlation with DXA and implications for opportunistic osteoporosis screening. Osteoporos Int. 2016;27(1):147–52.

    Article  PubMed  CAS  Google Scholar 

  85. Cann CE, Adams JE, Brown JK, Brett AD. CTXA hip—an extension of classical DXA measurements using quantitative CT. PLoS One. 2014;9(3):e91904.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  86. McCloskey E, Johansson H, Oden A, Kanis JA. Fracture risk assessment. Clin Biochem. 2012;45(12):887–93.

    Article  PubMed  Google Scholar 

  87. Brown JK, Timm W, Bodeen G, Chason A, Perry M, Vernacchia F, et al. Asynchronously calibrated quantitative bone densitometry. J Clin Densitom. 2017;20(2):216–25.

    Article  PubMed  CAS  Google Scholar 

  88. Fidler JL, Murthy NS, Khosla S, Clarke BL, Bruining DH, Kopperdahl DL, et al. Comprehensive assessment of osteoporosis and bone fragility with CT colonography. Radiology. 2016;278(1):172–80.

    Article  PubMed  Google Scholar 

  89. Weber NK, Fidler JL, Keaveny TM, Clarke BL, Khosla S, Fletcher JG, et al. Validation of a CT-derived method for osteoporosis screening in IBD patients undergoing contrast-enhanced CT enterography. Am J Gastroenterol. 2014;109(3):401–8.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Lee, SJ, Graffy PM, Zea RD, Ziemlewicz TJ, Pickhardt PJ. Future osteoporotic fracture risk related to lumbar vertebral trabecular attenuation measured at routine body CT. J Bone Miner Res, 2018;33(5):860–7.

  91. • Adams A, Fischer H, Kopperdahl DL. The Fracture, Osteoporosis, and CT Utilization Study (FOCUS)—utilizing pre-existing CT to assess risk of hip fracture in a large real-world clinical setting. J Bone Miner Res. 2017;32(Suppl 1) https://doi.org/10.1002/jbmr.3423. The Fracture, Osteoporosis, and CT Utilization Study showed that finite element analysis of previously obtained routine CT scans could predict hip fracture as well as DXA aBMD.

  92. • Shepstone L, Lenaghan E, Cooper C, Clarke S, Fong-Soe-Khioe R, Fordham R, et al. Screening in the community to reduce fractures in older women (SCOOP): a randomised controlled trial. Lancet. 2018;391:741–7. https://doi.org/10.1016/S0140-6736(17)32640-5. This study reported that community-based osteoporosis screening of fracture risk in older women in the UK is feasible and could be effective in reducing the incidence of hip fractures.

    Article  PubMed  Google Scholar 

  93. Rossman T, Kushvaha V, Dragomir-Daescu D. QCT/FEA predictions of femoral stiffness are strongly affected by boundary condition modeling. Comput Methods Biomech Biomed Engin. 2016;19(2):208–16.

    Article  PubMed  Google Scholar 

  94. Helgason B, Gilchrist S, Ariza O, Vogt P, Enns-Bray W, Widmer RP, et al. The influence of the modulus-density relationship and the material mapping method on the simulated mechanical response of the proximal femur in side-ways fall loading configuration. Med Eng Phys. 2016;38(7):679–89.

    Article  PubMed  CAS  Google Scholar 

  95. Poole KE, Treece GM, Gee AH, Brown JP, McClung MR, Wang A, et al. Denosumab rapidly increases cortical bone in key locations of the femur: a 3D bone mapping study in women with osteoporosis. J Bone Miner Res. 2015;30(1):46–54.

    Article  PubMed  CAS  Google Scholar 

  96. Whitmarsh T, Treece GM, Gee AH, Poole KES. Mapping bone changes at the proximal femoral cortex of postmenopausal women in response to alendronate and teriparatide alone, combined or sequentially. J Bone Miner Res. 2015;30(7):1309–18.

    Article  PubMed  CAS  Google Scholar 

  97. Allison SJ, Poole KES, Treece GM, Gee AH, Tonkin C, Rennie WJ, et al. The influence of high-impact exercise on cortical and trabecular bone mineral content and 3D distribution across the proximal femur in older men: a randomized controlled unilateral intervention. J Bone Miner Res. 2015;30(9):1709–16.

    Article  PubMed  CAS  Google Scholar 

  98. Seeherman HJ, Li XJ, Smith E, Parkington J, Li R, Wozney JM. Intraosseous injection of rhBMP-2/calcium phosphate matrix improves bone structure and strength in the proximal aspect of the femur in chronic ovariectomized nonhuman primates. J Bone Joint Surg Am. 2013;95(1):36–47.

    Article  PubMed  Google Scholar 

  99. Cummings SR, Nevitt MC, Browner WS, Stone K, Fox KM, Ensrud KE, et al. Risk factors for hip fracture in white women. Study of Osteoporotic Fractures Research Group. N Engl J Med. 1995;332(12):767–73.

    Article  PubMed  CAS  Google Scholar 

  100. Greenspan SL, Myers ER, Kiel DP, Parker RA, Hayes WC, Resnick NM. Fall direction, bone mineral density, and function: risk factors for hip fracture in frail nursing home elderly. Am J Med. 1998;104(6):539–45.

    Article  PubMed  CAS  Google Scholar 

  101. Greenspan SL, Myers ER, Maitland LA, Resnick NM, Hayes WC. Fall severity and bone mineral density as risk factors for hip fracture in ambulatory elderly. Jama. 1994;271(2):128–33.

    Article  PubMed  CAS  Google Scholar 

  102. Hayes WC, Myers ER, Morris JN, Gerhart TN, Yett HS, Lipsitz LA. Impact near the hip dominates fracture risk in elderly nursing home residents who fall. Calcif Tissue Int. 1993;52(3):192–8.

    Article  PubMed  CAS  Google Scholar 

  103. Hwang HF, Lee HD, Huang HH, Chen CY, Lin MR. Fall mechanisms, bone strength, and hip fractures in elderly men and women in Taiwan. Osteoporos Int. 2011;22(8):2385–93.

    Article  PubMed  Google Scholar 

  104. Nevitt MC, Cummings SR. Type of fall and risk of hip and wrist fractures: the study of osteoporotic fractures. The Study of Osteoporotic Fractures Research Group. J Am Geriatr Soc. 1993;41(11):1226–34.

    Article  PubMed  CAS  Google Scholar 

  105. Bouxsein ML, Szulc P, Munoz F, Thrall E, Sornay-Rendu E, Delmas PD. Contribution of trochanteric soft tissues to fall force estimates, the factor of risk, and prediction of hip fracture risk. J Bone Miner Res. 2007;22(6):825–31.

    Article  PubMed  Google Scholar 

  106. Choi WJ, Russell CM, Tsai CM, Arzanpour S, Robinovitch SN. Age-related changes in dynamic compressive properties of trochanteric soft tissues over the hip. J Biomech. 2015;48(4):695–700.

    Article  PubMed  CAS  Google Scholar 

  107. Dufour AB, Roberts B, Broe KE, Kiel DP, Bouxsein ML, Hannan MT. The factor-of-risk biomechanical approach predicts hip fracture in men and women: the Framingham Study. Osteoporos Int. 2012;23(2):513–20.

    Article  PubMed  CAS  Google Scholar 

  108. Robinovitch SN, McMahon TA, Hayes WC. Force attenuation in trochanteric soft tissues during impact from a fall. J Orthop Res. 1995;13(6):956–62.

    Article  PubMed  CAS  Google Scholar 

  109. Yang Y, Mackey DC, Liu-Ambrose T, Feldman F, Robinovitch SN. Risk factors for hip impact during real-life falls captured on video in long-term care. Osteoporos Int. 2016;27(2):537–47.

    Article  PubMed  CAS  Google Scholar 

  110. Sarvi MN, Luo Y. A two-level subject-specific biomechanical model for improving prediction of hip fracture risk. Clin Biomech (Bristol, Avon). 2015;30(8):881–7.

    Article  Google Scholar 

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Funding

This article was supported by NHI fund. Grant Number: R01 AR053986, PI:Mary L. Bouxsein.

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Correspondence to Fjola Johannesdottir.

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Fjola Johannesdottir, Brett Allaire, and Mary Bouxsein declare no conflict of interest.

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Johannesdottir, F., Allaire, B. & Bouxsein, M.L. Fracture Prediction by Computed Tomography and Finite Element Analysis: Current and Future Perspectives. Curr Osteoporos Rep 16, 411–422 (2018). https://doi.org/10.1007/s11914-018-0450-z

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