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7 Tesla MRI of bone microarchitecture discriminates between women without and with fragility fractures who do not differ by bone mineral density

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Abstract

Osteoporosis is a disease of poor bone quality. Bone mineral density (BMD) has limited ability to discriminate between subjects without and with poor bone quality, and assessment of bone microarchitecture may have added value in this regard. Our goals were to use 7 T MRI to: (1) quantify and compare distal femur bone microarchitecture in women without and with poor bone quality (defined clinically by presence of fragility fractures); and (2) determine whether microarchitectural parameters could be used to discriminate between these two groups. This study had institutional review board approval, and we obtained written informed consent from all subjects. We used a 28-channel knee coil to image the distal femur of 31 subjects with fragility fractures and 25 controls without fracture on a 7 T MRI scanner using a 3-D fast low angle shot sequence (0.234 mm × 0.234 mm × 1 mm, parallel imaging factor = 2, acquisition time = 7 min 9 s). We applied digital topological analysis to quantify parameters of bone microarchitecture. All subjects also underwent standard clinical BMD assessment in the hip and spine. Compared to controls, fracture cases demonstrated lower bone volume fraction and markers of trabecular number, plate-like structure, and plate-to-rod ratio, and higher markers of trabecular isolation, rod disruption, and network resorption (p < 0.05 for all). There were no differences in hip or spine BMD T-scores between groups (p > 0.05). In receiver-operating-characteristics analyses, microarchitectural parameters could discriminate cases and controls (AUC = 0.66–0.73, p < 0.05). Hip and spine BMD T-scores could not discriminate cases and controls (AUC = 0.58–0.64, p ≥ 0.08). We conclude that 7 T MRI can detect bone microarchitectural deterioration in women with fragility fractures who do not differ by BMD. Microarchitectural parameters might some day be used as an additional tool to detect patients with poor bone quality who cannot be detected by dual-energy X-ray absorptiometry (DXA).

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References

  1. Consensus development conference: diagnosis, prophylaxis, and treatment of osteoporosis (1993). Am J Med 94:646–650

  2. Kanis JA (2002) Diagnosis of osteoporosis and assessment of fracture risk. Lancet 359:1929–1936

    Article  PubMed  Google Scholar 

  3. Marshall D, Johnell O, Wedel H (1996) Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 312:1254–1259

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Management of osteoporosis in postmenopausal women: 2010 position statement of The North American Menopause Society (2010). Menopause 17:25–54; quiz 55–26

  5. Seeman E, Delmas PD (2006) Bone quality—the material and structural basis of bone strength and fragility. N Engl J Med 354:2250–2261

    Article  CAS  PubMed  Google Scholar 

  6. Cummings SR (1985) Are patients with hip fractures more osteoporotic? Review of the evidence. Am J Med 78:487–494

    Article  CAS  PubMed  Google Scholar 

  7. Wehrli FW (2007) Structural and functional assessment of trabecular and cortical bone by micro magnetic resonance imaging. J Magn Reson Imaging 25:390–409

    Article  PubMed  Google Scholar 

  8. Dempster DW (2000) The contribution of trabecular architecture to cancellous bone quality. J Bone Miner Res 15:20–23

    Article  CAS  PubMed  Google Scholar 

  9. Baum T, Kutscher M, Muller D et al (2013) Cortical and trabecular bone structure analysis at the distal radius-prediction of biomechanical strength by DXA and MRI. J Bone Miner Metab 31:212–221

    Article  CAS  PubMed  Google Scholar 

  10. Boehm HF, Horng A, Notohamiprodjo M et al (2008) Prediction of the fracture load of whole proximal femur specimens by topological analysis of the mineral distribution in DXA-scan images. Bone 43:826–831

    Article  PubMed  Google Scholar 

  11. Le Corroller T, Halgrin J, Pithioux M, Guenoun D, Chabrand P, Champsaur P (2012) Combination of texture analysis and bone mineral density improves the prediction of fracture load in human femurs. Osteoporos Int 23:163–169

    Article  PubMed  Google Scholar 

  12. Bohr H, Schaadt O (1983) Bone mineral content of femoral bone and the lumbar spine measured in women with fracture of the femoral neck by dual photon absorptiometry. Clin Orthop Relat Res 179:240–245

    Article  PubMed  Google Scholar 

  13. Ross PD, Davis JW, Vogel JM, Wasnich RD (1990) A critical review of bone mass and the risk of fractures in osteoporosis. Calcif Tissue Int 46:149–161

    Article  CAS  PubMed  Google Scholar 

  14. Cranney A, Jamal SA, Tsang JF, Josse RG, Leslie WD (2007) Low bone mineral density and fracture burden in postmenopausal women. CMAJ 177:575–580

    Article  PubMed Central  PubMed  Google Scholar 

  15. Stone KL, Seeley DG, Lui LY et al (2003) BMD at multiple sites and risk of fracture of multiple types: long-term results from the Study of Osteoporotic Fractures. J Bone Miner Res 18:1947–1954

    Article  PubMed  Google Scholar 

  16. Wainwright SA, Marshall LM, Ensrud KE et al (2005) Hip fracture in women without osteoporosis. J Clin Endocrinol Metab 90:2787–2793

    Article  CAS  PubMed  Google Scholar 

  17. Schuit SC, van der Klift M, Weel AE et al (2004) Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam Study. Bone 34:195–202

    Article  CAS  PubMed  Google Scholar 

  18. Link TM (2012) Osteoporosis imaging: state of the art and advanced imaging. Radiology 263:3–17

    Article  PubMed Central  PubMed  Google Scholar 

  19. Griffith JF, Engelke K, Genant HK (2010) Looking beyond bone mineral density: imaging assessment of bone quality. Ann NY Acad Sci 1192:45–56

    Article  PubMed  Google Scholar 

  20. Majumdar S (2002) Magnetic resonance imaging of trabecular bone structure. Top Magn Reson Imaging 13:323–334

    Article  PubMed  Google Scholar 

  21. Liu XS, Cohen A, Shane E et al (2010) Individual trabeculae segmentation (ITS)-based morphological analysis of high-resolution peripheral quantitative computed tomography images detects abnormal trabecular plate and rod microarchitecture in premenopausal women with idiopathic osteoporosis. J Bone Miner Res 25:1496–1505

    Article  PubMed Central  PubMed  Google Scholar 

  22. Melton LJ 3rd, Riggs BL, van Lenthe GH et al (2007) Contribution of in vivo structural measurements and load/strength ratios to the determination of forearm fracture risk in postmenopausal women. J Bone Miner Res 22:1442–1448

    Article  PubMed  Google Scholar 

  23. Nishiyama KK, Macdonald HM, Hanley DA, Boyd SK (2013) Women with previous fragility fractures can be classified based on bone microarchitecture and finite element analysis measured with HR-pQCT. Osteoporos Int 24:1733–1740. doi:10.1007/s00198-012-2160-1

    Google Scholar 

  24. Melton LJ 3rd, Christen D, Riggs BL et al (2010) Assessing forearm fracture risk in postmenopausal women. Osteoporos Int 21:1161–1169

    Article  PubMed Central  PubMed  Google Scholar 

  25. Boutroy S, Van Rietbergen B, Sornay-Rendu E, Munoz F, Bouxsein ML, Delmas PD (2008) Finite element analysis based on in vivo HR-pQCT images of the distal radius is associated with wrist fracture in postmenopausal women. J Bone Miner Res 23:392–399

    Article  PubMed  Google Scholar 

  26. Melton LJ 3rd, Riggs BL, Keaveny TM et al (2007) Structural determinants of vertebral fracture risk. J Bone Miner Res 22:1885–1892

    Article  PubMed  Google Scholar 

  27. Chang G, Wang L, Liang G, Babb JS, Saha PK, Regatte RR (2011) Reproducibility of subregional trabecular bone micro-architectural measures derived from 7-Tesla magnetic resonance images. MAGMA 24:121–125

    Article  PubMed Central  PubMed  Google Scholar 

  28. Chang G, Rajapakse CS, Diamond M et al (2013) Micro-finite element analysis applied to high-resolution MRI reveals improved bone mechanical competence in the distal femur of female pre-professional dancers. Osteoporos Int 24:1407–1417

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  29. Chang G, Rajapakse CS, Babb JS, Honig SP, Recht MP, Regatte RR (2012) In vivo estimation of bone stiffness at the distal femur and proximal tibia using ultra-high-field 7-Tesla magnetic resonance imaging and micro-finite element analysis. J Bone Miner Metab 30:243–251

    Article  PubMed Central  PubMed  Google Scholar 

  30. Saha PK, Chaudhuri BB (1996) 3D digital topology under binary transformation with applications. Comput Vis Image Underst 63:418–429

    Article  Google Scholar 

  31. Saha PK, Gomberg BR, Wehrli FW (2000) Three-dimensional digital topological characterization of cancellous bone architecture. Int J Imaging Syst Technol 11:81–90

    Article  Google Scholar 

  32. Kleerekoper M, Villanueva AR, Stanciu J, Rao DS, Parfitt AM (1985) The role of three-dimensional trabecular microstructure in the pathogenesis of vertebral compression fractures. Calcif Tissue Int 37:594–597

    Article  CAS  PubMed  Google Scholar 

  33. Amling M, Posl M, Ritzel H et al (1996) Architecture and distribution of cancellous bone yield vertebral fracture clues. A histomorphometric analysis of the complete spinal column from 40 autopsy specimens. Arch Orthop Trauma Surg 115:262–269

    Article  CAS  PubMed  Google Scholar 

  34. Majumdar S, Link TM, Augat P et al (1999) Trabecular bone architecture in the distal radius using magnetic resonance imaging in subjects with fractures of the proximal femur. Magnetic Resonance Science Center and Osteoporosis and Arthritis Research Group. Osteoporos Int 10:231–239

    Article  CAS  PubMed  Google Scholar 

  35. Wehrli FW, Hwang SN, Ma J, Song HK, Ford JC, Haddad JG (1998) Cancellous bone volume and structure in the forearm: noninvasive assessment with MR microimaging and image processing. Radiology 206:347–357

    Article  CAS  PubMed  Google Scholar 

  36. 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  CAS  PubMed  Google Scholar 

  37. Blumenkrantz G, Lindsey CT, Dunn TC et al (2004) A pilot, 2-year longitudinal study of the interrelationship between trabecular bone and articular cartilage in the osteoarthritic knee. Osteoarthr Cartil 12:997–1005

    Article  PubMed  Google Scholar 

  38. Chang G, Pakin SK, Schweitzer ME, Saha PK, Regatte RR (2008) Adaptations in trabecular bone microarchitecture in Olympic athletes determined by 7T MRI. J Magn Reson Imaging 27:1089–1095

    Article  PubMed  Google Scholar 

  39. Krug R, Carballido-Gamio J, Banerjee S et al (2007) In vivo bone and cartilage MRI using fully-balanced steady-state free-precession at 7 Tesla. Magn Reson Med 58:1294–1298

    Article  PubMed  Google Scholar 

  40. Regatte RR, Schweitzer ME (2007) Ultra-high-field MRI of the musculoskeletal system at 7.0T. J Magn Reson Imaging 25:262–269

    Article  PubMed  Google Scholar 

  41. Krug R, Stehling C, Kelley DA, Majumdar S, Link TM (2009) Imaging of the musculoskeletal system in vivo using ultra-high field magnetic resonance at 7 T. Invest Radiol 44:613–618

    Article  PubMed  Google Scholar 

  42. Wright SM, Wald LL (1997) Theory and application of array coils in MR spectroscopy. NMR Biomed 10:394–410

    Article  CAS  PubMed  Google Scholar 

  43. Chang G, Wiggins GC, ** of knee cartilage at 7T. J Magn Reson Imaging 35:441–448

    Article  PubMed Central  PubMed  Google Scholar 

  44. Wehrli FW, Gomberg BR, Saha PK, Song HK, Hwang SN, Snyder PJ (2001) Digital topological analysis of in vivo magnetic resonance microimages of trabecular bone reveals structural implications of osteoporosis. J Bone Miner Res 16:1520–1531

    Article  CAS  PubMed  Google Scholar 

  45. Nelson HD, Helfand M, Woolf SH, Allan JD (2002) Screening for postmenopausal osteoporosis: a review of the evidence for the US Preventive Services Task Force. Ann Intern Med 137:529–541

    Article  PubMed  Google Scholar 

Download references

Conflict of interest

The authors acknowledge grant support from the United States National Institutes of Health: NIAMS/NIH K23-AR059748, NIAMS/NIH RO1-AR053133, NIAMS/NIH RO1-AR056260, NIAMS/NIH RO1-AR060238. Otherwise, the authors have no financial disclosures or conflicts of interest.

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Authors and Affiliations

  1. Department of Radiology, NYU Langone Medical Center, Center for Musculoskeletal Care, 333 E. 38th Street, 6th Floor, Room 6-210, New York, NY, 10016, USA

    Gregory Chang

  2. Osteoporosis Center, Hospital for Joint Diseases, NYU Langone Medical Center, 301 E. 17th Street, Suite 1101, New York, NY, 10003, USA

    Stephen Honig

  3. Departments of Radiology and Electrical and Computer Engineering, University of Iowa, 3414 Seamans Center for the Engineering Arts and Sciences, Iowa City, IA, 52242, USA

    Yinxiao Liu, Cheng Chen & Punam K. Saha

  4. Department of Radiology, NYU Langone Medical Center, Center for Biomedical Imaging, 660 First Avenue, 4th Floor, New York, NY, 10016, USA

    Kevin K. Chu, Ding **a & Ravinder R. Regatte

  5. Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA

    Chamith S. Rajapakse

  6. Department of Orthopaedic Surgery, Hospital for Joint Diseases, NYU Langone Medical Center, 301 E. 17th Street, New York, NY, 10003, USA

    Kenneth Egol

Authors
  1. Gregory Chang
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Correspondence to Gregory Chang.

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Chang, G., Honig, S., Liu, Y. et al. 7 Tesla MRI of bone microarchitecture discriminates between women without and with fragility fractures who do not differ by bone mineral density. J Bone Miner Metab 33, 285–293 (2015). https://doi.org/10.1007/s00774-014-0588-4

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  • DOI: https://doi.org/10.1007/s00774-014-0588-4

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