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Current Osteoporosis Reports

, Volume 14, Issue 6, pp 359–373 | Cite as

A Comparison of Peripheral Imaging Technologies for Bone and Muscle Quantification: a Mixed Methods Clinical Review

  • Andy Kin On Wong
Muscle and Bone (L Bonewald and M Hamrick, Section Editors)
Part of the following topical collections:
  1. Topical Collection on Muscle and Bone

Abstract

Purpose of Review

Bone and muscle peripheral imaging technologies are reviewed for their association with fractures and frailty. A narrative systematized review was conducted for bone and muscle parameters from each imaging technique. In addition, meta-analyses were performed across all bone quality parameters.

Recent Findings

The current body of evidence for bone quality’s association with fractures is strong for (high-resolution) peripheral quantitative computed tomography (pQCT), with trabecular separation (Tb.Sp) and integral volumetric bone mineral density (vBMD) reporting consistently large associations with various fracture types across studies. Muscle has recently been linked to fractures and frailty, but the quality of evidence remains weaker from studies of small sample sizes.

Summary

It is increasingly apparent that musculoskeletal tissues have a complex relationship with interrelated clinical endpoints such as fractures and frailty. Future studies must concurrently address these relationships in order to decipher the relative importance of one causal pathway from another.

Keywords

Peripheral quantitative computed tomography Magnetic resonance imaging Bone and muscle quality Fractures Frailty Meta-analysis 

Notes

Compliance with Ethical Standards

Conflict of Interest

Andy Kin On Wong declares no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group. World Health Organ Tech Rep Ser. 1994;843:1–129.Google Scholar
  2. 2.
    Cheung AM, Detsky AS. Osteoporosis and fractures: missing the bridge? Jama. 2008;299(12):1468–70.CrossRefPubMedGoogle Scholar
  3. 3.
    Hillier TA, Beck TJ, Oreskovic T, Rizzo JH, Pedula KL, Black DM. Predicting long-term hip fracture risk with bone mineral density and hip structure in postmenopausal women: the study of osteoporotic fractures (SOF). J Bone Miner Res. 2003;18:S21.CrossRefGoogle Scholar
  4. 4.
    Felsenberg D, Boonen S. The bone quality framework: determinants of bone strength and their interrelationships, and implications for osteoporosis management. Clin Ther. 2005;27(1):1–11.CrossRefPubMedGoogle Scholar
  5. 5.
    Ferretti JL, Cointry GR, Capozza RF, Frost HM. Bone mass, bone strength, muscle-bone interactions, osteopenias and osteoporoses. Mech Ageing Dev. 2003;124(3):269–79. Epub 2003/03/29.CrossRefPubMedGoogle Scholar
  6. 6.
    Wong AK, Beattie KA, Min KK, Webber CE, Gordon CL, Papaioannou A, et al. A Trimodality comparison of volumetric bone imaging technologies. Part I: short-term precision and validity. J Clin Densitom. 2014. Epub 2014/08/19.Google Scholar
  7. 7.
    Wong AK, Hummel K, Moore C, Beattie KA, Shaker S, Craven BC, et al. Improving reliability of pQCT-derived muscle area and density measures using a watershed algorithm for muscle and fat segmentation. J Clin Densitom. 2014. Epub 2014/07/06Google Scholar
  8. 8.•
    Wong AK, Beattie KA, Min KK, Gordon C, Pickard L, Papaioannou A, et al. Peripheral quantitative computed tomography-derived muscle density and peripheral magnetic resonance imaging-derived muscle adiposity: precision and associations with fragility fractures in women. J Musculoskelet Neuronal Interact. 2014;14(4):401–10. Breaks down association between muscle density and fractures by accounting for inter- and intramuscular fat.PubMedPubMedCentralGoogle Scholar
  9. 9.
    Wong AK, Beattie KA, Min KK, Merali Z, Webber CE, Gordon CL, et al. A Trimodality comparison of volumetric bone imaging technologies. Part II: 1-Yr Change, Long-Term Precision, and Least Significant Change. J Clin Densitom. 2014. Epub 2014/08/19.Google Scholar
  10. 10.••
    van Rietbergen B, Ito K. A survey of micro-finite element analysis for clinical assessment of bone strength: the first decade. J Biomech. 2015;48(5):832–41. Epub 2015/01/03. Provides a meta-analysis of finite element analysis variables and their associations with fractures, not included in the present clinical review.Google Scholar
  11. 11.
    Melton 3rd LJ, Riggs BL, van Lenthe GH, Achenbach SJ, Muller R, Bouxsein ML, et al. Contribution of in vivo structural measurements and load/strength ratios to the determination of forearm fracture risk in postmenopausal women. J Bone Miner Res. 2007;22(9):1442–8.CrossRefPubMedGoogle Scholar
  12. 12.
    Melton 3rd LJ, Riggs BL, Keaveny TM, Achenbach SJ, Hoffmann PF, Camp JJ, et al. Structural determinants of vertebral fracture risk. J Bone Miner Res. 2007;22(12):1885–92.CrossRefPubMedGoogle Scholar
  13. 13.
    Melton 3rd LJ, Christen D, Riggs BL, Achenbach SJ, Muller R, van Lenthe GH, et al. Assessing forearm fracture risk in postmenopausal women. Osteoporos Int. 2010;21(7):1161–9. Epub 2009/08/29.CrossRefPubMedGoogle Scholar
  14. 14.
    Boutroy S, Van Rietbergen B, Sornay-Rendu E, Munoz F, Bouxsein ML, Delmas PD. 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. 2008;23(3):392–9.CrossRefPubMedGoogle Scholar
  15. 15.
    Sornay-Rendu E, Boutroy S, Munoz F, Delmas PD. Alterations of cortical and trabecular architecture are associated with fractures in postmenopausal women, partially independent of decreased BMD measured by DXA: the OFELY study. J Bone Miner Res. 2007;22(3):425–33.CrossRefPubMedGoogle Scholar
  16. 16.
    Sornay-Rendu E, Cabrera-Bravo JL, Boutroy S, Munoz F, Delmas PD. Severity of vertebral fractures is associated with alterations of cortical architecture in postmenopausal women. J Bone Miner Res. 2009;24(4):737–43.CrossRefPubMedGoogle Scholar
  17. 17.
    Cejka D, Patsch JM, Weber M, Diarra D, Riegersperger M, Kikic Z, et al. Bone microarchitecture in hemodialysis patients assessed by HR-pQCT. Clin J Am Soc Nephrol. 2011;6(9):2264–71. Epub 2011/07/09.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Szulc P, Boutroy S, Vilayphiou N, Chaitou A, Delmas PD, Chapurlat R. Cross-sectional analysis of the association between fragility fractures and bone microarchitecture in older men: the STRAMBO study. J Bone Miner Res. 2011;26(6):1358–67. Epub 2011/05/26.CrossRefPubMedGoogle Scholar
  19. 19.
    Vilayphiou N, Boutroy S, Szulc P, van Rietbergen B, Munoz F, Delmas PD, et al. Finite element analysis performed on radius and tibia HR-pQCT images and fragility fractures at all sites in men. J Bone Miner Res. 2011;26(5):965–73. Epub 2011/05/05.CrossRefPubMedGoogle Scholar
  20. 20.
    Bjornerem A, Bui QM, Ghasem-Zadeh A, Hopper JL, Zebaze R, Seeman E. Fracture risk and height: an association partly accounted for by cortical porosity of relatively thinner cortices. J Bone Miner Res. 2013;28(9):2017–26. Epub 2013/03/23.CrossRefPubMedGoogle Scholar
  21. 21.•
    Bala Y, Bui QM, Wang XF, Iuliano S, Wang Q, Ghasem-Zadeh A, et al. Trabecular and cortical microstructure and fragility of the distal radius in women. J Bone Miner Res. 2015;30(4):621–9. Epub 2014/10/21. Provides odds ratios for fractures across girls, pre-menopausal and post-menopausal women, illustrating the incremental effect sizes with older age groups.Google Scholar
  22. 22.
    Chevalley T, Bonjour JP, van Rietbergen B, Ferrari S, Rizzoli R. Fracture history of healthy premenopausal women is associated with a reduction of cortical microstructural components at the distal radius. Bone. 2013;55(2):377–83. Epub 2013/05/11.CrossRefPubMedGoogle Scholar
  23. 23.
    Jamal S, Cheung AM, West S, Lok C. Bone mineral density by DXA and HR pQCT can discriminate fracture status in men and women with stages 3 to 5 chronic kidney disease. Osteoporos Int. 2012;23(12):2805–13. Epub 2012/02/03.CrossRefPubMedGoogle Scholar
  24. 24.•
    Wong AK, Beattie KA, Min KK, Merali Z, Webber CE, Gordon CL, et al. A Trimodality comparison of volumetric bone imaging technologies. Part III: SD, SEE, LSC Association With Fragility Fractures. J Clin Densitom. 2014. Epub 2014/08/19. Compares pQCT, HR-pQCT and pMRI associations with fractures within the same cohort, showing the tighter confidence intervals and signfiicance with HR-pQCT parameters compared to those obtained from other modalities Google Scholar
  25. 25.
    Wang J, Stein EM, Zhou B, Nishiyama KK, Yu YE, Shane E, et al. Deterioration of trabecular plate-rod and cortical microarchitecture and reduced bone stiffness at distal radius and tibia in postmenopausal women with vertebral fractures. Bone. 2016;88:39–46. Epub 2016/04/17.CrossRefPubMedGoogle Scholar
  26. 26.••
    Boutroy S, Khosla S, Sornay-Rendu E, Zanchetta MB, McMahon DJ, Zhang CA, et al. Microarchitecture and peripheral BMD are impaired in postmenopausal Caucasian women with fracture independently of total hip T-score—an international multicenter study. J Bone Miner Res. 2016. Epub 2016/01/29. Large multi-centre study with 1379 women examining associations with various fracture types and demonstrating significant odds ratios for most measures examined, independently of total hip aBMD Google Scholar
  27. 27.
    Pialat JB, Vilayphiou N, Boutroy S, Gouttenoire PJ, Sornay-Rendu E, Chapurlat R, 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. 2012;51(3):362–8. Epub 2012/06/26.CrossRefPubMedGoogle Scholar
  28. 28.•
    Biver E, Durosier C, Chevalley T, Herrmann FR, Ferrari S, Rizzoli R. Prior ankle fractures in postmenopausal women are associated with low areal bone mineral density and bone microstructure alterations. Osteoporos Int. 2015;26(8):2147–55. Epub 2015/04/09. Evidence that ankle fractures should be considered fragility fractures, as compared to forearm fractures, with HR-pQCT parameters illustrating significant odds for fractures comparable to forearm fractures.Google Scholar
  29. 29.
    Gorai I, Nonaka K, Kishimoto H, Sakata H, Fujii Y, Fujita T. Cut-off values determined for vertebral fracture by peripheral quantitative computed tomography in Japanese women. Osteoporos Int. 2001;12(9):741–8.CrossRefPubMedGoogle Scholar
  30. 30.
    MacIntyre NJ, Adachi JD, Webber CE. In vivo measurement of apparent trabecular bone structure of the radius in women with low bone density discriminates patients with recent wrist fracture from those without fracture. J Clin Densitom. 2003;6(1):35–43.CrossRefPubMedGoogle Scholar
  31. 31.
    Jamal SA, Gilbert J, Gordon C, Bauer DC. Cortical pQCT measures are associated with fractures in dialysis patients. J Bone Miner Res. 2006;21(4):543–8.CrossRefPubMedGoogle Scholar
  32. 32.
    Grampp S, Genant HK, Mathur A, Lang P, Jergas M, Takada M, et al. Comparisons of noninvasive bone mineral measurements in assessing age-related loss, fracture discrimination, and diagnostic classification. J Bone Miner Res. 1997;12(5):697–711. Epub 1997/05/01.CrossRefPubMedGoogle Scholar
  33. 33.
    Clowes JA, Eastell R, Peel NF. The discriminative ability of peripheral and axial bone measurements to identify proximal femoral, vertebral, distal forearm and proximal humeral fractures: a case control study. Osteoporos Int. 2005;16(12):1794–802. Epub 2005/06/11.CrossRefPubMedGoogle Scholar
  34. 34.
    Augat P, Fan B, Lane NE, Lang TF, LeHir P, Lu Y, et al. Assessment of bone mineral at appendicular sites in females with fractures of the proximal femur. Bone. 1998;22(4):395–402. Epub 1998/04/29.CrossRefPubMedGoogle Scholar
  35. 35.
    Moilanen P, Maatta M, Kilappa V, Xu L, Nicholson PH, Alen M, et al. Discrimination of fractures by low-frequency axial transmission ultrasound in postmenopausal females. Osteoporos Int. 2013;24(2):723–30. Epub 2012/05/29.CrossRefPubMedGoogle Scholar
  36. 36.
    Tsugeno H, Tsugeno H, Fujita T, Goto B, Sugishita T, Hosaki Y, et al. Vertebral fracture and cortical bone changes in corticosteroid-induced osteoporosis. Osteoporos Int. 2002;13(8):650–6. Epub 2002/08/16.CrossRefPubMedGoogle Scholar
  37. 37.
    Schneider P, Reiners C, Cointry GR, Capozza RF, Ferretti JL. Bone quality parameters of the distal radius as assessed by pQCT in normal and fractured women. Osteoporos Int. 2001;12(8):639–46. Epub 2001/10/03.CrossRefPubMedGoogle Scholar
  38. 38.
    Majumdar S, Link TM, Millard J, Lin JC, Augat P, Newitt D, et al. In vivo assessment of trabecular bone structure using fractal analysis of distal radius radiographs. Med Phys. 2000;27(11):2594–9. Epub 2000/12/29.CrossRefPubMedGoogle Scholar
  39. 39.
    Matsushita R, Yamamoto I, Takada M, Hamanaka Y, Yuh I, Morita R. Comparison of various biochemical measurements with bone mineral densitometry and quantitative ultrasound for the assessment of vertebral fracture. J Bone Miner Metab. 2000;18(3):158–64. Epub 2000/04/28.CrossRefPubMedGoogle Scholar
  40. 40.
    Formica CA, Nieves JW, Cosman F, Garrett P, Lindsay R. Comparative assessment of bone mineral measurements using dual X-ray absorptiometry and peripheral quantitative computed tomography. Osteoporos Int. 1998;8(5):460–7. Epub 1998/12/16.CrossRefPubMedGoogle Scholar
  41. 41.
    Grampp S, Jergas M, Lang P, Steiner E, Fuerst T, Gluer CC, et al. Quantitative CT assessment of the lumbar spine and radius in patients with osteoporosis. AJR Am J Roentgenol. 1996;167(1):133–40. Epub 1996/07/01.CrossRefPubMedGoogle Scholar
  42. 42.
    Tsurusaki K, Ito M, Hayashi K. Differential effects of menopause and metabolic disease on trabecular and cortical bone assessed by peripheral quantitative computed tomography (pQCT). Br J Radiol. 2000;73(865):14–22. Epub 2000/03/18.CrossRefPubMedGoogle Scholar
  43. 43.
    Christen D, Melton 3rd LJ, Zwahlen A, Amin S, Khosla S, Muller R. Improved fracture risk assessment based on nonlinear micro-finite element simulations from HRpQCT images at the distal radius. J Bone Miner Res. 2013;28(12):2601–8. Epub 2013/05/25.CrossRefPubMedGoogle Scholar
  44. 44.
    Vico L, Zouch M, Amirouche A, Frere D, Laroche N, Koller B, et al. High-resolution pQCT analysis at the distal radius and tibia discriminates patients with recent wrist and femoral neck fractures. J Bone Miner Res. 2008;23(11):1741–50.CrossRefPubMedGoogle Scholar
  45. 45.
    Rolland T, Boutroy S, Vilayphiou N, Blaizot S, Chapurlat R, Szulc P. Poor trabecular microarchitecture at the distal radius in older men with increased concentration of high-sensitivity C-reactive protein—the STRAMBO study. Calcif Tissue Int. 2012;90(6):496–506. Epub 2012/04/25.CrossRefPubMedGoogle Scholar
  46. 46.
    Patsch JM, Burghardt AJ, Yap SP, Baum T, Schwartz AV, Joseph GB, et al. Increased cortical porosity in type 2 diabetic postmenopausal women with fragility fractures. J Bone Miner Res. 2013;28(2):313–24. Epub 2012/09/20.CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Ostertag A, Collet C, Chappard C, Fernandez S, Vicaut E, Cohen-Solal M, et al. A case-control study of fractures in men with idiopathic osteoporosis: fractures are associated with older age and low cortical bone density. Bone. 2013;52(1):48–55. Epub 2012/09/27.CrossRefPubMedGoogle Scholar
  48. 48.
    Nishiyama KK, Macdonald HM, Hanley DA, Boyd SK. Women with previous fragility fractures can be classified based on bone microarchitecture and finite element analysis measured with HR-pQCT. Osteoporos Int. 2013;24(5):1733–40. Epub 2012/11/28.CrossRefPubMedGoogle Scholar
  49. 49.
    Stein EM, Kepley A, Walker M, Nickolas TL, Nishiyama K, Zhou B, et al. Skeletal structure in postmenopausal women with osteopenia and fractures is characterized by abnormal trabecular plates and cortical thinning. J Bone Miner Res. 2014;29(5):1101–9. Epub 2014/05/31.CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.•
    West SL, Lok CE, Langsetmo L, Cheung AM, Szabo E, Pearce D, et al. Bone mineral density predicts fractures in chronic kidney disease. J Bone Miner Res. 2015;30(5):913–9. Epub 2014/11/18. One of few cohort studies showing link between bone quality and incident fractures, albeit in a smaller sample.Google Scholar
  51. 51.
    Biver E, Durosier C, Chevalley T, Van Rietbergen B, Rizzoli R, Ferrari S. Distal radius cortical microstructure and calculated strength predict incident fractures independently of FRAX in postmenopausal women. Osteoporos Int. 2016;27 Suppl 1:OC30.Google Scholar
  52. 52.••
    Rajapakse CS, Phillips EA, Sun W, Wald MJ, Magland JF, Snyder PJ, et al. Vertebral deformities and fractures are associated with MRI and pQCT measures obtained at the distal tibia and radius of postmenopausal women. Osteoporos Int. 2014;25(3):973–82. Epub 2013/11/14. Provides evidence that peripheral measures of bone quality correlate with severity of vertebral fractures and not just peripheral fractures.Google Scholar
  53. 53.
    Wong AKO, Berger C, Ioannidis G, Beattie KA, Gordon CL, Pickard L, et al. The Canadian Multicentre Osteoporosis Bone Quality Study (CaMos BQS): baseline comparison of HR-pQCT and pQCT and fracture associations. J Bone Miner Res. 2015;30 Suppl 1:#P251.Google Scholar
  54. 54.
    Sheu Y, Zmuda JM, Boudreau RM, Petit MA, Ensrud KE, Bauer DC, et al. Bone strength measured by peripheral quantitative computed tomography and the risk of nonvertebral fractures: the osteoporotic fractures in men (MrOS) study. J Bone Miner Res. 2011;26(1):63–71. Epub 2010/07/02.CrossRefPubMedGoogle Scholar
  55. 55.••
    Dennison EM, Jameson KA, Edwards MH, Denison HJ, Aihie Sayer A, Cooper C. Peripheral quantitative computed tomography measures are associated with adult fracture risk: the Hertfordshire Cohort Study. Bone. 2014;64:13–7. Epub 2014/04/01. Evidence of a link between pQCT-derived bone quality measures and incident fractures, independent of aBMD, in a large cohort study.Google Scholar
  56. 56.
    Laib A, Newitt DC, Lu Y, Majumdar S. New model-independent measures of trabecular bone structure applied to in vivo high-resolution MR images. Osteoporos Int. 2002;13(2):130–6.CrossRefPubMedGoogle Scholar
  57. 57.
    Cortet B, Boutry N, Dubois P, Bourel P, Cotten A, Marchandise X. In vivo comparison between computed tomography and magnetic resonance image analysis of the distal radius in the assessment of osteoporosis. J Clin Densitom. 2000;3(1):15–26. Epub 2000/08/05.CrossRefPubMedGoogle Scholar
  58. 58.
    Wurnig MC, Calcagni M, Kenkel D, Vich M, Weiger M, Andreisek G, et al. Characterization of trabecular bone density with ultra-short echo-time MRI at 1.5, 3.0 and 7.0 T—comparison with micro-computed tomography. NMR Biomed. 2014;27(10):1159–66. Epub 2014/08/05.CrossRefPubMedGoogle Scholar
  59. 59.
    Damilakis J, Maris T, Papadokostakis G, Sideri L, Gourtsoyiannis N. Discriminatory ability of magnetic resonance T2* measurements in a sample of postmenopausal women with low-energy fractures: a comparison with phalangeal speed of sound and dual x-ray absorptiometry. Investig Radiol. 2004;39(11):706–12. Epub 2004/10/16.CrossRefGoogle Scholar
  60. 60.
    Wehrli FW, Gomberg BR, Saha PK, Song HK, Hwang SN, Snyder PJ. Digital topological analysis of in vivo magnetic resonance microimages of trabecular bone reveals structural implications of osteoporosis. J Bone Miner Res. 2001;16(8):1520–31. Epub 2001/08/14.CrossRefPubMedGoogle Scholar
  61. 61.
    Folkesson J, Carballido-Gamio J, Eckstein F, Link TM, Majumdar S. Local bone enhancement fuzzy clustering for segmentation of MR trabecular bone images. Med Phys. 2010;37(1):295–302. Epub 2010/02/24.CrossRefPubMedGoogle Scholar
  62. 62.
    Ioannidis G, Papaioannou A, Hopman WM, Akhtar-Danesh N, Anastassiades T, Pickard L, et al. Relation between fractures and mortality: results from the Canadian Multicentre Osteoporosis Study. CMAJ. 2009;181(5):1–7.CrossRefGoogle Scholar
  63. 63.
    Liu XS, Cohen A, Shane E, Yin PT, Stein EM, Rogers H, et al. Bone density, geometry, microstructure, and stiffness: relationships between peripheral and central skeletal sites assessed by DXA, HR-pQCT, and cQCT in premenopausal women. J Bone Miner Res. 2010;25(10):2229–38. Epub 2010/05/26.CrossRefPubMedPubMedCentralGoogle Scholar
  64. 64.
    Horikoshi T, Endo N, Uchiyama T, Tanizawa T, Takahashi HE. Peripheral quantitative computed tomography of the femoral neck in 60 Japanese women. Calcif Tissue Int. 1999;65(6):447–53.CrossRefPubMedGoogle Scholar
  65. 65.
    Davison MJ, Maly MR, Adachi JD, Noseworthy MD, Beattie KA. Relationships between fatty infiltration in the thigh and calf in women with knee osteoarthritis. Aging Clin Exp Res. 2016. Epub 2016/03/12Google Scholar
  66. 66.
    Sjoblom S, Suuronen J, Rikkonen T, Honkanen R, Kroger H, Sirola J. Relationship between postmenopausal osteoporosis and the components of clinical sarcopenia. Maturitas. 2013;75(2):175–80. Epub 2013/05/01.CrossRefPubMedGoogle Scholar
  67. 67.
    Leslie WD, Orwoll ES, Nielson CM, Morin SN, Majumdar SR, Johansson H, et al. Estimated lean mass and fat mass differentially affect femoral bone density and strength index but are not FRAX independent risk factors for fracture. J Bone Miner Res. 2014;29(11):2511–9. Epub 2014/05/16.CrossRefPubMedGoogle Scholar
  68. 68.•
    Crockett K, Arnold CM, Farthing JP, Chilibeck PD, Johnston JD, Bath B, et al. Bone strength and muscle properties in postmenopausal women with and without a recent distal radius fracture. Osteoporos Int. 2015;26(10):2461–9. Epub 2015/05/24. Demonstrated both poorer bone and muscle quality in those who had fractured within the last 6-24 months compared to controls.Google Scholar
  69. 69.
    Blew RM, Lee VR, Farr JN, Schiferl DJ, Going SB. Standardizing evaluation of pQCT image quality in the presence of subject movement: qualitative versus quantitative assessment. Calcif Tissue Int. 2014;94(2):202–11. Epub 2013/10/01.CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    Chan A, Adachi JD, Papaioannou A, Pickard L, Wong AK. Investigating the effects of motion streaks on the association between pQCT-derived leg muscle density and fractures in older adults. J Bone Miner Res. 2015;30(Suppl 1):Available at: http://www.asbmr.org/education/AbstractDetail?aid=c8844053-995d-4768-9263-457296822c3d.
  71. 71.••
    Wong AK, Cawthon PM, Peters KW, Cummings SR, Gordon CL, Sheu Y, et al. Bone-muscle indices as risk factors for fractures in men: the Osteoporotic Fractures in Men (MrOS) Study. J Musculoskelet Neuronal Interact. 2014;14(3):246–54. Epub 2014/09/10. Large population-based cohort study of men showing significant associations between bone and muscle properties and incident fractures, independent of spine but not hip aBMD.Google Scholar
  72. 72.
    Cesari M, Leeuwenburgh C, Lauretani F, Onder G, Bandinelli S, Maraldi C, et al. Frailty syndrome and skeletal muscle: results from the Invecchiare in Chianti study. Am J Clin Nutr. 2006;83(5):1142–8. Epub 2006/05/11.PubMedPubMedCentralGoogle Scholar
  73. 73.
    Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol. 2001;56(3):M146–56. Epub 2001/03/17.CrossRefGoogle Scholar
  74. 74.
    Kennedy CC, Ioannidis G, Rockwood K, Thabane L, Adachi JD, Kirkland S, et al. A Frailty Index predicts 10-year fracture risk in adults age 25 years and older: results from the Canadian Multicentre Osteoporosis Study (CaMos). Osteoporos Int. 2014. Epub 2014/08/12Google Scholar
  75. 75.
    Wong AKO, Kennedy C, Ioannidis G, Beattie KA, Gordon CL, Pickard L, et al. Direct and indirect effects of frailty on fractures: potential roles of muscle and bone. J Bone Miner Res. 2014;29 Suppl 1:334.Google Scholar
  76. 76.
    Li G, Ioannidis G, Pickard L, Kennedy C, Papaioannou A, Thabane L, et al. Frailty index of deficit accumulation and falls: data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) Hamilton cohort. BMC Musculoskelet Disord. 2014;15:185. Epub 2014/06/03.CrossRefPubMedPubMedCentralGoogle Scholar
  77. 77.•
    Addison O, Drummond MJ, LaStayo PC, Dibble LE, Wende AR, McClain DA, et al. Intramuscular fat and inflammation differ in older adults: the impact of frailty and inactivity. J Nutr Health Aging. 2014;18(5):532–8. Epub 2014/06/03. One of few studies showing differences in intramuscular fat between those with frailty and controls without.Google Scholar
  78. 78.
    Delgado C, Doyle JW, Johansen KL. Association of frailty with body composition among patients on hemodialysis. J Ren Nutr. 2013;23(5):356–62. Epub 2013/05/08.CrossRefPubMedPubMedCentralGoogle Scholar
  79. 79.•
    Melville DM, Mohler J, Fain M, Muchna AE, Krupinski E, Sharma P, et al. Multi-parametric MR imaging of quadriceps musculature in the setting of clinical frailty syndrome. Skelet Radiol. 2016;45(5):583–9. Epub 2016/01/09. Although a small study, illustrated differences in muscle fibre tractography and intramyocellular lipids between frail and non-frail women based on Fried criteria.Google Scholar
  80. 80.
    Zhang T, Suen C. A fast parallel algorithm for thinning digital patterns. Commun Assoc Comput Mach. 1984;27:236–9.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Joint Department of Medical Imaging, Toronto General Research InstituteUniversity Health Network, Toronto General HospitalTorontoCanada
  2. 2.McMaster University, Department of MedicineFaculty of Health SciencesHamiltonCanada

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