Skip to main content
Top

02-05-2018 | Osteoporosis | Review | Article

Novel Imaging Modalities in Osteoporosis Diagnosis and Risk Stratification

Journal: Current Treatment Options in Rheumatology

Authors: Saarah Haque, BHSc, MSc, Arthur Lau, MD, Karen Beattie, MD, Jonathan D. Adachi, MD

Publisher: Springer International Publishing

Abstract

Purpose of review

Two hundred million individuals worldwide are diagnosed with osteoporosis, and every year, approximately 8.9 million experience a fracture. There is an opportunity with new diagnostic technology to enhance risk stratification of osteoporosis to improve patient outcomes. The current standard for osteoporosis diagnosis includes an areal bone mineral density (aBMD) T-score derived from a dual-energy X-ray absorptiometry (DXA) scan. However, aBMD does not account for bone quality, resulting in some individuals at risk for fracture not being identified. This review article will explore the potential of novel imaging technologies in osteoporosis diagnosis and risk stratification.

Recent findings

Several novel imaging technologies have had success identifying those at risk for fracture and measuring treatment effectiveness. These include trabecular bone score (TBS), high-resolution peripheral quantitative computed tomography (HR-pQCT), peripheral quantitative computed tomography (pQCT), magnetic resonance imaging (MRI), and quantitative ultrasound (QUS). Recently, TBS has been incorporated into fracture risk prediction.

Summary

While these imaging modalities show promise, further investigation is necessary to determine accuracy and reliability in osteoporosis diagnostics and fracture risk stratification before clinical integration is possible.
Literature
1.
Johnell O, Kanis JA. An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int. 2006;17:1726–33.CrossRefPubMed
2.
Anonymous. Consensus development conference: diagnosis, prophylaxis and treatment of osteoporosis. Am J Med. 1993;94:646–50.CrossRef
3.
Wallace I, Rubin C, Lieberman D. Osteoporosis. Evol Med Public Health. 2015;2015(1):343.CrossRefPubMedPubMedCentral
4.
Shuid A, Khaithir T, Mokhtar S, Mohamed I. A systematic review of the outcomes of osteoporotic fracture patients after hospital discharge: morbidity, subsequent fractures, and mortality. Ther Clin Risk Manag. 2014;10:937–48.CrossRef
5.
Celi M, Rao C, Scialdoni A, Tempesta V, Gasbarra E, Pistillo P, et al. Bone mineral density evaluation in osteoporosis: why yes and why not? Aging Clin Exp Res. 2013;25(S1):47–9.CrossRef
6.
Kanis J, Johnell O, Oden A, Dawson A, De Laet C, Jonsson B. Ten year probabilities of osteoporotic fractures according to BMD and diagnostic thresholds. Osteoporos Int. 2001;12:989–95.CrossRefPubMed
7.
Siris ES, Chen YT, Abbott TA, Barrett-Connor E, Miller PD, Wehren LE, et al. Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med. 2004;164:1108–12.CrossRefPubMed
8.
Cosman F, de Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S, et al. Clinicians guide to prevention and treatment of osteoporosis. Osteoporos Int. 2014;25:2359–81.CrossRefPubMedPubMedCentral
9.
Didier H, Barthe N, Boutroy S, Pothuaud L, Winzenrieth R, Krieg M. Correlations between trabecular bone score, measured using anteroposterior dual-energy X-ray absorptiometry acquisition, and 3-dimensional parameters of bone microarchitecture: an experimental study on human cadaver vertebrae. J Clin Densitom. 2011;14(3):302–12.CrossRef
10.
Winzenrieth R, Piveteau T, Hans D. Assessment of correlations between 3D μCT microarchitecture parameters and TBS: effects of resolution and correlation with TBS DXA measurements. J Clin Densitom. 2011;14(2):169.
11.
Harvey N, Glüer C, Binkley N, McCloskey E, Brandi M, Cooper C, et al. Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice. Bone. 2015;78:216–24.CrossRefPubMedPubMedCentral
12.
Hans D, Goertzen AL, Krieg M-A, Leslie WD. Bone micro-architecture assessed by TBS predicts osteoporotic fractures independent of bone density: the Manitoba study. J Bone Miner Res. 2011;26:2762–9.CrossRefPubMed
13.
Kanis JA, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H, et al. A meta-analysis of trabecular bone score in fracture risk prediction and its interaction with FRAX. Osteoporos Int. 2015;26:940–8.
14.
Tjong W, Kazakia GJ, Burghardt AJ, Majumdar S. The effect of voxel size on high-resolution peripheral computed tomography measurements of trabecular and cortical bone microstructure. Med Phys. 2012;39:1893–903.CrossRefPubMedPubMedCentral
15.
MacNeil JA, Boyd SK. Improved reproducibility of highresolution peripheral quantitative computed tomography for measurement of bone quality. Med Eng Phys. 2008;30:792–9.CrossRefPubMed
16.
Boutroy S, Bouxsein ML, Munoz F, Delmas PD. In vivo assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography. J Clin Endocrinol Metab. 2005;90(12):6508–15.CrossRefPubMed
17.
Burghardt AJ, Buie HR, Laib A, Majumdar S, Boyd SK. Reproducibility of direct quantitative measures of cortical bone microarchitecture of the distal radius and tibia by HR-pQCT. Bone. 2010;47:519–28.CrossRefPubMedPubMedCentral
18.
Nishiyama K, Shane E. Clinical imaging of bone microarchitecture with HR-pQCT. Curr Osteoporos Rep. 2013;11(2):147–55.CrossRefPubMedPubMedCentral
19.
Liu X, Cohen A, Shane E, Yin P, Stein E, 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.CrossRefPubMedPubMedCentral
20.
•• Wong A. A comparison of peripheral imaging technologies for bone and muscle quantification: a mixed methods clinical review. Curr Osteoporos Rep. 2016;14(6):359–73. This article provides a comprehensive analysis and consolidation of the literature on novel imaging technology including peripheral quantitative tomography and magnetic resonance imaging.CrossRefPubMed
21.
Walker MD, McMahon DJ, Udesky J, Liu G, Bilezikian JP. Application of high resolution skeletal imaging to measurements of volumetric bone density and skeletal microarchitecture in Chinese American and Caucasian women: explanation of a paradox. J Bone Miner Res. 2009;24(12):1953–9.CrossRefPubMedPubMedCentral
22.
• Cheung A, Adachi J, Hanley D, Kendler D, Davison K, Josse R, et al. High-resolution peripheral quantitative computed tomography for the assessment of bone strength and structure: a review by the Canadian Bone Strength Working Group. Curr Osteoporos Rep. 2013;11(2):136–46. This article provides a thorough overview of high-resolution peripheral quantitative tomography for predictive fracture risk assessment and risk stratification in patients with osteoporosis.CrossRefPubMedPubMedCentral
23.
Hansen S, Hauge EM, Jensen JE, Brixen K. Differing effects of PTH 1-34, PTH 1-84, and zoledronic acid on bone microarchitecture and estimated strength in postmenopausal women with osteoporosis. An 18 month open-labeled observational study using HR-pQCT. J Bone Miner Res. 2012;10:736–45.
24.
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.
25.
Jones E, Bishop P, Woods A, Green J. Cross-sectional area and muscular strength. Sports Med. 2008;38(12):987–94.CrossRefPubMed
26.
Wong AKO, Beattie KA, Min KKH, 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(40):401–10.PubMedPubMedCentral
27.
Wong A, Hummel K, Moore C, Beattie K, Shaker S, Craven B, et al. Improving reliability of pQCT-derived muscle area and density measures using a watershed algorithm for muscle and fat segmentation. J Clin Densitometry. 2015;18(1):93–101.CrossRef
28.
Zebaze RM, Ghasem-Zadeh A, Bohte A, Iuliano-Burns S, Mirams M, Price RI, et al. Intracortical remodelling and porosity in the distal radius and post-mortem femurs of women: a cross-sectional study. Lancet. 2010;375:1729–36.CrossRefPubMed
29.
Link T. Osteoporosis imaging: state of the art and advanced imaging. Radiology. 2012;263(1):3–17.CrossRefPubMedPubMedCentral
30.
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.CrossRefPubMed
31.
Burt L, Liang Z, Sajobi T, Hanley D, Boyd S. Sex- and site-specific normative data curves for HR-pQCT. J Bone Miner Res. 2016;31(11):2041–7.CrossRefPubMed
32.
Hung V, Zhu T, Cheung W, Fong T, Yu F, Hung L, et al. Age-related differences in volumetric bone mineral density, microarchitecture, and bone strength of distal radius and tibia in Chinese women: a high-resolution pQCT reference database study. Osteoporos Int. 2015;26(6):1691–703.CrossRefPubMed
33.
Jiang H, Yates C, Gorelik A, Kale A, Song Q, Wark J. Peripheral quantitative computed tomography measures contribute to the understanding of bone fragility in low-trauma fracture patients. Bone Abstracts. 2016. https://​doi.​org/​10.​1530/​boneabs.​5.​LB3.
34.
Krug R, Banerjee S, Han ET, Newitt DC, Link TM, Majumdar S. Feasibility of in vivo structural analysis of high-resolution magnetic resonance images of the proximal femur. Osteoporos Int. 2005;16:1307–14.CrossRefPubMed
35.
Hotca A, Rajapakse CS, Cheng C, Honig S, Egol K, Regatte RR, et al. In vivo measurement reproducibility of femoral neck microarchitectural parameters derived from 3T MR images. J Magn Reson Imaging. 2015;42:1339–45.CrossRefPubMedPubMedCentral
36.
Zhang N, Magland JF, Rajapakse CS, Bhagat YA, Wehrli FW. Potential of in vivo MRI-based nonlinear finite-element analysis for the assessment of trabecular bone post-yield properties. Med Phys. 2013;40:1–10.CrossRef
37.
SornayRendu 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;22:425–33.CrossRef
38.
Chang G, Rajapakse CS, Regatte RR, Babb J, Saxena A, Belmont HM, et al. 3 tesla MRI detects deterioration in proximal femur microarchitecture and strength in long-term glucocorticoid users compared with controls. J Magn Reson Img. 2015;42:1489–96.CrossRef
39.
Folkesson J, Goldenstein J, Carballido-Gamio J, Kazakia G, Burghardt AJ, Rodriguez A, et al. Longitudinal evaluation of the effects of alendronate on MRI bone microarchitecture in postmenopausal osteopenic women. Bone. 2011;48:611–21.CrossRefPubMed
40.
Wang X, Shen X, Li X, Agrawal CM. Age-related changes in the collagen network and toughness of bone. Bone. 2002;31:1–7.CrossRefPubMed
41.
VanRietbergen B, Majumdar S, Newitt D, MacDonald B. High-resolution MRI and micro-FE for the evaluation of changes in bone mechanical properties during longitudinal clinical trials: application to calcaneal bone in postmenopausal women after one year of idoxifene treatment. Clin Biomech. 2002;17:81–8.CrossRef
42.
Seeman E, Delmas PD, Hanley DA, Sellmeyer D, Cheung AM, Shane E, et al. Microarchitectural deterioration of cortical and trabecular bone: Differing effects of denosumab and alendronate. J Bone Miner Res. 2010 Aug;25(8):1886–94.CrossRefPubMedPubMedCentral
43.
Lam S, Wald M, Rajapakse C, Liu Y, Saha P, Wehrli F. Performance of the MRI-based virtual bone biopsy in the distal radius: serial reproducibility and reliability of structural and mechanical parameters in women representative of osteoporosis study populations. Bone. 2011;49(4):895–903.CrossRefPubMedPubMedCentral
44.
Gregg E, Kriska A, Salamone L, Roberts MM, Anderson SJ, Ferrell RE, et al. The epidemiology of quantitative ultrasound: a review of the relationships with bone mass, osteoporosis and fracture risk. Osteoporos Int. 1997;7:89–99.CrossRefPubMed
45.
Guglielmi G, Terlizzi FD. Quantitative ultrasound in the assessment of osteoporosis. Eur J Radiol. 2009;71:425–31.CrossRefPubMed
46.
Bouxsein ML, Coan BS, Lee SC. Prediction of the strength of the elderly proximal femur by bone mineral density and quantitative ultrasound measurements of the heel and tibia. Bone. 1999;25:49–54.CrossRefPubMed
47.
Moayyeri A, Adams JE, Adler RA, Krieg MA, Hans D, Compston, et al. Quantitative ultrasound of the heel and fracture risk assessment: an updated meta-analysis. Osteoporos Int. 2012;23:143–53.CrossRefPubMed
48.
Chan MY, Nguyen ND, Center JR, Eisman JA, Nguyen TV. Absolute fracture-risk prediction by a combination of calcaneal quantitative ultrasound and bone mineral density. Calcif Tissue Int. 2012;90:128–36.CrossRefPubMed
49.
Villa P, Lassandro A, Moruzzi M, Amar ID, Vacca L, Nardo D, et al. A non-invasive prevention program model for the assessment of osteoporosis in the early postmenopausal period: a pilot study on FRAX and QUS tools advantages. J Endocrinol Investig. 2016;39:191–8.CrossRef