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Advancements in Osteoporosis Imaging, Screening, and Study of Disease Etiology

  • Imaging (H Isaksson and S Boyd, Section Editors)
  • Published:
Current Osteoporosis Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

The purpose of this review is to inform researchers and clinicians with the most recent imaging techniques that are employed (1) to opportunistically screen for osteoporosis and (2) to provide a better understanding into the disease etiology of osteoporosis.

Recent Findings

Phantomless calibration techniques for computed tomography (CT) may pave the way for better opportunistic osteoporosis screening and the retroactive analysis of imaging data. Additionally, hardware advances are enabling new applications of dual-energy CT and cone-beam CT to the study of bone. Advances in MRI sequences are also improving imaging evaluation of bone properties. Finally, the application of image registration techniques is enabling new uses of imaging to investigate soft tissue-bone interactions as well as bone turnover.

Summary

While DXA remains the most prominent imaging tool for osteoporosis diagnosis, new imaging techniques are becoming more widely available and providing additional information to inform clinical decision-making.

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References

  1. Glüer C-C. 30 years of DXA technology innovations. Bone. 2017;104:7–12.

    Article  PubMed  CAS  Google Scholar 

  2. Shepherd J, Hans D. The passing of the baton—in memory of Professor Harry Genant MD. J Clin Densitom. 2021;24:169–74.

    Article  Google Scholar 

  3. Genant HK, Boyd D. Quantitative bone mineral analysis using dual energy computed tomography. Investig Radiol. 1977;12:545–51.

    Article  CAS  Google Scholar 

  4. Lenchik L, Weaver AA, Ward RJ, Boone JM, Boutin RD. Opportunistic screening for osteoporosis using computed tomography: state of the art and argument for paradigm shift. Curr Rheumatol Rep. 2018;20:74.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Johannesdottir F, Allaire B, Kopperdahl DL, Keaveny TM, Sigurdsson S, Bredella MA, et al. Bone density and strength from thoracic and lumbar CT scans both predict incident vertebral fractures independently of fracture location. Osteoporos Int. 2021;32:261–9.

  6. Xu X-m, Li N, Li K, Li X-Y, Zhang P, Xuan Y-j, et al. Discordance in diagnosis of osteoporosis by quantitative computed tomography and dual-energy X-ray absorptiometry in Chinese elderly men. J Orthop Translat. 2019;18:59–64.

  7. Ko JH, Lim S, Lee YH, Yang IH, Kam JH, Park KK. Does simultaneous computed tomography and quantitative computed tomography show better prescription rate than dual-energy X-ray absorptiometry for osteoporotic hip fracture? Hip Pelvis. 2018;30:233–40.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Leonhardt Y, May P, Gordijenko O, Koeppen-Ursic VA, Brandhorst H, Zimmer C, et al. Opportunistic QCT bone mineral density measurements predicting osteoporotic fractures: a use case in a prospective clinical cohort. Front Endocrinol. 2020;11.

  9. Cohen A, Foldes AJ, Hiller N, Simanovsky N, Szalat A. Opportunistic screening for osteoporosis and osteopenia by routine computed tomography scan: a heterogeneous, multiethnic, middle-eastern population validation study. Eur J Radiol. 2021;136:109568.

    Article  PubMed  Google Scholar 

  10. Park SH, Jeong YM, Lee HY, Kim EY, Kim JH, Park HK, et al. Opportunistic use of chest CT for screening osteoporosis and predicting the risk of incidental fracture in breast cancer patients: a retrospective longitudinal study. PLoS ONE. 2020;15:e0240084.

  11. Alacreu E, Moratal D, Arana E. Opportunistic screening for osteoporosis by routine CT in Southern Europe. Osteoporos Int. 2017;28:983–90.

    Article  PubMed  Google Scholar 

  12. Jain RK, Lee E, Mathai C, Dako F, Gogineni P, Weiner MG, et al. Using opportunistic screening with abdominal CT to identify osteoporosis and osteopenia in patients with diabetes. Osteoporos Int. 2020;31:2189–96.

  13. Berger-Groch J, Thiesen DM, Ntalos D, Hennes F, Hartel MJ. Assessment of bone quality at the lumbar and sacral spine using CT scans: a retrospective feasibility study in 50 comparing CT and DXA data. Eur Spine J. 2020;29:1098–104.

    Article  CAS  PubMed  Google Scholar 

  14. Amador Martínez A, Lara Padilla E, Pérez Rodríguez JA, Alfaro A, Solis Cano DG, Bandala C, et al. Sensitivity and specificity of computed tomography in the evaluation of bone mineral density in Mexican patients with breast cancer. Cureus. 2019;11:e5505.

  15. Li Y-L, Wong K-H, Law MW-M, Fang BX-H, Lau VW-H, Vardhanabuti VV, et al. Opportunistic screening for osteoporosis in abdominal computed tomography for Chinese population. Arch Osteoporos. 2018;13:76.

  16. 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;158:588–95.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Zou D, Ye K, Tian Y, Li W, Zhou F, Zhang Z, et al. Characteristics of vertebral CT Hounsfield units in elderly patients with acute vertebral fragility fractures. Eur Spine J. 2020;29:1092–7.

  18. Perrier-Cornet J, Omorou AY, Fauny M, Loeuille D, Chary-Valckenaere I. Opportunistic screening for osteoporosis using thoraco-abdomino-pelvic CT-scan assessing the vertebral density in rheumatoid arthritis patients. Osteoporos Int. 2019;30:1215–22.

    Article  CAS  PubMed  Google Scholar 

  19. Kim YW, Kim JH, Yoon SH, Lee JH, Lee CH, Shin CS, et al. Vertebral bone attenuation on low-dose chest CT: quantitative volumetric analysis for bone fragility assessment. Osteoporos Int. 2017;28:329–38.

  20. Boutin RD, Hernandez AM, Lenchik L, Seibert JA, Gress DA, Boone JM. CT phantom evaluation of 67,392 American College of Radiology accreditation examinations: implications for opportunistic screening of osteoporosis using CT. AJR Am J Roentgenol. 2021;216:447–52.

    Article  PubMed  Google Scholar 

  21. Levi C, Gray JE, McCullough EC, Hattery RR. The unreliability of CT numbers as absolute values. Am J Roentgenol. 1982;139:443–7.

    Article  CAS  Google Scholar 

  22. Zerhouni EA, Spivey JF, Morgan RH, Leo FP, Stitik FP, Siegelman SS. Factors influencing quantitative CT measurements of solitary pulmonary nodules. J Comput Assist Tomogr. 1982;6:1075–87.

    Article  CAS  PubMed  Google Scholar 

  23. Maki DD, Birnbaum BA, Chakraborty DP, Jacobs JE, Carvalho BM, Herman GT. Renal cyst pseudoenhancement: beam-hardening effects on CT numbers. Radiology. 1999;213:468–72.

    Article  CAS  PubMed  Google Scholar 

  24. Groell R, Rienmueller R, Schaffler GJ, Portugaller HR, Graif E, Willfurth P. CT number variations due to different image acquisition and reconstruction parameters: a thorax phantom study. Comput Med Imaging Graph. 2000;24:53–8.

    Article  CAS  PubMed  Google Scholar 

  25. Cheng X, Zhao K, Zha X, Du X, Li Y, Chen S, et al. Opportunistic screening using low-dose CT and the prevalence of osteoporosis in China: a nationwide, multicenter study. Journal of Bone and Mineral Research. 2021;36:427–35.

  26. 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;18:5–12.

    Article  PubMed  Google Scholar 

  27. Wang L, Su Y, Wang Q, Duanmu Y, Yang M, Yi C, et al. Validation of asynchronous quantitative bone densitometry of the spine: accuracy, short-term reproducibility, and a comparison with conventional quantitative computed tomography. Sci Rep. 2017;7:6284.

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

  29. Löffler MT, Jacob A, Valentinitsch A, Rienmüller A, Zimmer C, Ryang Y-M, et al. Improved prediction of incident vertebral fractures using opportunistic QCT compared to DXA. Eur Radiol. 2019;29:4980–9.

  30. Engelke K, Lang T, Khosla S, Qin L, Zysset P, Leslie WD, et al. Clinical use of quantitative computed tomography-based advanced techniques in the management of osteoporosis in adults: the 2015 ISCD official positions-part III. J Clin Densitom. 2015;18:393–407.

  31. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  32. 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. 2015;278:172–80.

  33. Adams AL, Fischer H, Kopperdahl DL, Lee DC, Black DM, Bouxsein ML, et al. Osteoporosis and hip fracture risk from routine computed tomography scans: the fracture, osteoporosis, and CT utilization study (FOCUS). J Bone Miner Res. 2018;33:1291–301.

  34. Michalski AS, Besler BA, Michalak GJ, Boyd SK. CT-based internal density calibration for opportunistic skeletal assessment using abdominal CT scans. Med Eng Phys. 2020;78:55–63.

    Article  PubMed  Google Scholar 

  35. Winsor C, Li X, Qasim M, Henak CR, Pickhardt PJ, Ploeg H, et al. Evaluation of patient tissue selection methods for deriving equivalent density calibration for femoral bone quantitative CT analyses. Bone. 2021;143:115759.

  36. Ziemlewicz TJ, Maciejewski A, Binkley N, Brett AD, Brown JK, Pickhardt PJ. Direct comparison of unenhanced and contrast-enhanced CT for opportunistic proximal femur bone mineral density measurement: implications for osteoporosis screening. Am J Roentgenol. 2016;206:694–698.

  37. Michalski AS, Besler BA, Burt LA, Boyd SK. Opportunistic CT screening predicts individuals at risk of major osteoporotic fracture. Osteoporos Int. 2021.

  38. Garwood M, Idiyatullin D, Corum C, Chamberlain R, Moeller S, Kobayashi N, et al. Capturing signals from fastrelaxing spins with frequency-swept MRI: SWIFT. Encyclopedia of Magnetic Resonance. 2012;1.

  39. Keaveny TM, Clarke BL, Cosman F, Orwoll ES, Siris ES, Khosla S, et al. Biomechanical computed tomography analysis (BCT) for clinical assessment of osteoporosis. Osteoporos Int. 2020;31:1025–48.

  40. Garner HW, Paturzo MM, Gaudier G, Pickhardt PJ, Wessell DE. Variation in attenuation in L1 trabecular bone at different tube voltages: caution is warranted when screening for osteoporosis with the use of opportunistic CT. Am J Roentgenol. 2016;208:165–70.

    Article  Google Scholar 

  41. Bao P, Xia W, Yang K, Chen W, Chen M, Xi Y, et al. Convolutional sparse coding for compressed sensing CT reconstruction. IEEE Trans Med Imaging. 2019;38:2607–19.

  42. Hsieh CJ, Huang TK, Hsieh TH, Chen GH, Shih KL, Chen ZY, et al. Compressed sensing based CT reconstruction algorithm combined with modified Canny edge detection. Phys Med Biol. 2018;63:155011.

  43. Bannas P, Li Y, Motosugi U, Li K, Lubner M, Chen G-H, et al. Prior image constrained compressed sensing metal artifact reduction (PICCS-MAR): 2D and 3D image quality improvement with hip prostheses at CT colonography. Eur Radiol. 2016;26:2039–46.

  44. Murray TÉ, Williams D, Lee MJ. Osteoporosis, obesity, and sarcopenia on abdominal CT: a review of epidemiology, diagnostic criteria, and management strategies for the reporting radiologist. Abdom Radiol. 2017;42:2376–86.

    Article  Google Scholar 

  45. Mallinson PI, Coupal TM, McLaughlin PD, Nicolaou S, Munk PL, Ouellette HA. Dual-energy CT for the musculoskeletal system. Radiology. 2016;281:690–707.

    Article  PubMed  Google Scholar 

  46. Roski F, Hammel J, Mei K, Baum T, Kirschke JS, Laugerette A, et al. Bone mineral density measurements derived from dual-layer spectral CT enable opportunistic screening for osteoporosis. Eur Radiol. 2019;29:6355–63.

  47. Zhou S, Zhu L, You T, Li P, Shen H, He Y, et al. In vivo quantification of bone mineral density of lumbar vertebrae using fast kVp switching dual-energy CT: correlation with quantitative computed tomography. Quant Imaging Med Surg. 2021;11:341–50.

  48. Booz C, Hofmann PC, Sedlmair M, Flohr TG, Schmidt B, D’Angelo T, et al. Evaluation of bone mineral density of the lumbar spine using a novel phantomless dual-energy CT post-processing algorithm in comparison with dual-energy X-ray absorptiometry. Eur Radiol Exp. 2017;1:11.

  49. Kim YJ, Cha JG, Kim H, Yi JS, Kim H-J. Dual-energy and iterative metal artifact reduction for reducing artifacts due to metallic hardware: a loosening hip phantom study. Am J Roentgenol. 2019;212:1106–11.

    Article  Google Scholar 

  50. Yoo HJ, Hong SH, Chung BM, Moon SJ, Choi J-Y, Chae HD, et al. Metal artifact reduction in virtual monoenergetic spectral dual-energy CT of patients with metallic orthopedic implants in the distal radius. Am J Roentgenol. 2018;211:1083–91.

  51. Roski F, Hammel J, Mei K, Haller B, Baum T, Kirschke JS, et al. Opportunistic osteoporosis screening: contrast-enhanced dual-layer spectral CT provides accurate measurements of vertebral bone mineral density. Eur Radiol. 2021;31:3147–55.

  52. De Cock J, Mermuys K, Goubau J, Van Petegem S, Houthoofd B, Casselman JW. Cone-beam computed tomography: a new low dose, high resolution imaging technique of the wrist, presentation of three cases with technique. Skelet Radiol. 2012;41:93–6.

    Article  Google Scholar 

  53. Shokri A, Ghanbari M, Maleki FH, Ramezani L, Amini P, Tapak L. Relationship of gray values in cone beam computed tomography and bone mineral density obtained by dual energy X-ray absorptiometry. Oral Surg Oral Med Oral Pathol Oral Radiol. 2019;128:319–31.

    Article  PubMed  Google Scholar 

  54. Guerra ENS, Almeida FT, Bezerra FV, Figueiredo PTDS, Silva MAG, Canto GDL, et al. Capability of CBCT to identify patients with low bone mineral density: a systematic review. Dentomaxillofac Radiol. 2017;46:20160475.

  55. Mys K, Varga P, Stockmans F, Gueorguiev B, Neumann V, Vanovermeire O, et al. High-resolution cone-beam computed tomography is a fast and promising technique to quantify bone microstructure and mechanics of the distal radius. Calcif Tissue Int. 2021;108:314–23.

  56. Mys K, Varga P, Gueorguiev B, Hemmatian H, Stockmans F, Lenthe GH v. Correlation between cone-beam computed tomography and high-resolution peripheral computed tomography for assessment of wrist bone microstructure. J Bone Miner Res. 2019;34:867–74.

    Article  PubMed  Google Scholar 

  57. Manske SL, Zhu Y, Sandino C, Boyd SK. Human trabecular bone microarchitecture can be assessed independently of density with second generation HR-pQCT. Bone. 2015;79:213–21.

    Article  CAS  PubMed  Google Scholar 

  58. Tran DM-L, Vilayphiou N, Koller B. Clinical in vivo assessment of bone microarchitecture with CT scanners: an enduring challenge. J Bone Miner Res. 2020;35:415–6.

    Article  PubMed  Google Scholar 

  59. de Charry C, Boutroy S, Ellouz R, Duboeuf F, Chapurlat R, Follet H, et al. Clinical cone beam computed tomography compared to high-resolution peripheral computed tomography in the assessment of distal radius bone. Osteoporos Int. 2016;27:3073–82.

  60. “VirtuOst: Fracture Risk Assessment” ON Diagnostics, https://ondiagnostics.com/. Accessed 10 Apr 2021.

  61. Robson MD, Gatehouse PD, Bydder M, Bydder GM. Magnetic resonance: an introduction to ultrashort TE (UTE) imaging. J Comput Assist Tomogr. 2003;27:825–46.

    Article  PubMed  Google Scholar 

  62. Nyman JS, Ni Q, Nicolella DP, Wang X. Measurements of mobile and bound water by nuclear magnetic resonance correlate with mechanical properties of bone. Bone. 2008;42:193–9.

    Article  CAS  PubMed  Google Scholar 

  63. Horch RA, Gochberg DF, Nyman JS, Does MD. Non-invasive predictors of human cortical bone mechanical properties: T2-discriminated 1H NMR compared with high resolution X-ray. PLoS ONE. 2011;6:e16359.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Wurnig MC, Calcagni M, Kenkel D, Vich M, Weiger M, Andreisek G, et al. NMR in Biomedicine. 2014;27:1159–66.

  65. Horch RA, Nyman JS, Gochberg DF, Dortch RD, Does MD. Characterization of 1H NMR signal in human cortical bone for magnetic resonance imaging. Magn Reson Med. 2010;64:680–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Du J, Bydder GM. Qualitative and quantitative ultrashort-TE MRI of cortical bone. NMR Biomed. 2013;26:489–506.

    Article  PubMed  Google Scholar 

  67. Weiger M, Stampanoni M, Pruessmann KP. Direct depiction of bone microstructure using MRI with zero echo time. Bone. 2013;54:44–7.

    Article  PubMed  Google Scholar 

  68. M. Garwood, D. Idiyatullin, C. Corum, R. Chamberlain, S. Moeller, N. Kobayashi, L. Lehto, J. Zhang, R. Connell, M. Tesch, M. Nissi, J. Ellermann, D. Nixdorf. “About Cone Beam CT” CurveBeam (2012). https://curvebeam.com/resources/tmp/, Accessed 10 Apr 2021.

  69. Wu Y, Ackerman JL, Chesler DA, Graham L, Wang Y, Glimcher MJ. Density of organic matrix of native mineralized bone measured by water- and fat-suppressed proton projection MRI. Magn Reson Med. 2003;50:59–68.

    Article  PubMed  Google Scholar 

  70. Ma Y-J, Jerban S, Jang H, Chang D, Chang EY, Du J. Quantitative ultrashort echo time (UTE) magnetic resonance imaging of bone: an update. Front Endocrinol. 2020;11.

  71. Zhao X, Song HK, Seifert AC, Li C, Wehrli FW. Feasibility of assessing bone matrix and mineral properties in vivo by combined solid-state 1H and 31P MRI. PLoS ONE. 2017;12:e0173995.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Jones BC, Jia S, Lee H, Feng A, Shetye SS, Batzdorf A, et al. MRI-derived porosity index is associated with whole-bone stiffness and mineral density in human cadaveric femora. Bone. 2021;143:115774.

  73. Majumdar S. Magnetic resonance imaging of trabecular bone structure. Top Magn Reson Imaging. 2002;13:323–34.

    Article  PubMed  Google Scholar 

  74. Ma Y-J, Chen Y, Li L, Cai Z, Wei Z, Jerban S, et al. Trabecular bone imaging using a 3D adiabatic inversion recovery prepared ultrashort TE Cones sequence at 3T. Magn Reson Med. 2020;83:1640–51.

  75. Zaia A, Rossi R, Galeazzi R, Sallei M, Maponi P, Scendoni P. Fractal lacunarity of trabecular bone in vertebral MRI to predict osteoporotic fracture risk in over-fifties women. The LOTO study. BMC Musculoskelet Disord. 2021;22:108.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. 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;90:6508–15.

    Article  CAS  PubMed  Google Scholar 

  77. Christen P, Muller R. In vivo visualisation and quantification of bone resorption and bone formation from time-lapse imaging. Curr Osteoporos Rep. 2017;15:311–7.

    Article  PubMed  Google Scholar 

  78. Brunet SC, Kuczynski MT, Bhatla JL, Lemay S, Pauchard Y, Salat P, et al. The utility of multi-stack alignment and 3D longitudinal image registration to assess bone remodeling in rheumatoid arthritis patients from second generation HR-pQCT scans. BMC Med Imaging. 2020;20:36–6.

  79. Christen P, Boutroy S, Ellouz R, Chapurlat R, van Rietbergen B. Least-detectable and age-related local in vivo bone remodelling assessed by time-lapse HR-pQCT. PLoS ONE. 2018;13:e0191369.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Frost HM. From Wolff’s law to the Utah paradigm: insights about bone physiology and its clinical applications. Anat Rec. 2001;262:398–419.

    Article  CAS  PubMed  Google Scholar 

  81. Mancuso ME, Troy KL. Relating bone strain to local changes in radius microstructure following 12 months of axial forearm loading in women. J Biomech Eng. 2020;142.

  82. Christen P, Ito K, Ellouz R, Boutroy S, Sornay-Rendu E, Chapurlat RD, et al. Bone remodelling in humans is load-driven but not lazy. Nat Commun. 2014;5:4855.

  83. Kroker A, Besler BA, Bhatla JL, Shtil M, Salat P, Mohtadi N, et al. Longitudinal effects of acute anterior cruciate ligament tears on peri-articular bone in human knees within the first year of injury. J Orthop Res. 2019;37:2325–36.

  84. Kazakia GJ, Kuo D, Schooler J, Siddiqui S, Shanbhag S, Bernstein G, et al. Bone and cartilage demonstrate changes localized to bone marrow edema-like lesions within osteoarthritic knees. Osteoarthr Cartil. 2013;21:94–101.

  85. Tse JJ, Brunet SC, Salat P, Hazlewood GS, Barnabe C, Manske SL. Multi-modal imaging to assess the interaction between inflammation and bone damage progression in inflammatory arthritis. Front Med. 2020;7.

  86. He J, Fang H, Li X. Vertebral bone marrow fat content in normal adults with varying bone densities at 3T magnetic resonance imaging. Acta Radiol. 2019;60:509–15.

    Article  PubMed  Google Scholar 

  87. Yoder JS, Kogan F, Gold GE. PET-MRI for the study of metabolic bone disease. Curr Osteoporos Rep. 2018;16:665–73.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Pahk K, Kwon Y, Kim M-K, Park S, Kim S. Visceral fat metabolic activity evaluated by 18F-FDG PET/CT is associated with osteoporosis in healthy postmenopausal Korean women. Obes Res Clin Pract. 2020;14:339–44.

    Article  PubMed  Google Scholar 

  89. Watkins L, MacKay J, Haddock B, Mazzoli V, Uhlrich S, Gold G, et al. Assessment of quantitative [(18)F]Sodium fluoride PET measures of knee subchondral bone perfusion and mineralization in osteoarthritic and healthy subjects. Osteoarthr Cartil. 2021;29:849–58.

  90. Haddock B, Fan AP, Uhlrich SD, Jørgensen NR, Suetta C, Gold GE, et al. Assessment of acute bone loading in humans using [18F]NaF PET/MRI. Eur J Nucl Med Mol Imaging. 2019;46:2452–63.

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Acknowledgements

JJT is supported by the Cumming School of Medicine Postdoctoral Fellowship; MTK, ACJS, and DAK are supported by Natural Sciences and Engineering Research Council (NSERC, Canada) fellowships. SLM’s research is supported by the Arthritis Society (Stars Early Career Investigator Award), NSERC, and the American Society for Bone and Mineral Research.

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Tse, J.J., Smith, A.C.J., Kuczynski, M.T. et al. Advancements in Osteoporosis Imaging, Screening, and Study of Disease Etiology. Curr Osteoporos Rep 19, 532–541 (2021). https://doi.org/10.1007/s11914-021-00699-3

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