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Is dual-energy absorptiometry accurate in the assessment of bone status of patients with chronic kidney disease?

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A Correction to this article was published on 26 June 2023

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Abstract

Summary

Several patients with chronic kidney disease (CKD) have deteriorated bone status. Estimation of bone status using DXA has limitations especially in patients with CKD accompanying aortic calcifications. Quantitative CT and the trabecular bone score could be more accurate methods to estimate bone status for patients with CKD and vascular calcifications.

Introduction

It remains unclear whether dual-energy absorptiometry (DXA) is appropriate for the assessment of bone status in patients with chronic kidney disease (CKD), a disease that impacts bone health. The aims of this study were to compare DXA and central quantitative computed tomography (cQCT) and to evaluate bone status in patients with pre-dialysis CKD.

Methods

This retrospective study included 363 healthy control subjects whose bone mineral density (BMD) was evaluated with DXA and 117 CKD patients whose BMD was evaluated using both cQCT and DXA. Diagnostic discordance was assessed between the lumbar spine (LS) and femur neck (FN) from DXA or between two modalities. The trabecular bone score (TBS) was extracted from DXA images. The volume of abdominal aortic calcification (AAC) was calculated using CT images from cQCT.

Results

Using LS DXA T-score, osteoporosis was less common in the CKD group than in controls. Patients with normal LS BMD using DXA were reclassified into osteopenia or osteoporosis using cQCT in CKD patients. Among discordant subjects between FN and LS in DXA, a higher BMD of LS was more common in CKD patients than in controls. CKD patients had lower TBS than controls despite having the same diagnosis using DXA. AAC volume negatively correlated with BMD from cQCT and with TBS but not with BMD from DXA.

Conclusions

TBS and cQCT could accurately assess bone status in CKD patients since DXA may overestimate LS BMD, likely due to an increased AAC volume.

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References

  1. Moe S, Drüeke T, Cunningham J, Goodman W, Martin K, Olgaard K, Ott S, Sprague S, Lameire N, Eknoyan G (2006) Definition, evaluation, and classification of renal osteodystrophy: a position statement from kidney disease: improving global outcomes (KDIGO). Kidney Int 69:1945–1953

    CAS  PubMed  Google Scholar 

  2. Khairallah P, Nickolas TL (2018) Management of Osteoporosis in CKD. Clin J Am Soc Nephrol 13:962–969

    PubMed  PubMed Central  Google Scholar 

  3. Alem AM, Sherrard DJ, Gillen DL, Weiss NS, Beresford SA, Heckbert SR, Wong C, Stehman-Breen C (2000) Increased risk of hip fracture among patients with end-stage renal disease. Kidney Int 58:396–399

    CAS  PubMed  Google Scholar 

  4. Nickolas TL, McMahon DJ, Shane E (2006) Relationship between moderate to severe kidney disease and hip fracture in the United States. J Am Soc Nephrol 17:3223–3232

    PubMed  Google Scholar 

  5. Ensrud KE, Lui L-Y, Taylor BC, Ishani A, Shlipak MG, Stone KL, Cauley JA, Jamal SA, Antoniucci DM, Cummings SR (2007) Renal function and risk of hip and vertebral fractures in older women. Arch Intern Med 167:133–139

    PubMed  Google Scholar 

  6. Kwon YE, Choi HY, Kim S, Ryu D-R, Oh HJ (2019) Fracture risk in chronic kidney disease: a Korean population-based cohort study. Kidney Res Clin Pract 38:220–228

    PubMed  PubMed Central  Google Scholar 

  7. Ketteler M, Block GA, Evenepoel P, Fukagawa M, Herzog CA, McCann L, Moe SM, Shroff R, Tonelli MA, Toussaint ND (2017) Executive summary of the 2017 KDIGO chronic kidney disease–mineral and bone disorder (CKD-MBD) guideline update: what’s changed and why it matters. Kidney Int 92:26–36

    PubMed  Google Scholar 

  8. Kanis JA, Melton LJ 3rd, Christiansen C, Johnston CC, Khaltaev N (1994) The diagnosis of osteoporosis. J Bone Miner Res 9:1137–1141

    CAS  PubMed  Google Scholar 

  9. El Maghraoui A, Roux C (2008) DXA scanning in clinical practice. QJM 101:605–617

    PubMed  Google Scholar 

  10. Johnell O, Kanis JA, Oden A, Johansson H, de Laet C, Delmas P, Eisman JA, Fujiwara S, Kroger H, Mellstrom D, Meunier PJ, Melton LJ III, O’Neill T, Pols H, Reeve J, Silman A, Tenenhouse A (2005) Predictive value of BMD for hip and other fractures. J Bone Miner Res 20:1185–1194

    PubMed  Google Scholar 

  11. Li N, Li X-m, Xu L, Sun W-j, Cheng X-g, Tian W (2013) Comparison of QCT and DXA: osteoporosis detection rates in postmenopausal women. Int J Endocrinol 2013:1–5

    Google Scholar 

  12. Adams JE (2009) Quantitative computed tomography. Eur J Radiol 71:415–424

    PubMed  Google Scholar 

  13. Pothuaud L, Carceller P, Hans D (2008) Correlations between grey-level variations in 2D projection images (TBS) and 3D microarchitecture: applications in the study of human trabecular bone microarchitecture. Bone 42:775–787

    PubMed  Google Scholar 

  14. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D (1999) A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 130:461–470

    CAS  PubMed  Google Scholar 

  15. West SL, Lok CE, Langsetmo L, Cheung AM, Szabo E, Pearce D, Fusaro M, Wald R, Weinstein J, Jamal SA (2015) Bone mineral density predicts fractures in chronic kidney disease. J Bone Miner Res 30:913–919

    PubMed  Google Scholar 

  16. Yenchek RH, Ix JH, Shlipak MG, Bauer DC, Rianon NJ, Kritchevsky SB, Harris TB, Newman AB, Cauley JA, Fried LF (2012) Bone mineral density and fracture risk in older individuals with CKD. Clin J Am Soc Nephrol 7:1130–1136

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Naylor KL, Garg AX, Zou G, Langsetmo L, Leslie WD, Fraser L-A, Adachi JD, Morin S, Goltzman D, Lentle B (2015) Comparison of fracture risk prediction among individuals with reduced and normal kidney function. Clin J Am Soc Nephrol 10:646–653

    PubMed  PubMed Central  Google Scholar 

  18. Iimori S, Mori Y, Akita W, Kuyama T, Takada S, Asai T, Kuwahara M, Sasaki S, Tsukamoto Y (2011) Diagnostic usefulness of bone mineral density and biochemical markers of bone turnover in predicting fracture in CKD stage 5D patients—a single-center cohort study. Nephrol Dial Transplant 27:345–351

    PubMed  Google Scholar 

  19. Kim K, Kim IJ, Pak K, Kim SJ, Shin S, Kim BH, Kim SS, Lee BJ, Jeon YK (2018) Evaluation of bone mineral density using DXA and cQCT in postmenopausal patients under thyrotropin suppressive therapy. J Clin Endocrinol Metab 103:4232–4240

    PubMed  Google Scholar 

  20. Yu W, Glüer C-C, Fuerst T, Grampp S, Li J, Lu Y, Genant H (1995) Influence of degenerative joint disease on spinal bone mineral measurements in postmenopausal women. Calcif Tissue Int 57:169–174

    CAS  PubMed  Google Scholar 

  21. Ito M, Hayashi K, Yamada M, Uetani M, Nakamura T (1993) Relationship of osteophytes to bone mineral density and spinal fracture in men. Radiology 189:497–502

    CAS  PubMed  Google Scholar 

  22. Engelke K, Adams JE, Armbrecht G, Augat P, Bogado CE, Bouxsein ML, Felsenberg D, Ito M, Prevrhal S, Hans DB (2008) 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 11:123–162

    PubMed  Google Scholar 

  23. Solomou G, Damilakis J (2016) Radiation exposure in bone densitometry. Semin Musculoskelet Radiol 20:392–398

    CAS  PubMed  Google Scholar 

  24. Hans D, Barthe N, Boutroy S, Pothuaud L, Winzenrieth R, Krieg M-A (2011) 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 14:302–312

    PubMed  Google Scholar 

  25. Pothuaud L, Barthe N, Krieg M-A, Mehsen N, Carceller P, Hans D (2009) Evaluation of the potential use of trabecular bone score to complement bone mineral density in the diagnosis of osteoporosis: a preliminary spine BMD–matched, case-control study. J Clin Densitom 12:170–176

    PubMed  Google Scholar 

  26. Silva BC, Leslie WD, Resch H, Lamy O, Lesnyak O, Binkley N, McCloskey EV, Kanis JA, Bilezikian JP (2014) Trabecular bone score: a noninvasive analytical method based upon the DXA image. J Bone Miner Res 29:518–530

    PubMed  Google Scholar 

  27. Ramalho J, Marques I, Hans D, Dempster D, Zhou H, Patel P, Pereira R, Jorgetti V, Moyses R, Nickolas TL (2018) The trabecular bone score: relationships with trabecular and cortical microarchitecture measured by HR-pQCT and histomorphometry in patients with chronic kidney disease. Bone 116:215–220

    CAS  PubMed  Google Scholar 

  28. Naylor KL, Prior J, Garg AX, Berger C, Langsetmo L, Adachi JD, Goltzman D, Kovacs CS, Josse RG, Leslie WD (2016) Trabecular bone score and incident fragility fracture risk in adults with reduced kidney function. Clin J Am Soc Nephrol 11:2032–2040

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Dusceac R, Niculescu DA, Dobre R, Dragne MC, Tacu C, Peride I, David C, Checherita I, Poiana C (2018) Chronic hemodialysis is associated with lower trabecular bone score, independent of bone mineral density: a case-control study. Arch Osteoporos 13:125

    PubMed  Google Scholar 

  30. Aleksova J, Kurniawan S, Vucak-Dzumhur M, Kerr P, Ebeling PR, Milat F, Elder GJ (2018) Aortic vascular calcification is inversely associated with the trabecular bone score in patients receiving dialysis. Bone 113:118–123

    CAS  PubMed  Google Scholar 

  31. De Laet C, Kanis J, Odén A, Johanson H, Johnell O, Delmas P, Eisman J, Kroger H, Fujiwara S, Garnero P (2005) Body mass index as a predictor of fracture risk: a meta-analysis. Osteoporos Int 16:1330–1338

    PubMed  Google Scholar 

  32. Carter DR, Bouxsein ML, Marcus R (1992) New approaches for interpreting projected bone densitometry data. J Bone Miner Res 7:137–145

    CAS  PubMed  Google Scholar 

  33. Savvidis C, Tournis S, Dede AD (2018) Obesity and bone metabolism. Hormones 17:205–217

    PubMed  Google Scholar 

  34. Evans AL, Paggiosi MA, Eastell R, Walsh JS (2015) Bone density, microstructure and strength in obese and normal weight men and women in younger and older adulthood. J Bone Miner Res 30:920–928

    PubMed  Google Scholar 

  35. Yu EW, Thomas BJ, Brown JK, Finkelstein JS (2012) Simulated increases in body fat and errors in bone mineral density measurements by DXA and QCT. J Bone Miner Res 27:119–124

    PubMed  Google Scholar 

  36. Hyder JA, Allison MA, Wong N, Papa A, Lang TF, Sirlin C, Gapstur SM, Ouyang P, Carr JJ, Criqui MH (2008) Association of coronary artery and aortic calcium with lumbar bone density: the MESA Abdominal Aortic Calcium Study. Am J Epidemiol 169:186–194

    PubMed  PubMed Central  Google Scholar 

  37. Farhat GN, Cauley JA, Matthews KA, Newman AB, Johnston J, Mackey R, Edmundowicz D, Sutton-Tyrrell K (2006) Volumetric BMD and vascular calcification in middle-aged women: the study of women’s health across the nation. J Bone Miner Res 21:1839–1846

    PubMed  Google Scholar 

  38. Schulz E, Arfai K, Liu X, Sayre J, Gilsanz V (2004) Aortic calcification and the risk of osteoporosis and fractures. J Clin Endocrinol Metab 89:4246–4253

    CAS  PubMed  Google Scholar 

  39. Demer LL, Tintut Y (2009) Mechanisms linking osteoporosis with cardiovascular calcification. Curr Osteoporos Rep 7:42–46

    PubMed  PubMed Central  Google Scholar 

  40. Parhami F, Morrow AD, Balucan J, Leitinger N, Watson AD, Tintut Y, Berliner JA, Demer LL (1997) Lipid oxidation products have opposite effects on calcifying vascular cell and bone cell differentiation: a possible explanation for the paradox of arterial calcification in osteoporotic patients. Arterioscler Thromb Vasc Biol 17:680–687

    CAS  PubMed  Google Scholar 

  41. Tintut Y, Morony S, Demer LL (2004) Hyperlipidemia promotes osteoclastic potential of bone marrow cells ex vivo. Arterioscler Thromb Vasc Biol 24:e6–e10

    CAS  PubMed  Google Scholar 

  42. Nakamura S, Ishibashi-Ueda H, Niizuma S, Yoshihara F, Horio T, Kawano Y (2009) Coronary calcification in patients with chronic kidney disease and coronary artery disease. Clin J Am Soc Nephrol 4:1892–1900

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Griffith JF, Yeung DK, Antonio GE, Lee FK, Hong AW, Wong SY, Lau EM, Leung PC (2005) Vertebral bone mineral density, marrow perfusion, and fat content in healthy men and men with osteoporosis: dynamic contrast-enhanced MR imaging and MR spectroscopy. Radiology 236:945–951

    PubMed  Google Scholar 

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Acknowledgments

We appreciate the Department of Nuclear Medicine for the kind cooperation in the further evaluation of the patients.

Funding

This study has received funding by the Biomedical Research Institute Grant of Pusan National University Hospital (2018B025).

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Correspondence to Y.K. Jeon.

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Ethical approval

This retrospective study was approved by our institutional review board, and the requirement for written consent was waived (IRB No. H-1906-004-079).

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The original online version of this article was revised: The affiliation details for Author K. Kim were incorrectly given as 'Department of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea.' but should have been 'Department of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital and School of Medicine, Pusan National University, Busan, Republic of Korea'.

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Kim, K., Song, S., Kim, IJ. et al. Is dual-energy absorptiometry accurate in the assessment of bone status of patients with chronic kidney disease?. Osteoporos Int 32, 1859–1868 (2021). https://doi.org/10.1007/s00198-020-05670-z

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