Skip to main content

Advertisement

SpringerLink
Log in

Biopsy vs. peripheral computed tomography to assess bone disease in CKD patients on dialysis: differences and similarities

  • Original Article
  • Published:
Osteoporosis International Aims and scope Submit manuscript

Abstract

Summary

Results from bone biopsy and high-resolution peripheral quantitative computed tomography (HR-pQCT) were compared in 31 CKD patients. There was an agreement mainly for cortical compartment that may represent a perspective on the fracture risk assessment. HR-pQCT also provided some clues on the turnover status, which warrants further studies.

Introduction

Chronic kidney disease (CKD) patients are at high risk of bone disease. Although bone biopsy is considered the best method to evaluate bone disease, it is expensive and not always available. Here we have compared, for the first time, data obtained from bone biopsy and HR-pQCT in a sample of CKD patients on dialysis.

Methods

HR-pQCT and dual-energy X-ray absorptiometry (DXA) were performed in 31 CKD patients (30 on dialysis). Biopsies were analyzed by quantitative histomorphometry, and classified according to TMV.

Results

We have found an inverse correlation between radius cortical density measured by HR-pQCT, with serum, as well as histomorphometric bone remodeling markers. Trabecular density and BV/TV measured through HR-pQCT in the distal radius correlated with trabecular and mineralized trabecular bone volume. Trabecular number, separation, and thickness obtained from HR-pQCT and from bone biopsy correlated with each other. Patients with cortical porosity on bone histomorphometry presented lower cortical density at the distal radius. Cortical density at radius was higher while bone alkaline phosphatase was lower in patients with low turnover. Combined, these parameters could identify the turnover status better than individually.

Conclusions

There was an agreement between HR-pQCT and bone biopsy parameters, particularly in cortical compartment, which may point to a new perspective on the fracture risk assessment for CKD patients. Besides classical bone resorption markers, HR-pQCT provided some clues on the turnover status by measurements of cortical density at radius, although the significance of this finding warrants further studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Kidney Disease: Improving Global Outcomes CKDMBDWG (2009) KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). Kidney Int Suppl S1-130

  2. Fusaro M, Gallieni M, Jamal SA (2014) Fractures in chronic kidney disease: neglected, common, and associated with sickness and death. Kidney Int 85:20–22

    Article  PubMed  Google Scholar 

  3. Tentori F, McCullough K, Kilpatrick RD, Bradbury BD, Robinson BM, Kerr PG, Pisoni RL (2014) High rates of death and hospitalization follow bone fracture among hemodialysis patients. Kidney Int 85:166–173

    Article  PubMed  Google Scholar 

  4. Wakasugi M, Kazama JJ, Narita I (2014) High rates of death and hospitalization follow bone fracture among hemodialysis patients. Kidney Int 86:649

    Article  PubMed  Google Scholar 

  5. Goldenstein PT, Jamal SA, Moyses RM (2015) Fractures in chronic kidney disease: pursuing the best screening and management. Curr Opin Nephrol Hypertens 24:317–323

    PubMed  Google Scholar 

  6. Jamal SA, West SL, Miller PD (2012) Fracture risk assessment in patients with chronic kidney disease. Osteoporos Int 23:1191–1198

    Article  CAS  PubMed  Google Scholar 

  7. Kanis JA, Johnell O, Oden A, Jonsson B, De Laet C, Dawson A (2000) Risk of hip fracture according to the World Health Organization criteria for osteopenia and osteoporosis. Bone 27:585–590

    Article  CAS  PubMed  Google Scholar 

  8. Iimori S, Mori Y, Akita W, Kuyama T, Takada S, Asai T, Kuwahara M, Sasaki S, Tsukamoto Y (2012) 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

    Article  CAS  PubMed  Google Scholar 

  9. Jamal S, Cheung AM, West S, Lok C (2012) 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 23:2805–2813

    Article  CAS  PubMed  Google Scholar 

  10. Jamal SA, Nickolas TL (2015) Bone imaging and fracture risk assessment in kidney disease. Curr Osteoporos Rep 13:166–172

    Article  PubMed  Google Scholar 

  11. 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

    Article  PubMed  Google Scholar 

  12. Yenchek RH, Ix JH, Shlipak MG et al (2012) Bone mineral density and fracture risk in older individuals with CKD. Clin J Am Soc Nephrol 7:1130–1136

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Negri AL, Del Valle EE, Zanchetta MB, Nobaru M, Silveira F, Puddu M, Barone R, Bogado CE, Zanchetta JR (2012) Evaluation of bone microarchitecture by high-resolution peripheral quantitative computed tomography (HR-pQCT) in hemodialysis patients. Osteoporos Int 23:2543–2550

    Article  CAS  PubMed  Google Scholar 

  14. Nickolas TL, Stein E, Cohen A, Thomas V, Staron RB, McMahon DJ, Leonard MB, Shane E (2010) Bone mass and microarchitecture in CKD patients with fracture. J Am Soc Nephrol 21:1371–1380

    Article  PubMed  PubMed Central  Google Scholar 

  15. Cohen A, Dempster DW, Muller R et al (2010) Assessment of trabecular and cortical architecture and mechanical competence of bone by high-resolution peripheral computed tomography: comparison with transiliac bone biopsy. Osteoporos Int 21:263–273

    Article  CAS  PubMed  Google Scholar 

  16. Pereira RC, Bischoff DS, Yamaguchi D, Salusky IB, Wesseling-Perry K (2015) Micro-CT in the assessment of pediatric renal osteodystrophy by bone histomorphometry. Clin J Am Soc Nephrol

  17. Tamminen IS, Isaksson H, Aula AS, Honkanen E, Jurvelin JS, Kroger H (2011) Reproducibility and agreement of micro-CT and histomorphometry in human trabecular bone with different metabolic status. J Bone Miner Metab 29:442–448

    Article  PubMed  Google Scholar 

  18. Parfitt AM, Drezner MK, Glorieux FH, Kanis JA, Malluche H, Meunier PJ, Ott SM, Recker RR (1987) Bone histomorphometry: standardization of nomenclature, symbols, and units. Report of the ASBMR Histomorphometry Nomenclature Committee. J Bone Miner Res 2:595–610

    Article  CAS  PubMed  Google Scholar 

  19. Dos Reis LM, Batalha JR, Munoz DR, Borelli A, Correa PH, Carvalho AB, Jorgetti V (2007) Brazilian normal static bone histomorphometry: effects of age, sex, and race. J Bone Miner Metab 25:400–406

    Article  PubMed  Google Scholar 

  20. Vedi S, Compston JE, Webb A, Tighe JR (1983) Histomorphometric analysis of dynamic parameters of trabecular bone formation in the iliac crest of normal British subjects. Metab Bone Dis Relat Res 5:69–74

    Article  PubMed  Google Scholar 

  21. Moe S, Drueke T, Cunningham J et al (2006) Definition, evaluation, and classification of renal osteodystrophy: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 69:1945–1953

    Article  CAS  PubMed  Google Scholar 

  22. Malluche HH, Mawad HW, Monier-Faugere MC (2011) Renal osteodystrophy in the first decade of the new millennium: analysis of 630 bone biopsies in black and white patients. J Bone Miner Res 26:1368–1376

    Article  PubMed  Google Scholar 

  23. Pasoto SG, Augusto KL, Alvarenga JC, Takayama L, Oliveira RM, Bonfa E, Pereira RM (2016) Cortical bone density and thickness alterations by high-resolution peripheral quantitative computed tomography: association with vertebral fractures in primary Sjogren's syndrome. Rheumatology (Oxford) 55:2200–2211

    Article  Google Scholar 

  24. Cejka D, Patsch JM, Weber M, Diarra D, Riegersperger M, Kikic Z, Krestan C, Schueller-Weidekamm C, Kainberger F, Haas M (2011) Bone microarchitecture in hemodialysis patients assessed by HR-pQCT. Clin J Am Soc Nephrol 6:2264–2271

    Article  PubMed  PubMed Central  Google Scholar 

  25. Nickolas TL, Stein EM, Dworakowski E et al (2013) Rapid cortical bone loss in patients with chronic kidney disease. J Bone Miner Res 28:1811–1820

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Amstrup AK, Jakobsen NF, Moser E, Sikjaer T, Mosekilde L, Rejnmark L (2015) Association between bone indices assessed by DXA, HR-pQCT and QCT scans in post-menopausal women. J Bone Miner Metab

  27. Jones G (2015) Interpreting vitamin D assay results: proceed with caution. Clin J Am Soc Nephrol 10:331–334

    Article  CAS  PubMed  Google Scholar 

  28. Cooper D, Turinsky A, Sensen C, Hallgrimsson B (2007) Effect of voxel size on 3D micro-CT analysis of cortical bone porosity. Calcif Tissue Int 80:211–219

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Operating grant 2011/22962-3 provided by Fundação de Amparo à Pesquisa do Estado de São Paulo—FAPESP, supported this work. This work was presented in part at ASN meeting, 2014, Philadelphia, USA. E. David-Neto, R. Moysés and V. Jorgetti were supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Renal Transplant Service, Hospital das Clínicas, University of São Paulo School of Medicine, São Paulo, Brazil

    I. D. B. Marques, M. J. C. L. N. Araújo, M. R. Custódio & E. David-Neto

  2. Nephrology Division, Hospital das Clínicas, University of São Paulo School of Medicine, São Paulo, Brazil

    M. J. C. L. N. Araújo, F. G. Graciolli, L. M . dos Reis, M. R. Custódio, V. Jorgetti, R. M. Elias & R. M. A. Moysés

  3. Rheumatology Division, Hospital das Clínicas, University of São Paulo School of Medicine, São Paulo, Brazil

    R. M. Pereira

  4. Universidade Nove de Julho (UNINOVE), Rua Iperoig, 690 ap 121, São Paulo, SP, 05016-000, Brazil

    R. M. A. Moysés

Authors
  1. I. D. B. Marques
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. J. C. L. N. Araújo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. F. G. Graciolli
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. L. M . dos Reis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. R. M. Pereira
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. R. Custódio
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. V. Jorgetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. R. M. Elias
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. E. David-Neto
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. R. M. A. Moysés
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R. M. A. Moysés.

Ethics declarations

Conflicts of interest

Drs. Rosa Moysés and Vanda Jorgetti have received honoraria for lectures and are on the speaker’s bureau for Amgen. Igor Marques, Maria Júlia Araújo, Fabiana Graciolli, Luciene dos Reis, Rosa Pereira, Melani Custódio, Rosilene Elias, and Elias David-Neto declared they have no conflict.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Marques, I.D.B., Araújo, M.J.C.L.N., Graciolli, F.G. et al. Biopsy vs. peripheral computed tomography to assess bone disease in CKD patients on dialysis: differences and similarities. Osteoporos Int 28, 1675–1683 (2017). https://doi.org/10.1007/s00198-017-3956-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00198-017-3956-9

Keywords

Search

Navigation