Skip to main content

Advertisement

Log in

Opportunistic Use of Lumbar Magnetic Resonance Imaging for Osteoporosis Screening

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

Abstract

Summary

Magnetic resonance imaging (MRI) is a routine assessment before spine surgery. We found that the opportunistic use of MRI with the vertebral bone quality (VBQ) score has good diagnostic ability, with a threshold value of VBQ > 3.0, in recognizing patients who may need further osteoporosis evaluation.

Introduction

The purpose of this study was to determine whether the opportunistic use of magnetic resonance imaging (MRI) is useful for identifying spine surgical patients who need further osteoporosis evaluation.

Methods

This retrospective study evaluated 83 thoracolumbar spine surgery patients age ≥ 50 who received T1-weighted MRI. Opportunistic MRI was evaluated with the vertebral bone quality (VBQ) score, VBQ (fat) score, and signal-to-noise ratio (SNR). Each uses the median L1-L4 vertebral body signal intensities (SI) divided by either the L3 cerebrospinal fluid (CSF) SI, average SI of the L1 and S1 dorsal fat, or standard deviation (SD) of the background SI dorsal to the skin. Single-level VBQ was calculated as the ratio of the L1 vertebral body and L1 CSF SIs. Receiver-operator curve analysis was performed to determine diagnostic ability.

Results

The mean age was 70.10, 80% were female, and 96% were Caucasian. The mean ± SD VBQ, single-level VBQ, VBQ (fat), and SNR were 3.39 ± 0.68, 3.56 ± 0.81, 3.95 ± 1.89, and 113.18 ± 77.26, respectively. Using area under the curve, the diagnostic ability of VBQ, single-level VBQ, VBQ (fat), and SNR for clinical osteoporosis were 0.806, 0.779, 0.608, and 0.586, respectively. Diagnostic threshold values identified with optimal sensitivity and specificity were VBQ of 2.95 and single-level VBQ of 3.06.

Conclusion

Opportunistic use of MRI is a simple, effective tool that may help recognize patients who are at risk for complications related to bone disease. A VBQ > 3.0 can identify patients who need additional diagnostic evaluation.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

The data generated and analyzed for this study are not openly available due to the datasets containing patient identifying information. The data are available from the corresponding author on reasonable request.

Code availability

Not applicable.

References

  1. Bjerke BT, Zarrabian M, Aleem IS, Fogelson JL, Currier BL, Freedman BA, Bydon M, Nassr A (2018) Incidence of osteoporosis-related complications following posterior lumbar fusion. Glob spine J 8(6):563–569. https://doi.org/10.1177/2192568217743727

    Article  Google Scholar 

  2. Russell LA (2013) Osteoporosis and orthopedic surgery: effect of bone health on total joint arthroplasty outcome. Curr Rheumatol Rep 15(11):371. https://doi.org/10.1007/s11926-013-0371-x

    Article  PubMed  Google Scholar 

  3. Huang CC, Jiang CC, Hsieh CH, Tsai CJ, Chiang H (2016) Local bone quality affects the outcome of prosthetic total knee arthroplasty. J Orthop Res 34(2):240–248. https://doi.org/10.1002/jor.23003

    Article  CAS  PubMed  Google Scholar 

  4. Schreiber JJ, Anderson PA, Rosas HG, Buchholz AL, Au AG (2011) Hounsfield units for assessing bone mineral density and strength: a tool for osteoporosis management. J Bone Joint Surg Am 93(11):1057–1063. https://doi.org/10.2106/JBJS.J.00160

    Article  PubMed  Google Scholar 

  5. Bandirali M, Di Leo G, Papini GDE, Messina C, Sconfienza LM, Ulivieri FM, Sardenelli F (2015) A new diagnostic score to detect osteoporosis in patients undergoing lumbar spine MRI. Eur Radiol 25(10):2951–2959. https://doi.org/10.1007/s00330-015-3699-y

    Article  PubMed  Google Scholar 

  6. Ehresman J, Pennington Z, Schilling A, Lubelski D, Ahmed AK, Cottrill E, Khan M, Sciubba DM (2020) Novel MRI-based score for assessment of bone density in operative spine patients. Spine J 20(4):556–562. https://doi.org/10.1016/j.spinee.2019.10.018

    Article  PubMed  Google Scholar 

  7. Karampinos DC, Ruschke S, Gordijenko O, Grande Garcia E, Kooijman H, Burgkart R, Rummeny EJ, Bauer JS, Baum T (2015) Association of MRS-based vertebral bone marrow fat fraction with bone strength in a human in vitro model. J Osteoporos 2015https://doi.org/10.1155/2015/152349

  8. Cordes C, Baum T, Dieckmeyer M, Ruschke S, Diefenbach MN, Hauner H, Kirschke JS, Karampinos DC (2016) MR-Based assessment of bone marrow fat in osteoporosis, diabetes, and obesity. Front Endocrinol (Lausanne) 7(June):1–7. https://doi.org/10.3389/fendo.2016.00074

    Article  Google Scholar 

  9. Kühn JP, Hernando D, Meffert PJ, Reeder S, Hosten N, Laqua R, Steveling A, Ender S, Schroder H, Pillich DT (2013) Proton-density fat fraction and simultaneous R2*estimation as an MRI tool for assessment of osteoporosis. Eur Radiol 23(12):3432–3439. https://doi.org/10.1007/s00330-013-2950-7

    Article  PubMed  PubMed Central  Google Scholar 

  10. Meunier P, Aaron J, Edouard C, Vignon G (1971) Osteoporosis and the replacement of cell populations of the marrow by adipose tissue:A quantitative study of 84 iliac bone biopsies. Clin Orthop Relat Res 80(147):154. https://doi.org/10.1097/00003086-197110000-00021

    Article  Google Scholar 

  11. Shah LM, Hanrahan CJ (2011) MRI of spinal bone marrow: Part 1, techniques and normal age-related appearances. Am J Roentgenol 197(6):1298–1308. https://doi.org/10.2214/AJR.11.7005

    Article  Google Scholar 

  12. Shen W, Chen J, Gantz M, Punyanitya M, Heymsfield SB, Gallagher D, Albu J, Engelson E, Kotler D, Pi-Sunyer X, Gilsanz V (2012) MRI-measured pelvic bone marrow adipose tissue is inversely related to DXA-measured bone mineral in younger and older adults. Eur J Clin Nutr 66(9):983–988. https://doi.org/10.1038/ejcn.2012.35

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bloem JL, Reijnierse M, Huizinga TWJ, Van Der Helm-Van Mil AHM (2018) MR signal intensity: staying on the bright side in MR image interpretation. RMD Open 4(1):1–6. https://doi.org/10.1136/rmdopen-2018-000728

    Article  Google Scholar 

  14. Kanis JA, Johansson H, Harvey NC, McCloskey EV (2018) A brief history of FRAX. Arch Osteoporos 13(1):118. https://doi.org/10.1007/s11657-018-0510-0

    Article  PubMed  PubMed Central  Google Scholar 

  15. Cosman F, de Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S, Lindsay R (2014) Clinician’s guide to prevention and treatment of osteoporosis. Osteoporos Int 25(10):2359–2381. https://doi.org/10.1007/s00198-014-2794-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sijbers J, Poot D, Den Dekker AJ, Pintjens W (2007) Automatic estimation of the noise variance from the histogram of a magnetic resonance image. Phys Med Biol 52(5):1335–1348. https://doi.org/10.1088/0031-9155/52/5/009

    Article  PubMed  Google Scholar 

  17. McCloskey EV, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H, Barkmann R, Boutroy S, Brown J, Chapurlat R, Elders PJM, Fujita Y, Gl¨uer CC, Goltzman D, Iki M, Karlsson M, Kindmark A, Kotowicz M, Kurumatani N, Kwok T, Lamy O, Leung J, Lippuner K, Ljunggren O, Lorentzon M, Mellstrom D, Merlijn T, Oei L, Ohlsson C, Pasco JA, Rivadeneira F, Rosengren B, Sornay-Rendu E, Szulc P, Tamaki J, Kanis JA (2016) A meta-analysis of trabecular bone score in fracture risk prediction and its relationship to FRAX. J Bone Miner Res 31(5). https://doi.org/10.1002/jbmr.2734

  18. Camacho PM, Petak SM, Binkley N, Clarke BL, Harris ST, Hurley DL, Kleerekoper M, Lewiecki EM, Miller PD, Narula HS, Pessah-Pollack R, Tangpricha V, Wimalawansa SJ, Watts NB (2016) American Association of Clinical Endocrinologists and American College of Endocrinology clinical practice guidelines for the diagnosis and treatment of postmenopausal osteoporosis - 2016. Endocr Pract 22(Suppl 4):1–42. https://doi.org/10.4158/EP161435.GL

    Article  PubMed  Google Scholar 

  19. Kadri A, Binkley N, Hare KJ, Anderson PA (2020) Bone health optimization in orthopaedic surgery. J Bone Joint Surg Am 102(7):574–581. https://doi.org/10.2106/JBJS.19.00999

    Article  PubMed  Google Scholar 

  20. Mittra E, Rubin C, Qin YX (2005) Interrelationship of trabecular mechanical and microstructural properties in sheep trabecular bone. J Biomech 38(6):1229–1237. https://doi.org/10.1016/j.jbiomech.2004.06.007

    Article  PubMed  Google Scholar 

  21. Rosen CJ, Ackert-Bicknell C, Rodriguez JP, Pino AM (2009) Marrow fat and the bone microenvironment: developmental, functional, and pathological implications. Crit Rev Eukaryot Gene Expr 19(2):109–124. https://doi.org/10.1615/CritRevEukarGeneExpr.v19.i2.20

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Osterhoff G, Morgan EF, Shefelbine SJ, Karim L, McNamara LM, Augat P (2016) Bone mechanical properties and changes with osteoporosis. Injury 47(Suppl 2):S11–S20. https://doi.org/10.1016/S0020-1383(16)47003-8

    Article  PubMed  PubMed Central  Google Scholar 

  23. Kawai M, de Paula FJA, Rosen CJ (2012) New insights into osteoporosis: The bone-fat connection. J Intern Med 272(4):317–329. https://doi.org/10.1111/j.1365-2796.2012.02564.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Shayganfar A, Khodayi M, Ebrahimian S, Tabrizi Z (2019) Quantitative diagnosis of osteoporosis using lumbar spine signal intensity in magnetic resonance imaging. Br J Radiol 92(1097):1–5. https://doi.org/10.1259/bjr.20180774

    Article  Google Scholar 

  25. Saad MM, Ahmed AT, Mohamed KE, Habba MR (2019) Role of lumbar spine signal intensity measurement by MRI in the diagnosis of osteoporosis in post-menopausal women. Egypt J Radiol Nucl Med 50(1) https://doi.org/10.1186/s43055-019-0046-3

  26. Coupé P, Manjón JV, Gedamu E, Arnold D, Robles M, Collins DL (2010) Robust Rician noise estimation for MR images. Med Image Anal 14(4):483–493. https://doi.org/10.1016/j.media.2010.03.001

    Article  PubMed  Google Scholar 

  27. Spector R, Robert Snodgrass S, Johanson CE (2015) A balanced view of the cerebrospinal fluid composition and functions: focus on adult humans. Exp Neurol 273:57–68. https://doi.org/10.1016/j.expneurol.2015.07.027

    Article  CAS  PubMed  Google Scholar 

  28. Damkier HH, Brown PD, Praetorius J (2010) Epithelial pathways in choroid plexus electrolyte transport. Physiology 25(4):239–249. https://doi.org/10.1152/physiol.00011.2010

    Article  CAS  PubMed  Google Scholar 

  29. Ehresman J, Ahmed AK, Lubelski D, Schilling A, Pennington Z, Cottrill E, McCracken J, Khan M, Witham T, Sciubba DM (2020) Vertebral bone quality score and postoperative lumbar lordosis associated with need for reoperation after lumbar fusion. World Neurosurg 140:e247–e252. https://doi.org/10.1016/j.wneu.2020.05.020

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank Jennifer Wang for her assistance in creating the REDCap database and Scott Hetzel for his consultation on statistical methods.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. A. Anderson.

Ethics declarations

Ethics approval

The University of Wisconsin’s IRB approved this retrospective study (2019–0420-CP003).

Consent to participate

The study was exempt from obtaining signed informed consent.

Consent for publication

All authors consent to the publication of this manuscript.

Conflicts of interest

Mr. Kadri and Dr. Binkley have nothing to disclose. Dr. Hernando is a co-founder of Calimetrix, LLC. Dr. Anderson reports personal fees from Radius Medical, Amgen, and Medtronic and stock interest in Titan Spine, outside of this submitted work.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Investigation performed at the University of Wisconsin School of Medicine and Public Health.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (EPS 1296 KB)

Supplementary file2 (EPS 1275 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kadri, A., Binkley, N., Hernando, D. et al. Opportunistic Use of Lumbar Magnetic Resonance Imaging for Osteoporosis Screening. Osteoporos Int 33, 861–869 (2022). https://doi.org/10.1007/s00198-021-06129-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00198-021-06129-5

Keywords

Navigation