Skip to main content
Log in

Use of proton density fat fraction MRI to predict the radiographic progression of osteoporotic vertebral compression fracture

  • Musculoskeletal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

This study evaluated the diagnostic performance of the proton density fat fraction (PDFF) in predicting the progression of osteoporotic vertebral compression fractures (OVCFs).

Methods

The cohort in this retrospective study consisted of 48 patients with OVCFs who underwent spine MRI that included PDFF between December 2016 and June 2018. The patients were divided into two groups (with versus without OVCF progression, based on the radiographic results obtained at the 6-month follow-up examination). Two musculoskeletal radiologists independently calculated the PDFF of the fracture and the PDFF ratio (fracture PDFF/normal vertebrae PDFF) using regions of interest. The mean values of these parameters were compared between the two groups, and the receiver operating characteristic curves were analysed.

Results

The mean age was significantly higher in the group with OVCF progression (71.6 ± 8.4 years) than in the group without (64.8 ± 10.5 years) (p = 0.018). According to reader 1, the PDFF ratio was significantly lower in the group with OVCF progression versus that without OVCF progression (0.38 ± 0.13 vs 0.51 ± 0.20; p = 0.009), whereas the difference in the PDFF itself was not statistically significant. The PDFF ratio [area under the curve (AUC) = 0.723; 95% confidence interval (CI), 0.575–0.842] had a larger AUC than did the PDFF (AUC = 0.667; 95% CI, 0.516–0.796). The optimal cut-off value of the PDFF ratio for predicting OVCF progression was 0.42; this threshold corresponded to sensitivity, specificity, and accuracy values of 84.0%, 60.9%, and 72.9%, respectively.

Conclusion

The age and PDFF ratio can be used to predict OVCF progression.

Key Points

Chemical shift-encoded magnetic resonance imaging provides quantitative parameters for predicting OVCF progression.

The PDFF ratio is significantly lower in patients with OVCF progression.

The PDFF ratio is superior to the PDFF for predicting OVCF progression.

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

Similar content being viewed by others

Abbreviations

AUC:

Area under the curve

BMD:

Bone mineral density

BMI:

Body mass index

CSE-MRI:

Chemical shift-encoded magnetic resonance imaging

DM:

Diabetes mellitus

FOV:

Field of view

HTN:

Hypertension

ICC:

Intraclass correlation coefficient

MRS:

Magnetic resonance spectroscopy

OVCF:

Osteoporotic vertebral compression fracture

PDFF:

Proton density fat fraction

ROC:

Receiver operating characteristic

ROI:

Region of interest

TE:

Echo time

TR:

Repetition time

VAS:

Visual analogue scale

References

  1. Cummings SR, Melton LJ (2002) Epidemiology and outcomes of osteoporotic fractures. Lancet 359:1761–1767

    Article  Google Scholar 

  2. Gabriel SE, Tosteson AN, Leibson CL et al (2002) Direct medical costs attributable to osteoporotic fractures. Osteoporos Int 13:323–330

    Article  CAS  Google Scholar 

  3. Longo UG, Loppini M, Denaro L, Maffulli N, Denaro V (2012) Osteoporotic vertebral fractures: current concepts of conservative care. Br Med Bull 102:171–189

    Article  Google Scholar 

  4. Kanchiku T, Taguchi T, Toyoda K, Fujii K, Kawai S (2003) Dynamic contrast-enhanced magnetic resonance imaging of osteoporotic vertebral fracture. Spine (Phila Pa 1976) 28:2522–2526 discussion 2522

    Article  Google Scholar 

  5. Kanchiku T, Imajo Y, Suzuki H, Yoshida Y, Taguchi T (2014) Usefulness of an early MRI-based classification system for predicting vertebral collapse and pseudoarthrosis after osteoporotic vertebral fractures. J Spinal Disord Tech 27:E61–E65

    Article  Google Scholar 

  6. Sugita M, Watanabe N, Mikami Y, Hase H, Kubo T (2005) Classification of vertebral compression fractures in the osteoporotic spine. J Spinal Disord Tech 18:376–381

    Article  Google Scholar 

  7. Tsujio T, Nakamura H, Terai H et al (2011) Characteristic radiographic or magnetic resonance images of fresh osteoporotic vertebral fractures predicting potential risk for nonunion: a prospective multicenter study. Spine (Phila Pa 1976) 36:1229–1235

    Article  Google Scholar 

  8. Ha KY, Kim YH (2013) Risk factors affecting progressive collapse of acute osteoporotic spinal fractures. Osteoporos Int 24:1207–1213

    Article  CAS  Google Scholar 

  9. Patil S, Nene AM (2014) Predictors of kyphotic deformity in osteoporotic vertebral compression fractures: a radiological study. Eur Spine J 23:2737–2742

    Article  Google Scholar 

  10. Omi H, Yokoyama T, Ono A, Numasawa T, Wada K, Fujisawa Y (2014) Can MRI predict subsequent pseudarthrosis resulting from osteoporotic thoracolumbar vertebral fractures? Eur Spine J 23:2705–2710

    Article  Google Scholar 

  11. Muratore M, Ferrera A, Masse A, Bistolfi A (2018) Osteoporotic vertebral fractures: predictive factors for conservative treatment failure. A systematic review. Eur Spine J 27:2565–2576

    Article  Google Scholar 

  12. Goldstein S, Smorgick Y, Mirovsky Y, Anekstein Y, Blecher R, Tal S (2016) Clinical and radiological factors affecting progressive collapse of acute osteoporotic compression spinal fractures. J Clin Neurosci 31:122–126

    Article  Google Scholar 

  13. Zhang J, He X, Fan Y, Du J, Hao D (2019) Risk factors for conservative treatment failure in acute osteoporotic vertebral compression fractures (OVCFs). Arch Osteoporos 14:24

    Article  Google Scholar 

  14. Schmeel FC, Luetkens JA, Enkirch SJ et al (2018) Proton density fat fraction (PDFF) MR imaging for differentiation of acute benign and neoplastic compression fractures of the spine. Eur Radiol 28:5001–5009

    Article  Google Scholar 

  15. Schmeel FC, Luetkens JA, Wagenhauser PJ et al (2018) Proton density fat fraction (PDFF) MRI for differentiation of benign and malignant vertebral lesions. Eur Radiol 28:2397–2405

    Article  Google Scholar 

  16. Zajick DC Jr, Morrison WB, Schweitzer ME, Parellada JA, Carrino JA (2005) Benign and malignant processes: normal values and differentiation with chemical shift MR imaging in vertebral marrow. Radiology 237:590–596

    Article  Google Scholar 

  17. Kim DH, Yoo HJ, Hong SH, Choi JY, Chae HD, Chung BM (2017) Differentiation of acute osteoporotic and malignant vertebral fractures by quantification of fat fraction with a Dixon MRI sequence. AJR Am J Roentgenol 209:1331–1339

    Article  Google Scholar 

  18. Fischer MA, Nanz D, Shimakawa A et al (2013) Quantification of muscle fat in patients with low back pain: comparison of multi-echo MR imaging with single-voxel MR spectroscopy. Radiology 266:555–563

    Article  Google Scholar 

  19. Schmeel FC, Vomweg T, Traber F et al (2019) Proton density fat fraction MRI of vertebral bone marrow: accuracy, repeatability, and reproducibility among readers, field strengths, and imaging platforms. J Magn Reson Imaging 50:1762–1772

    Article  Google Scholar 

  20. Sun K, Chai W, Fu C et al (2016) Diffusion-weighted imaging-guided MR spectroscopy in breast lesions using readout-segmented echo-planar imaging. Eur Radiol 26:1565–1574

    Article  Google Scholar 

  21. Koo TK, Li MY (2016) A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 15:155–163

    Article  Google Scholar 

  22. Meisamy S, Hines CD, Hamilton G et al (2011) Quantification of hepatic steatosis with T1-independent, T2-corrected MR imaging with spectral modeling of fat: blinded comparison with MR spectroscopy. Radiology 258:767–775

    Article  Google Scholar 

  23. Kuhn JP, Hernando D, Munoz del Rio A et al (2012) Effect of multipeak spectral modeling of fat for liver iron and fat quantification: correlation of biopsy with MR imaging results. Radiology 265:133–142

    Article  Google Scholar 

  24. Lee SH, Yoo HJ, Yu SM, Hong SH, Choi JY, Chae HD (2019) Fat quantification in the vertebral body: comparison of modified Dixon technique with single-voxel magnetic resonance spectroscopy. Korean J Radiol 20:126–133

    Article  Google Scholar 

  25. Kim D, Kim SK, Lee SJ, Choo HJ, Park JW, Kim KY (2019) Simultaneous estimation of the fat fraction and R(2)(*) via T(2)(*)-Corrected 6-echo Dixon volumetric interpolated breath-hold examination imaging for osteopenia and osteoporosis detection: correlations with sex, age, and menopause. Korean J Radiol 20:916–930

    Article  Google Scholar 

  26. Suh CH, Yun SJ, Jin W, Lee SH, Park SY, Ryu CW (2018) ADC as a useful diagnostic tool for differentiating benign and malignant vertebral bone marrow lesions and compression fractures: a systematic review and meta-analysis. Eur Radiol 28:2890–2902

    Article  Google Scholar 

  27. van Vucht N, Santiago R, Lottmann B et al (2019) The Dixon technique for MRI of the bone marrow. Skeletal Radiol 48:1861–1874

    Article  Google Scholar 

  28. Kugel H, Jung C, Schulte O, Heindel W (2001) Age- and sex-specific differences in the 1H-spectrum of vertebral bone marrow. J Magn Reson Imaging 13:263–268

    Article  CAS  Google Scholar 

Download references

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sunghoon Park.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Sunghoon Park.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

Additional information

Publisher’s note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yun, J.S., Lee, HD., Kwack, KS. et al. Use of proton density fat fraction MRI to predict the radiographic progression of osteoporotic vertebral compression fracture. Eur Radiol 31, 3582–3589 (2021). https://doi.org/10.1007/s00330-020-07529-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-020-07529-7

Keywords

Navigation