The diagnostic value of SE MRI and DWI of the spine in patients with monoclonal gammopathy of undetermined significance, smouldering myeloma and multiple myeloma

Abstract

Objectives

To evaluate DWI of the bone marrow in the differentiation of monoclonal gammopathy of undetermined significance (MGUS), smouldering myeloma (SMM) and multiple myeloma (MM).

Methods

The retrospective study includes 64 patients with MGUS, 27 with SMM, 64 with new MM and 12 controls. Signal intensity (SI) of spinal SE-MRI and DWI (b0-1000) as well as apparent diffusion coefficients (ADC) were measured in the T10 and L3. Qualitative assessment of b-images was performed by one experienced radiologist.

Results

ADC600 and ADC1000 are the best ADC values in differentiating patient groups (p < 0.030). SIT2, SIb1000 and ADC1000 are higher and SIT1 lower in L3 compared to T10 (p < 0.050). All quantitative parameters of L3 can differentiate significantly between MGUS and MM (p < 0.050) and between patients with percentage plasma cells (PC%) between 0-10 % compared to >50 % (p = 0.001). Only SIT2 for L3 can differentiate MGUS from SMM (p = 0.044) and PC%0-10 from PC%10-25 (p = 0.033). Qualitative interpretation of b1000 images allows differentiating MM patients from those with MGUS or SMM (p < 0.001).

Conclusions

Spinal SE-MRI can differentiate among MGUS, SMM, MM and control subjects. DWI based on the SI on b1000 images and ADC values is increased in MM compared to MGUS and SMM. Qualitative assessment of b-images can differentiate MM from MGUS or SMM.

Key points

ADC values are higher in patients with MM compared to MGUS

DWI parameters change late in disease evolution

DWI is sensitive but not specific in diagnosing patients with MM

Qualitative DWI assessment is good in detecting myeloma patients

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Abbreviations

IMWG:

International Myeloma Working Group

MRI:

Magnetic resonance imaging

CT:

Computed tomography

PET:

Positron emission tomography

DWI:

Diffusion-weighted imaging

ADC:

Apparent diffusion coefficient

SI:

Signal intensity

MGUS:

Monoclonal gammopathy of undetermined significance

SMM:

Smouldering myeloma

MM:

Multiple myeloma

ISS:

International Staging System

HME:

Hereditary multiple exostoses

NF:

Neurofibromatosis

EPI:

Echo planar imaging

ROI:

Region of interest

T:

Thoracic

L:

Lumbar

ROC:

Receiver-operating characteristic

AUC:

Area under the curve

PC%:

Percentage plasma cells

T1:

T1 weighted

fsT2:

Fat-suppressed T2 weighted

ST:

Slice thickness

TSE:

Turbo spin echo

TR:

Repetition time

TE:

Echo time

TI:

Inversion time

References

  1. 1.

    Shah R, Stieltjes B, Andrulis M et al (2013) Intravoxel incoherent motion imaging for assessment of bone marrow infiltration of monoclonal plasma cell diseases. Ann Hematol 92:1553–1557

    PubMed  Article  Google Scholar 

  2. 2.

    Dutoit JC, Vanderkerken MA, Verstraete KL (2013) Value of whole body MRI and dynamic contrast enhanced MRI in the diagnosis, follow-up and evaluation of disease activity and extent in multiple myeloma. Eur J Radiol 82:1444–1452

    PubMed  Article  Google Scholar 

  3. 3.

    Schmidt GP, Reiser MF, Baur-Melnyk A (2007) Whole-body imaging of the musculoskeletal system: the value of MR imaging. Skelet Radiol 36:1109–1119

    Article  Google Scholar 

  4. 4.

    Padhani AR, van Ree K, Collins DJ, D'Sa S, Makris A (2013) Assessing the relation between bone marrow signal intensity and apparent diffusion coefficient in diffusion-weighted MRI. AJR Am J Roentgenol 200:163–170

    PubMed  Article  Google Scholar 

  5. 5.

    Khoo MM, Tyler PA, Saifuddin A, Padhani AR (2011) Diffusion-weighted imaging (DWI) in musculoskeletal MRI: a critical review. Skelet Radiol 40:665–681

    Article  Google Scholar 

  6. 6.

    Petralia G, Thoeny HC (2010) DW-MRI of the urogenital tract: applications in oncology. Cancer Imaging 10 Spec no A:S112–S123

    PubMed  Article  CAS  Google Scholar 

  7. 7.

    Kitajima K, Takahashi S, Ueno Y et al (2013) Do apparent diffusion coefficient (ADC) values obtained using high b-values with a 3-T MRI correlate better than a transrectal ultrasound (TRUS)-guided biopsy with true Gleason scores obtained from radical prostatectomy specimens for patients with prostate cancer? Eur J Radiol 82:1219–1226

    PubMed  Article  Google Scholar 

  8. 8.

    Dietrich O, Biffar A, Reiser MF, Baur-Melnyk A (2009) Diffusion-weighted imaging of bone marrow. Semin Musculoskelet Radiol 13:134–144

    PubMed  Article  Google Scholar 

  9. 9.

    Messiou C, Collins DJ, Morgan VA, Desouza NM (2011) Optimising diffusion weighted MRI for imaging metastatic and myeloma bone disease and assessing reproducibility. Eur Radiol 21:1713–1718

    PubMed  Article  CAS  Google Scholar 

  10. 10.

    Padhani AR, Koh DM, Collins DJ (2011) Whole-body diffusion-weighted MR imaging in cancer: current status and research directions. Radiology 261:700–718

    PubMed  Article  Google Scholar 

  11. 11.

    Fenchel M, Konaktchieva M, Weisel K et al (2010) Early response assessment in patients with multiple myeloma during anti-angiogenic therapy using arterial spin labelling: first clinical results. Eur Radiol 20:2899–2906

    PubMed  Article  Google Scholar 

  12. 12.

    Messiou C, Giles S, Collins DJ et al (2012) Assessing response of myeloma bone disease with diffusion-weighted MRI. Br J Radiol 85:e1198–e1203

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  13. 13.

    Hillengass J, Bauerle T, Bartl R et al (2011) Diffusion-weighted imaging for non-invasive and quantitative monitoring of bone marrow infiltration in patients with monoclonal plasma cell disease: a comparative study with histology. Br J Haematol 153:721–728

    PubMed  Article  Google Scholar 

  14. 14.

    Hillengass J, Stieltjes B, Bauerle T et al (2011) Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging of bone marrow in healthy individuals. Acta Radiol 52:324–330

    PubMed  Article  Google Scholar 

  15. 15.

    International Myeloma Working G (2003) Criteria for the classification of monoclonal gammopathies, multiple myeloma and related disorders: a report of the International Myeloma Working Group. Br J Haematol 121:749–757

    Article  Google Scholar 

  16. 16.

    Landgren O, Korde N (2011) Multiple myeloma precursor disease: current clinical and epidemiological insights and future opportunities. Oncology (Williston Park) 25:589–590

    Google Scholar 

  17. 17.

    Landgren O, Waxman AJ (2010) Multiple myeloma precursor disease. Jama 304:2397–2404

    PubMed  Article  CAS  Google Scholar 

  18. 18.

    Narquin S, Ingrand P, Azais I et al (2013) Comparison of whole-body diffusion MRI and conventional radiological assessment in the staging of myeloma. Diagn Interv Imaging 94:629–636

    PubMed  Article  CAS  Google Scholar 

  19. 19.

    Koh DM (2010) Qualitative and quantitative analyses: image evaluation and interpretation. In: Koh DM, Thoeny HC (eds) Diffusion-weighted MR imaging applications in the body. Springer, Heidelberg, pp 33–47

    Chapter  Google Scholar 

  20. 20.

    Padhani AR, Khan AA (2010) Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy. Target Oncol 5:39–52

    PubMed  Article  Google Scholar 

  21. 21.

    Landgren O (2010) Monoclonal gammopathy of undetermined significance and smoldering myeloma: new insights into pathophysiology and epidemiology. Hematol Am Soc Hematol Educ Program 2010:295–302

    Article  Google Scholar 

  22. 22.

    Silva JR Jr, Hayashi D, Yonenaga T et al (2013) MRI of bone marrow abnormalities in hematological malignancies. Diagn Interv Radiol 19:393–399

    PubMed  Google Scholar 

  23. 23.

    Herrmann J, Krstin N, Schoennagel BP et al (2012) Age-related distribution of vertebral bone-marrow diffusivity. Eur J Radiol 81:4046–4049

    PubMed  Article  Google Scholar 

  24. 24.

    Savvopoulou V, Maris TG, Vlahos L, Moulopoulos LA (2008) Differences in perfusion parameters between upper and lower lumbar vertebral segments with dynamic contrast-enhanced MRI (DCE MRI). Eur Radiol 18:1876–1883

    PubMed  Article  Google Scholar 

  25. 25.

    Nakanishi K, Gutzeit A (2010) Evaluation of malignant bone disease using DW-MRI. In: Koh DM, Thoeny HC (eds) Diffusion-weighted MR imaging applications in the body. Springer, Heidelberg, pp 207–226

    Chapter  Google Scholar 

  26. 26.

    Vande Berg BC, Malghem J, Lecouvet FE, Maldague B (1998) Magnetic resonance imaging of the normal bone marrow. Skelet Radiol 27:471–483

    Article  CAS  Google Scholar 

  27. 27.

    Lecouvet FE, Larbi A, Pasoglou V et al (2013) MRI for response assessment in metastatic bone disease. Eur Radiol 23:1986–1997

    PubMed  Article  CAS  Google Scholar 

  28. 28.

    Nonomura Y, Yasumoto M, Yoshimura R et al (2001) Relationship between bone marrow cellularity and apparent diffusion coefficient. J Magn Reson Imaging 13:757–760

    PubMed  Article  CAS  Google Scholar 

  29. 29.

    Padhani AR, Gogbashian A (2011) Bony metastases: assessing response to therapy with whole-body diffusion MRI. Cancer Imaging 11 Spec No A:S129–S145

    PubMed  Article  CAS  Google Scholar 

Download references

Acknowledgments

The scientific guarantor of this publication is Koenraad Verstraete. 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. The authors state that this work has not received any funding. One of the authors has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Some study subjects or cohorts have been previously reported in Euro J Radiol, A correlation was made between data of conventional whole-body MRI and dynamic contrast-enhanced MRI. Methodology: retrospective, diagnostic or prognostic study/observational, performed at one institution.

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Correspondence to Julie C. Dutoit.

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Dutoit, J.C., Vanderkerken, M.A., Anthonissen, J. et al. The diagnostic value of SE MRI and DWI of the spine in patients with monoclonal gammopathy of undetermined significance, smouldering myeloma and multiple myeloma. Eur Radiol 24, 2754–2765 (2014). https://doi.org/10.1007/s00330-014-3324-5

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Keywords

  • Diffusion-weighted imaging
  • Magnetic resonance imaging
  • Multiple myeloma
  • Monoclonal gammopathy of undetermined significance
  • Diagnosis