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Whole-body MRI, dynamic contrast-enhanced MRI, and diffusion-weighted imaging for the staging of multiple myeloma

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Abstract

Magnetic resonance imaging (MRI) is the most sensitive imaging technique for the detection of bone marrow infiltration, and has therefore recently been included in the new diagnostic myeloma criteria, as proposed by the International Myeloma Working Group. Nevertheless, conventional MRI only provides anatomical information and is therefore only of limited use in the response assessment of patients with multiple myeloma. The additional information from functional MRI techniques, such as diffusion-weighted imaging and dynamic contrast-enhanced MRI, can improve the detection rate of bone marrow infiltration and the assessment of response. This can further enhance the sensitivity and specificity of MRI in the staging of multiple myeloma patients. This article provides an overview of the technical aspects of conventional and functional MRI techniques with practical recommendations. It reviews the diagnostic performance, prognostic value, and role in therapy assessment in multiple myeloma and its precursor stages.

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Abbreviations

18F-FDG PET:

18F-fluoro-deoxyglucose positron emission tomography

ADC:

Apparent diffusion coefficient

DCE:

Dynamic contrast-enhanced

DWI:

Diffusion-weighted imaging

EPI:

Echoplanar imaging

fs:

Fat-suppressed

IMWG:

International Myeloma Working Group

MGUS:

Monoclonal gammopathy of undetermined significance

MDCT:

Multidetector computed tomography

MM:

Multiple myeloma

MVD:

Microvascular density

SI:

Signal intensity

SMM:

Smoldering multiple myeloma

TIC:

Time-intensity curve

References

  1. Durie BG, Salmon SE. A clinical staging system for multiple myeloma. Correlation of measured myeloma cell mass with presenting clinical features, response to treatment, and survival. Cancer. 1975;36(3):842–54.

    Article  CAS  PubMed  Google Scholar 

  2. Engelhardt M, Kleber M, Frydrychowicz A, et al. Superiority of magnetic resonance imaging over conventional radiographs in multiple myeloma. Anticancer Res. 2009;29(11):4745–50.

    PubMed  Google Scholar 

  3. Winterbottom AP, Shaw AS. Imaging patients with myeloma. Clin Radiol. 2009;64(1):1–11.

    Article  CAS  PubMed  Google Scholar 

  4. Gleeson TG, Moriarty J, Shortt CP, et al. Accuracy of whole-body low-dose multidetector CT (WBLDCT) versus skeletal survey in the detection of myelomatous lesions, and correlation of disease distribution with whole-body MRI (WBMRI). Skeletal Radiol. 2009;38(3):225–36.

    Article  CAS  PubMed  Google Scholar 

  5. Terpos E, Moulopoulos LA, Dimopoulos MA. Advances in imaging and the management of myeloma bone disease. J Clin Oncol. 2011;29(14):1907–15.

    Article  PubMed  Google Scholar 

  6. Mahnken AH, Wildberger JE, Gehbauer G, et al. Multidetector CT of the spine in multiple myeloma: comparison with MR imaging and radiography. AJR Am J Roentgenol. 2002;178(6):1429–36.

    Article  CAS  PubMed  Google Scholar 

  7. Wolf MB, Murray F, Kilk K, et al. Sensitivity of whole-body CT and MRI versus projection radiography in the detection of osteolyses in patients with monoclonal plasma cell disease. Eur J Radiol. 2014;83(7):1222–30.

    Article  PubMed  Google Scholar 

  8. Baur-Melnyk A, Buhmann S, Becker C, et al. Whole-body MRI versus whole-body MDCT for staging of multiple myeloma. AJR Am J Roentgenol. 2008;190(4):1097–104.

    Article  PubMed  Google Scholar 

  9. Durie BG. The role of anatomic and functional staging in myeloma: description of Durie/Salmon plus staging system. Eur J Cancer. 2006;42(11):1539–43.

    Article  PubMed  Google Scholar 

  10. Mena E, Choyke P, Tan E, Landgren O, Kurdziel K. Molecular imaging in myeloma precursor disease. Semin Hematol. 2011;48(1):22–31.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Durie BG, Harousseau JL, Miguel JS, et al. International uniform response criteria for multiple myeloma. Leukemia. 2006;20(9):1467–73.

    Article  CAS  PubMed  Google Scholar 

  12. Adam Z, Bolcak K, Stanicek J, et al. Fluorodeoxyglucose positron emission tomography in multiple myeloma, solitary plasmocytoma and monoclonal gammapathy of unknown significance. Neoplasma. 2007;54(6):536–40.

    CAS  PubMed  Google Scholar 

  13. Lutje S, de Rooy JW, Croockewit S, Koedam E, Oyen WJ, Raymakers RA. Role of radiography, MRI and FDG-PET/CT in diagnosing, staging and therapeutical evaluation of patients with multiple myeloma. Ann Hematol. 2009;88(12):1161–8.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Zamagni E, Patriarca F, Nanni C, et al. Prognostic relevance of 18-F FDG PET/CT in newly diagnosed multiple myeloma patients treated with up-front autologous transplantation. Blood. 2011;118(23):5989–95.

    Article  CAS  PubMed  Google Scholar 

  15. Zamagni E, Nanni C, Patriarca F, et al. A prospective comparison of 18F-fluorodeoxyglucose positron emission tomography-computed tomography, magnetic resonance imaging and whole-body planar radiographs in the assessment of bone disease in newly diagnosed multiple myeloma. Haematologica. 2007;92(1):50–5.

    Article  PubMed  Google Scholar 

  16. Derlin T, Weber C, Habermann CR, et al. 18F-FDG PET/CT for detection and localization of residual or recurrent disease in patients with multiple myeloma after stem cell transplantation. Eur J Nucl Med Mol Imaging. 2012;39(3):493–500.

    Article  PubMed  Google Scholar 

  17. Spinnato P, Bazzocchi A, Brioli A, et al. Contrast enhanced MRI and (1)(8)F-FDG PET-CT in the assessment of multiple myeloma: a comparison of results in different phases of the disease. Eur J Radiol. 2012;81(12):4013–8.

    Article  CAS  PubMed  Google Scholar 

  18. Shortt CP, Gleeson TG, Breen KA, et al. Whole-body MRI versus PET in assessment of multiple myeloma disease activity. Am J Roentgenol 2009;192:980–6.

  19. Walker RC, Brown TL, Jones-Jackson LB, De Blanche L, Bartel T. Imaging of multiple myeloma and related plasma cell dyscrasias. J Nucl Med. 2012;53(7):1091–101.

    Article  PubMed  Google Scholar 

  20. Hillengass J, Landgren O. Challenges and opportunities of novel imaging techniques in monoclonal plasma cell disorders: imaging “early myeloma”. Leuk Lymphoma. 2013;54(7):1355–63.

    Article  PubMed  Google Scholar 

  21. Schmidt GP, Reiser MF, Baur-Melnyk A. Whole-body MRI for the staging and follow-up of patients with metastasis. Eur J Radiol. 2009;70(3):393–400.

    Article  PubMed  Google Scholar 

  22. Dimopoulos MA, Hillengass J, Usmani S, et al. Role of magnetic resonance imaging in the management of patients with multiple myeloma: a consensus statement. J Clin Oncol. 2015;33(6):657–64.

    Article  PubMed  Google Scholar 

  23. Lecouvet FE, Larbi A, Pasoglou V, et al. MRI for response assessment in metastatic bone disease. Eur Radiol. 2013;23(7):1986–97.

    Article  CAS  PubMed  Google Scholar 

  24. Padhani AR, Khan AA. Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy. Target Oncol. 2010;5(1):39–52.

    Article  PubMed  Google Scholar 

  25. Caers J, Withofs N, Hillengass J, et al. The role of positron emission tomography-computed tomography and magnetic resonance imaging in diagnosis and follow up of multiple myeloma. Haematologica. 2014;99(4):629–37.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Dutoit JC, Vanderkerken MA, Verstraete KL. 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. 2013;82(9):1444–52.

    Article  PubMed  Google Scholar 

  27. Dutoit JC, Vanderkerken MA, Anthonissen J, Dochy F, Verstraete KL. 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. 2014;24(11):2754–65.

    Article  PubMed  Google Scholar 

  28. Dutoit JC, Claus E, Offner F, Noens L, Delanghe J, Verstraete KL. Combined evaluation of conventional MRI, dynamic contrast-enhanced MRI and diffusion weighted imaging for response evaluation of patients with multiple myeloma. Eur J Radiol. 2016;85(2):373–82.

    Article  PubMed  Google Scholar 

  29. Vande Berg BC, Malghem J, Lecouvet FE, Maldague B. Magnetic resonance imaging of the normal bone marrow. Skeletal Radiol. 1998;27(9):471–83.

    Article  CAS  PubMed  Google Scholar 

  30. Lecouvet FE. Whole-body MR imaging: musculoskeletal applications. Radiology. 2016;279(2):345–65.

  31. Vogler 3rd JB, Murphy WA. Bone marrow imaging. Radiology. 1988;168(3):679–93.

    Article  PubMed  Google Scholar 

  32. Shah LM, Hanrahan CJ. MRI of spinal bone marrow. I. Techniques and normal age-related appearances. AJR Am J Roentgenol. 2011;197(6):1298–308.

    Article  PubMed  Google Scholar 

  33. Bier G, Kloth C, Schabel C, Bongers M, Nikolaou K, Horger M. Vertebral lesion distribution in multiple myeloma—assessed by reduced-dose whole-body MDCT. Skeletal Radiol. 2016;45(1):127–33.

    Article  PubMed  Google Scholar 

  34. Hillengass J, Fechtner K, Weber MA, et al. Prognostic significance of focal lesions in whole-body magnetic resonance imaging in patients with asymptomatic multiple myeloma. J Clin Oncol. 2010;28(9):1606–10.

    Article  PubMed  Google Scholar 

  35. Vande Berg BC, Michaux L, Lecouvet FE, et al. Nonmyelomatous monoclonal gammopathy: correlation of bone marrow MR images with laboratory findings and spontaneous clinical outcome. Radiology. 1997;202(1):247–51.

    Article  CAS  PubMed  Google Scholar 

  36. Hillengass J, Weber MA, Kilk K, et al. Prognostic significance of whole-body MRI in patients with monoclonal gammopathy of undetermined significance. Leukemia. 2014;28(1):174–8.

    Article  CAS  PubMed  Google Scholar 

  37. Merz M, Hielscher T, Wagner B, et al. Predictive value of longitudinal whole-body magnetic resonance imaging in patients with smoldering multiple myeloma. Leukemia. 2014;28(9):1902–8.

    Article  CAS  PubMed  Google Scholar 

  38. Silva Jr JR, Hayashi D, Yonenaga T, et al. MRI of bone marrow abnormalities in hematological malignancies. Diagn Interv Radiol. 2013;19(5):393–9.

    PubMed  Google Scholar 

  39. Schmidt GP, Reiser MF, Baur-Melnyk A. Whole-body imaging of the musculoskeletal system: the value of MR imaging. Skeletal Radiol. 2007;36(12):1109–19.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Baur A, Stabler A, Bartl R, Lamerz R, Reiser M. Infiltration patterns of plasmacytomas in magnetic resonance tomography. Rofo. 1996;164(6):457–63.

    Article  CAS  PubMed  Google Scholar 

  41. Baur-Melnyk A, Buhmann S, Durr HR, Reiser M. Role of MRI for the diagnosis and prognosis of multiple myeloma. Eur J Radiol. 2005;55(1):56–63.

    Article  PubMed  Google Scholar 

  42. Stabler A, Baur A, Bartl R, Munker R, Lamerz R, Reiser MF. Contrast enhancement and quantitative signal analysis in MR imaging of multiple myeloma: assessment of focal and diffuse growth patterns in marrow correlated with biopsies and survival rates. AJR Am J Roentgenol. 1996;167(4):1029–36.

    Article  CAS  PubMed  Google Scholar 

  43. Vande Berg BC, Michaux L, Scheiff JM, et al. Sequential quantitative MR analysis of bone marrow: differences during treatment of lymphoid versus myeloid leukemia. Radiology. 1996;201(2):519–23.

    Article  CAS  PubMed  Google Scholar 

  44. Moulopoulos LA, Dimopoulos MA. Magnetic resonance imaging of the bone marrow in hematologic malignancies. Blood. 1997;90(6):2127–47.

    CAS  PubMed  Google Scholar 

  45. Dimopoulos MA, Moulopoulos A, Smith T, Delasalle KB, Alexanian R. Risk of disease progression in asymptomatic multiple myeloma. Am J Med. 1993;94(1):57–61.

    Article  CAS  PubMed  Google Scholar 

  46. Mariette X, Zagdanski AM, Guermazi A, et al. Prognostic value of vertebral lesions detected by magnetic resonance imaging in patients with stage I multiple myeloma. Br J Haematol. 1999;104(4):723–9.

    Article  CAS  PubMed  Google Scholar 

  47. Weber DM, Dimopoulos MA, Moulopoulos LA, Delasalle KB, Smith T, Alexanian R. Prognostic features of asymptomatic multiple myeloma. Br J Haematol. 1997;97(4):810–4.

    Article  CAS  PubMed  Google Scholar 

  48. Walker R, Barlogie B, Haessler J, et al. Magnetic resonance imaging in multiple myeloma: diagnostic and clinical implications. J Clin Oncol. 2007;25(9):1121–8.

    Article  PubMed  Google Scholar 

  49. Moulopoulos LA, Dimopoulos MA, Christoulas D, et al. Diffuse MRI marrow pattern correlates with increased angiogenesis, advanced disease features and poor prognosis in newly diagnosed myeloma treated with novel agents. Leukemia. 2010;24(6):1206–12.

    Article  CAS  PubMed  Google Scholar 

  50. Moulopoulos LA, Dimopoulos MA, Kastritis E, et al. Diffuse pattern of bone marrow involvement on magnetic resonance imaging is associated with high risk cytogenetics and poor outcome in newly diagnosed, symptomatic patients with multiple myeloma: a single center experience on 228 patients. Am J Hematol. 2012;87(9):861–4.

    Article  PubMed  Google Scholar 

  51. Mai EK, Hielscher T, Kloth JK, et al. Association between magnetic resonance imaging patterns and baseline disease features in multiple myeloma: analyzing surrogates of tumour mass and biology. Eur Radiol. 2016;26(11):3939–48.

    Article  PubMed  Google Scholar 

  52. Yankelevitz DF, Henschke CI, Knapp PH, Nisce L, Yi Y, Cahill P. Effect of radiation therapy on thoracic and lumbar bone marrow: evaluation with MR imaging. AJR Am J Roentgenol. 1991;157(1):87–92.

    Article  CAS  PubMed  Google Scholar 

  53. Stevens SK, Moore SG, Kaplan ID. Early and late bone-marrow changes after irradiation: MR evaluation. AJR Am J Roentgenol. 1990;154(4):745–50.

    Article  CAS  PubMed  Google Scholar 

  54. Daldrup-Link HE, Henning T, Link TM. MR imaging of therapy-induced changes of bone marrow. Eur Radiol. 2007;17(3):743–61.

    Article  PubMed  Google Scholar 

  55. Lecouvet FE, Dechambre S, Malghem J, Ferrant A, Vande Berg BC, Maldague B. Bone marrow transplantation in patients with multiple myeloma: prognostic significance of MR imaging. AJR Am J Roentgenol. 2001;176(1):91–6.

    Article  CAS  PubMed  Google Scholar 

  56. Hillengass J, Ayyaz S, Kilk K, et al. Changes in magnetic resonance imaging before and after autologous stem cell transplantation correlate with response and survival in multiple myeloma. Haematologica. 2012;97(11):1757–60.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Vande Berg BC, Lecouvet FE, Galant C, Maldague BE, Malghem J. Normal variants and frequent marrow alterations that simulate bone marrow lesions at MR imaging. Radiol Clin North Am. 2005;43(4):761–70.

    Article  PubMed  Google Scholar 

  58. Hartman RP, Sundaram M, Okuno SH, Sim FH. Effect of granulocyte-stimulating factors on marrow of adult patients with musculoskeletal malignancies: incidence and MRI findings. AJR Am J Roentgenol. 2004;183(3):645–53.

    Article  PubMed  Google Scholar 

  59. Padhani AR, Koh DM. Diffusion MR imaging for monitoring of treatment response. Magn Reson Imaging Clin N Am. 2011;19(1):181–209.

    Article  PubMed  Google Scholar 

  60. Vaupel P, Kallinowski F, Okunieff P. Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review. Cancer Res. 1989;49(23):6449–65.

    CAS  PubMed  Google Scholar 

  61. Vacca A, Ribatti D, Roccaro AM, Ria R, Palermo L, Dammacco F. Bone marrow angiogenesis and plasma cell angiogenic and invasive potential in patients with active multiple myeloma. Acta Haematol. 2001;106(4):162–9.

    Article  CAS  PubMed  Google Scholar 

  62. Nosas-Garcia S, Moehler T, Wasser K, et al. Dynamic contrast-enhanced MRI for assessing the disease activity of multiple myeloma: a comparative study with histology and clinical markers. J Magn Reson Imaging. 2005;22(1):154–62.

    Article  PubMed  Google Scholar 

  63. Barrett T, Brechbiel M, Bernardo M, Choyke PL. MRI of tumor angiogenesis. J Magn Reson Imaging. 2007;26(2):235–49.

    Article  PubMed  Google Scholar 

  64. Merz M, Ritsch J, Kunz C, et al. Dynamic contrast-enhanced magnetic resonance imaging for assessment of antiangiogenic treatment effects in multiple myeloma. Clin Cancer Res. 2015;21(1):106–12.

    Article  CAS  PubMed  Google Scholar 

  65. Verstraete KL, Van der Woude HJ, Hogendoorn PC, De-Deene Y, Kunnen M, Bloem J. Dynamic contrast-enhanced MR imaging of musculoskeletal tumors: basic principles and clinical applications. J Magn Reson Imaging. 1996;6(2):311–21.

    Article  CAS  PubMed  Google Scholar 

  66. Verstraete KL, De Deene Y, Roels H, Dierick A, Uyttendaele D, Kunnen M. Benign and malignant musculoskeletal lesions: dynamic contrast-enhanced MR imaging--parametric “first-pass” images depict tissue vascularization and perfusion. Radiology. 1994;192(3):835–43.

    Article  CAS  PubMed  Google Scholar 

  67. Haase A. Snapshot FLASH MRI. Applications to T1, T2, and chemical-shift imaging. Magn Reson Med. 1990;13(1):77–89.

  68. Haase A, Matthaei D, Bartkowski R, Duhmke E, Leibfritz D. Inversion recovery snapshot FLASH MR imaging. J Comput Assist Tomogr. 1989;13(6):1036–40.

    Article  CAS  PubMed  Google Scholar 

  69. Verstraete KL, Vanzieleghem B, De Deene Y, et al. Static, dynamic and first-pass MR imaging of musculoskeletal lesions using gadodiamide injection. Acta Radiol. 1995;36(1):27–36.

    Article  CAS  PubMed  Google Scholar 

  70. Kormano M, Dean PB. Extravascular contrast material: the major component of contrast enhancement. Radiology. 1976;121(2):379–82.

    Article  CAS  PubMed  Google Scholar 

  71. Brasch RC. New directions in the development of MR imaging contrast media. Radiology. 1992;183(1):1–11.

    Article  CAS  PubMed  Google Scholar 

  72. Ross JS, Delamarter R, Hueftle MG, et al. Gadolinium-DTPA-enhanced MR imaging of the postoperative lumbar spine: time course and mechanism of enhancement. AJR Am J Roentgenol. 1989;152(4):825–34.

    Article  CAS  PubMed  Google Scholar 

  73. Erlemann R, Reiser MF, Peters PE, et al. Musculoskeletal neoplasms: static and dynamic Gd-DTPA--enhanced MR imaging. Radiology. 1989;171(3):767–73.

    Article  CAS  PubMed  Google Scholar 

  74. Breault SR, Heye T, Bashir MR, et al. Quantitative dynamic contrast-enhanced MRI of pelvic and lumbar bone marrow: effect of age and marrow fat content on pharmacokinetic parameter values. AJR Am J Roentgenol. 2013;200(3):W297–303.

    Article  PubMed  Google Scholar 

  75. Dutoit JC, Verstraete KL. MRI in multiple myeloma: a pictorial review of diagnostic and post-treatment findings. Insights Imaging. 2016;7(4):553–69.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Lavini C, de Jonge MC, van de Sande MG, Tak PP, Nederveen AJ, Maas M. Pixel-by-pixel analysis of DCE MRI curve patterns and an illustration of its application to the imaging of the musculoskeletal system. Magn Reson Imaging. 2007;25(5):604–12.

    Article  PubMed  Google Scholar 

  77. Hayes C, Padhani AR, Leach MO. Assessing changes in tumour vascular function using dynamic contrast-enhanced magnetic resonance imaging. NMR Biomed. 2002;15(2):154–63.

    Article  PubMed  Google Scholar 

  78. Padhani AR, Leach MO. Antivascular cancer treatments: functional assessments by dynamic contrast-enhanced magnetic resonance imaging. Abdom Imaging. 2005;30(3):324–41.

    Article  CAS  PubMed  Google Scholar 

  79. Garcia-Figueiras R, Padhani AR, Beer AJ, et al. Imaging of tumor angiogenesis for radiologists. I. Biological and technical basis. Curr Probl Diagn Radiol. 2015;44(5):407–24.

    Article  PubMed  Google Scholar 

  80. Brix G, Semmler W, Port R, Schad LR, Layer G, Lorenz WJ. Pharmacokinetic parameters in CNS Gd-DTPA enhanced MR imaging. J Comput Assist Tomogr. 1991;15(4):621–8.

    Article  CAS  PubMed  Google Scholar 

  81. Tofts PS. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging. 1997;7(1):91–101.

    Article  CAS  PubMed  Google Scholar 

  82. Brix G, Schreiber W, Hoffmann U, Guckel F, Hawighorst H, Knopp MV. Methodological approaches to quantitative evaluation of microcirculation in tissues with dynamic magnetic resonance tomography. Radiologe. 1997;37(6):470–80.

    Article  CAS  PubMed  Google Scholar 

  83. Turkbey B, Thomasson D, Pang Y, Bernardo M, Choyke P. The role of dynamic contrast-enhanced MRI in cancer diagnosis and treatment. Diagn Interv Radiol. 2010;16(3):186–92.

    PubMed  Google Scholar 

  84. Chen WT, Shih TT, Chen RC, et al. Vertebral bone marrow perfusion evaluated with dynamic contrast-enhanced MR imaging: significance of aging and sex. Radiology. 2001;220(1):213–8.

    Article  CAS  PubMed  Google Scholar 

  85. Hillengass J, Stieltjes B, Bauerle T, et al. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging of bone marrow in healthy individuals. Acta Radiol. 2011;52(3):324–30.

    Article  PubMed  Google Scholar 

  86. Montazel JL, Divine M, Lepage E, Kobeiter H, Breil S, Rahmouni A. Normal spinal bone marrow in adults: dynamic gadolinium-enhanced MR imaging. Radiology. 2003;229(3):703–9.

    Article  PubMed  Google Scholar 

  87. Baur A, Bartl R, Pellengahr C, Baltin V, Reiser M. Neovascularization of bone marrow in patients with diffuse multiple myeloma: a correlative study of magnetic resonance imaging and histopathologic findings. Cancer. 2004;101(11):2599–604.

    Article  PubMed  Google Scholar 

  88. Alyas F, Saifuddin A, Connell D. MR imaging evaluation of the bone marrow and marrow infiltrative disorders of the lumbar spine. Magn Reson Imaging Clin N Am. 2007;15(2):199–219. vi.

    Article  PubMed  Google Scholar 

  89. Savvopoulou V, Maris TG, Vlahos L, Moulopoulos LA. Differences in perfusion parameters between upper and lower lumbar vertebral segments with dynamic contrast-enhanced MRI (DCE MRI). Eur Radiol. 2008;18(9):1876–83.

    Article  PubMed  Google Scholar 

  90. Dwek JR, Shapiro F, Laor T, Barnewolt CE, Jaramillo D. Normal gadolinium-enhanced MR images of the developing appendicular skeleton.2. Epiphyseal and metaphyseal marrow. AJR Am J Roentgenol. 1997;169(1):191–6.

    Article  CAS  PubMed  Google Scholar 

  91. Hillengass J, Zechmann C, Bauerle T, et al. Dynamic contrast-enhanced magnetic resonance imaging identifies a subgroup of patients with asymptomatic monoclonal plasma cell disease and pathologic microcirculation. Clin Cancer Res. 2009;15(9):3118–25.

    Article  PubMed  Google Scholar 

  92. Rajkumar SV, Mesa RA, Fonseca R, et al. Bone marrow angiogenesis in 400 patients with monoclonal gammopathy of undetermined significance, multiple myeloma, and primary amyloidosis. Clin Cancer Res. 2002;8(7):2210–6.

    PubMed  Google Scholar 

  93. Hillengass J, Ritsch J, Merz M, et al. Increased microcirculation detected by dynamic contrast-enhanced magnetic resonance imaging is of prognostic significance in asymptomatic myeloma. Br J Haematol. 2016;174(1):127–35.

    Article  PubMed  Google Scholar 

  94. Jakob C, Sterz J, Zavrski I, et al. Angiogenesis in multiple myeloma. Eur J Cancer. 2006;42(11):1581–90.

    Article  CAS  PubMed  Google Scholar 

  95. Sezer O, Niemoller K, Eucker J, et al. Bone marrow microvessel density is a prognostic factor for survival in patients with multiple myeloma. Ann Hematol. 2000;79(10):574–7.

    Article  CAS  PubMed  Google Scholar 

  96. Rajkumar SV, Leong T, Roche PC, et al. Prognostic value of bone marrow angiogenesis in multiple myeloma. Clin Cancer Res. 2000;6(8):3111–6.

    CAS  PubMed  Google Scholar 

  97. Rana C, Sharma S, Agrawal V, Singh U. Bone marrow angiogenesis in multiple myeloma and its correlation with clinicopathological factors. Ann Hematol. 2010;89(8):789–94.

    Article  PubMed  Google Scholar 

  98. Moehler TM, Hawighorst H, Neben K, et al. Bone marrow microcirculation analysis in multiple myeloma by contrast-enhanced dynamic magnetic resonance imaging. Int J Cancer. 2001;93(6):862–8.

    Article  CAS  PubMed  Google Scholar 

  99. Zha Y, Li M, Yang J. Dynamic contrast enhanced magnetic resonance imaging of diffuse spinal bone marrow infiltration in patients with hematological malignancies. Korean J Radiol. 2010;11(2):187–94.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Hillengass J, Wasser K, Delorme S, et al. Lumbar bone marrow microcirculation measurements from dynamic contrast-enhanced magnetic resonance imaging is a predictor of event-free survival in progressive multiple myeloma. Clin Cancer Res. 2007;13(2 Pt 1):475–81.

    Article  PubMed  Google Scholar 

  101. Merz M, Moehler TM, Ritsch J, et al. Prognostic significance of increased bone marrow microcirculation in newly diagnosed multiple myeloma: results of a prospective DCE-MRI study. Eur Radiol. 2016;26(5):1404–11.

    Article  PubMed  Google Scholar 

  102. Lin C, Luciani A, Belhadj K, et al. Multiple myeloma treatment response assessment with whole-body dynamic contrast-enhanced MR imaging. Radiology. 2010;254(2):521–31.

    Article  PubMed  Google Scholar 

  103. Sezer O, Niemoller K, Jakob C, et al. Relationship between bone marrow angiogenesis and plasma cell infiltration and serum beta2-microglobulin levels in patients with multiple myeloma. Ann Hematol. 2001;80(10):598–601.

    Article  CAS  PubMed  Google Scholar 

  104. Oh HS, Choi JH, Park CK, et al. Comparison of microvessel density before and after peripheral blood stem cell transplantation in multiple myeloma patients and its clinical implications: multicenter trial. Int J Hematol. 2002;76(5):465–70.

    Article  PubMed  Google Scholar 

  105. Zwick S, Strecker R, Kiselev V, et al. Assessment of vascular remodeling under antiangiogenic therapy using DCE-MRI and vessel size imaging. J Magn Reson Imaging. 2009;29(5):1125–33.

    Article  PubMed  Google Scholar 

  106. Zechmann CM, Traine L, Meissner T, et al. Parametric histogram analysis of dynamic contrast-enhanced MRI in multiple myeloma: a technique to evaluate angiogenic response to therapy? Acad Radiol. 2012;19(1):100–8.

    Article  PubMed  Google Scholar 

  107. Otake S, Mayr NA, Ueda T, Magnotta VA, Yuh WT. Radiation-induced changes in MR signal intensity and contrast enhancement of lumbosacral vertebrae: do changes occur only inside the radiation therapy field? Radiology. 2002;222(1):179–83.

    Article  PubMed  Google Scholar 

  108. Baur A, Stabler A, Bartl R, Lamerz R, Scheidler J, Reiser M. MRI gadolinium enhancement of bone marrow: age-related changes in normals and in diffuse neoplastic infiltration. Skeletal Radiol. 1997;26(7):414–8.

    Article  CAS  PubMed  Google Scholar 

  109. Moulopoulos LA, Maris TG, Papanikolaou N, Panagi G, Vlahos L, Dimopoulos MA. Detection of malignant bone marrow involvement with dynamic contrast-enhanced magnetic resonance imaging. Ann Oncol. 2003;14(1):152–8.

    Article  CAS  PubMed  Google Scholar 

  110. Hillengass J, Stoll J, Zechmann CM, et al. The application of Gadopentate-Dimeneglumin has no impact on progression free and overall survival as well as renal function in patients with monoclonal plasma cell disorders if general precautions are taken. Eur Radiol. 2015;25(3):745–50.

    Article  CAS  PubMed  Google Scholar 

  111. Khoo MM, Tyler PA, Saifuddin A, Padhani AR. Diffusion-weighted imaging (DWI) in musculoskeletal MRI: a critical review. Skeletal Radiol. 2011;40(6):665–81.

    Article  PubMed  Google Scholar 

  112. Padhani AR, van Ree K, Collins DJ, D’Sa S, Makris A. Assessing the relation between bone marrow signal intensity and apparent diffusion coefficient in diffusion-weighted MRI. AJR Am J Roentgenol. 2013;200(1):163–70.

    Article  PubMed  Google Scholar 

  113. Messiou C, Kaiser M. Whole body diffusion weighted MRI: a new view of myeloma. Br J Haematol. 2015;171(1):29–37.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Messiou C, Collins DJ, Morgan VA, Desouza NM. Optimising diffusion weighted MRI for imaging metastatic and myeloma bone disease and assessing reproducibility. Eur Radiol. 2011;21(8):1713–8.

    Article  CAS  PubMed  Google Scholar 

  115. Padhani AR, Koh DM, Collins DJ. Whole-body diffusion-weighted MR imaging in cancer: current status and research directions. Radiology. 2011;261(3):700–18.

    Article  PubMed  Google Scholar 

  116. Messiou C, Giles S, Collins DJ, et al. Assessing response of myeloma bone disease with diffusion-weighted MRI. Br J Radiol. 2012;85(1020):e1198–203.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Koh DM. Qualitative and quantitative analyses: image evaluation and interpretation. In: Koh DM, Thoeny HC, eds. Diffusion-Weighted MR imaging: applications in the body. Springer Science and Business Media; 2010. p. 33-47.

  118. Messiou C, deSouza NM. Diffusion weighted magnetic resonance imaging of metastatic bone disease: a biomarker for treatment response monitoring. Cancer Biomark. 2010;6(1):21–32.

    Article  CAS  PubMed  Google Scholar 

  119. Nonomura Y, Yasumoto M, Yoshimura R, et al. Relationship between bone marrow cellularity and apparent diffusion coefficient. J Magn Reson Imaging. 2001;13(5):757–60.

    Article  CAS  PubMed  Google Scholar 

  120. Herneth AM, Friedrich K, Weidekamm C, et al. Diffusion weighted imaging of bone marrow pathologies. Eur J Radiol. 2005;55(1):74–83.

    Article  PubMed  Google Scholar 

  121. Herrmann J, Krstin N, Schoennagel BP, et al. Age-related distribution of vertebral bone-marrow diffusivity. Eur J Radiol. 2012;81(12):4046–9.

    Article  PubMed  Google Scholar 

  122. Dietrich O, Geith T, Reiser MF, et al. Diffusion imaging of the vertebral bone marrow. NMR Biomed. 2015. doi:10.1002/nbm.3333.

    Google Scholar 

  123. Hillengass J, Bauerle T, Bartl R, et al. 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. 2011;153(6):721–8.

    Article  PubMed  Google Scholar 

  124. Fenchel M, Konaktchieva M, Weisel K, et al. Early response assessment in patients with multiple myeloma during anti-angiogenic therapy using arterial spin labelling: first clinical results. Eur Radiol. 2010;20(12):2899–906.

    Article  PubMed  Google Scholar 

  125. Bonaffini PA, Ippolito D, Casiraghi A, Besostri V, Franzesi CT, Sironi S. Apparent diffusion coefficient maps integrated in whole-body MRI examination for the evaluation of tumor response to chemotherapy in patients with multiple myeloma. Acad Radiol. 2015;22(9):1163–71.

    Article  PubMed  Google Scholar 

  126. Horger M, Weisel K, Horger W, Mroue A, Fenchel M, Lichy M. Whole-body diffusion-weighted MRI with apparent diffusion coefficient mapping for early response monitoring in multiple myeloma: preliminary results. AJR Am J Roentgenol. 2011;196(6):W790–5.

    Article  PubMed  Google Scholar 

  127. Giles SL, Messiou C, Collins DJ, et al. Whole-body diffusion-weighted MR imaging for assessment of treatment response in myeloma. Radiology. 2014;271(3):785–94.

    Article  PubMed  Google Scholar 

  128. Pratt G, Bowcock S, Chantry A, et al. Time to redefine myeloma. Br J Haematol. 2015;171(1):1–10.

    Article  PubMed  Google Scholar 

  129. Bauerle T, Hillengass J, Fechtner K, et al. Multiple myeloma and monoclonal gammopathy of undetermined significance: importance of whole-body versus spinal MR imaging. Radiology. 2009;252(2):477–85.

    Article  PubMed  Google Scholar 

  130. Rajkumar SV, Dimopoulos MA, Palumbo A, et al. International myeloma working group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15(12):e538–48.

    Article  PubMed  Google Scholar 

  131. Lecouvet FE, Vande Berg BC, Michaux L, et al. Stage III multiple myeloma: clinical and prognostic value of spinal bone marrow MR imaging. Radiology. 1998;209(3):653–60.

    Article  CAS  PubMed  Google Scholar 

  132. Pawlyn C, Fowkes L, Otero SJ, et al. Whole-body diffusion-weighted MRI: a new gold standard for assessing disease burden in patients with multiple myeloma? Leukemia. 2016;30(6):1446–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Gertz MA. Advanced skeletal imaging redefines the management of plasma cell disorders. J Clin Oncol. 2015;33(6):537–9.

    Article  PubMed  Google Scholar 

  134. Dammacco F, Rubini G, Ferrari C, Vacca A, Racanelli V. 18F-FDG PET/CT: a review of diagnostic and prognostic features in multiple myeloma and related disorders. Clin Exp Med. 2015;15(1):1–18.

    Article  CAS  PubMed  Google Scholar 

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  1. Department of Radiology, Ghent University Hospital, MR -1 K12, De Pintelaan 185, 9000, Ghent, Belgium

    Julie C. Dutoit & Koenraad L. Verstraete

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  1. Julie C. Dutoit
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  2. Koenraad L. Verstraete
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Correspondence to Julie C. Dutoit.

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Dutoit, J.C., Verstraete, K.L. Whole-body MRI, dynamic contrast-enhanced MRI, and diffusion-weighted imaging for the staging of multiple myeloma. Skeletal Radiol 46, 733–750 (2017). https://doi.org/10.1007/s00256-017-2609-6

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