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Progress of modern imaging modalities in multiple myeloma

  • Progress in Hematology
  • Novel technologies and innovative treatments in multiple myeloma
  • Published:
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Abstract

Multiple myeloma (MM) is an incurable hematological malignancy, but treatment advances made in the last two decades have markedly improved its prognosis. Imaging has played a particularly important role in the management of myeloma. Whole-body low-dose computed tomography (WBLDCT) is replacing conventional skeletal survey by whole-body X-rays. In addition, magnetic resonance imaging (MRI) and positron-emission tomography/computed tomography (PET/CT) have become important imaging modalities not only for MM diagnosis but also for assessment of myeloma cell infiltration, extramedullary disease, treatment efficacy, and prognosis. However, there is room to improve their accuracy and specificity for assessment of treatment response, tumor volume, and residual disease. This review introduces novel diagnostic techniques, such as WBLDCT, MRI, and PET/CT, discusses their contribution to MM care, and lists areas for future research.

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References

  1. National Cancer Registry in Japan (2016–2018), Cancer Information Service, National Cancer Center, Japan.

  2. Terpos E, Berenson J, Raje N, Roodman GD. Management of bone disease in multiple myeloma. Expert Rev Hematol. 2014;7(1):113–25. https://doi.org/10.1586/17474086.2013.874943.

    Article  CAS  PubMed  Google Scholar 

  3. Healy CF, Murray JG, Eustace SJ, Madewell J, O’Gorman PJ, O’Sullivan P. Multiple myeloma: a review of imaging features and radiological techniques. Bone Marrow Res. 2011;2011: 583439. https://doi.org/10.1155/2011/583439.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Zamagni E, Tacchetti P, Cavo M. Imaging in multiple myeloma: how? When? Blood. 2019;133(7):644–51. https://doi.org/10.1182/blood-2018-08-825356.

    Article  CAS  PubMed  Google Scholar 

  5. Baffour FI, Glazebrook KN, Kumar SK, Broski SM. Role of imaging in multiple myeloma. Am J Hematol. 2020;95(8):966–77. https://doi.org/10.1002/ajh.25846.

    Article  PubMed  Google Scholar 

  6. Rajkumar SV, Dimopoulos MA, Palumbo A, Blade J, Merlini G, Mateos MV, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15(12):e538–48. https://doi.org/10.1016/s1470-2045(14)70442-5.

    Article  PubMed  Google Scholar 

  7. Dimopoulos MA, Hillengass J, Usmani S, Zamagni E, Lentzsch S, Davies FE, 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. https://doi.org/10.1200/jco.2014.57.9961.

    Article  PubMed  Google Scholar 

  8. Lecouvet FE, Vande Berg BC, Malghem J, Maldague BE. Magnetic resonance and computed tomography imaging in multiple myeloma. Semin Musculoskelet Radiol. 2001;5(1):43–55. https://doi.org/10.1055/s-2001-12920.

    Article  CAS  PubMed  Google Scholar 

  9. Kumar S, Paiva B, Anderson KC, Durie B, Landgren O, Moreau P, et al. International Myeloma Working Group consensus criteria for response and minimal residual disease assessment in multiple myeloma. Lancet Oncol. 2016;17(8):e328–46. https://doi.org/10.1016/s1470-2045(16)30206-6.

    Article  PubMed  Google Scholar 

  10. Hillengass J, Usmani S, Rajkumar SV, Durie BGM, Mateos MV, Lonial S, et al. International myeloma working group consensus recommendations on imaging in monoclonal plasma cell disorders. Lancet Oncol. 2019;20(6):e302–12. https://doi.org/10.1016/s1470-2045(19)30309-2.

    Article  PubMed  Google Scholar 

  11. Chantry A, Kazmi M, Barrington S, Goh V, Mulholland N, Streetly M, et al. Guidelines for the use of imaging in the management of patients with myeloma. Br J Haematol. 2017;178(3):380–93. https://doi.org/10.1111/bjh.14827.

    Article  PubMed  Google Scholar 

  12. Larson D, Kyle RA, Rajkumar SV. Prevalence and monitoring of oligosecretory myeloma. N Engl J Med. 2012;367(6):580–1. https://doi.org/10.1056/NEJMc1206740.

    Article  CAS  PubMed  Google Scholar 

  13. Horger M, Claussen CD, Bross-Bach U, Vonthein R, Trabold T, Heuschmid M, et al. Whole-body low-dose multidetector row-CT in the diagnosis of multiple myeloma: an alternative to conventional radiography. Eur J Radiol. 2005;54(2):289–97. https://doi.org/10.1016/j.ejrad.2004.04.015.

    Article  PubMed  Google Scholar 

  14. Horger M, Pereira P, Claussen CD, Kanz L, Vonthein R, Denecke B, et al. Hyperattenuating bone marrow abnormalities in myeloma patients using whole-body non-enhanced low-dose MDCT: correlation with haematological parameters. Br J Radiol. 2008;81(965):386–96. https://doi.org/10.1259/bjr/21850180.

    Article  CAS  PubMed  Google Scholar 

  15. Gleeson TG, Byrne B, Kenny P, Last J, Fitzpatrick P, O’Gorman P, et al. Image quality in low-dose multidetector computed tomography: a pilot study to assess feasibility and dose optimization in whole-body bone imaging. Can Assoc Radiol J. 2010;61(5):258–64. https://doi.org/10.1016/j.carj.2010.01.003.

    Article  PubMed  Google Scholar 

  16. Nishida Y, Matsue Y, Suehara Y, Fukumoto K, Fujisawa M, Takeuchi M, et al. Clinical and prognostic significance of bone marrow abnormalities in the appendicular skeleton detected by low-dose whole-body multidetector computed tomography in patients with multiple myeloma. Blood Cancer J. 2015;5(7): e329. https://doi.org/10.1038/bcj.2015.57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Matsue K, Kobayashi H, Matsue Y, Abe Y, Narita K, Kitadate A, et al. Prognostic significance of bone marrow abnormalities in the appendicular skeleton of patients with multiple myeloma. Blood Adv. 2018;2(9):1032–9. https://doi.org/10.1182/bloodadvances.2017014720.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Hillengass J, Moulopoulos LA, Delorme S, Koutoulidis V, Mosebach J, Hielscher T, et al. Whole-body computed tomography versus conventional skeletal survey in patients with multiple myeloma: a study of the International Myeloma Working Group. Blood Cancer J. 2017;7(8): e599-e. https://doi.org/10.1038/bcj.2017.78.

    Article  Google Scholar 

  19. Dutoit JC, Verstraete KL. MRI in multiple myeloma: a pictorial review of diagnostic and post-treatment findings. Insights Imaging. 2016;7(4):553–69. https://doi.org/10.1007/s13244-016-0492-7.

    Article  PubMed  PubMed Central  Google Scholar 

  20. 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. https://doi.org/10.2214/ajr.11.8185.

    Article  PubMed  Google Scholar 

  21. Costachescu D, Ionita I, Borsi EC, Potre O, Potre C, Navolan DB, et al. Whole-body diffusion-weighted magnetic resonance imaging and apparent diffusion coefficient values as prognostic factors in multiple myeloma. Exp Ther Med. 2021;22(2):827. https://doi.org/10.3892/etm.2021.10259.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Zhang L, Wang Q, Wu X, Zhao A, Feng J, Zhang H, et al. Baseline bone marrow ADC value of diffusion-weighted MRI: a potential independent predictor for progression and death in patients with newly diagnosed multiple myeloma. Eur Radiol. 2021;31(4):1843–52. https://doi.org/10.1007/s00330-020-07295-6.

    Article  PubMed  Google Scholar 

  23. Giles SL, Messiou C, Collins DJ, Morgan VA, Simpkin CJ, West S, et al. Whole-body diffusion-weighted MR imaging for assessment of treatment response in myeloma. Radiology. 2014;271(3):785–94. https://doi.org/10.1148/radiol.13131529.

    Article  PubMed  Google Scholar 

  24. Wang K, Lee E, Kenis S, Hallam S, Haroon A, Wan S, et al. Application of diffusion-weighted whole-body MRI for response monitoring in multiple myeloma after chemotherapy: a systematic review and meta-analysis. Eur Radiol. 2022. https://doi.org/10.1007/s00330-021-08311-z.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Messiou C, Giles S, Collins DJ, West S, Davies FE, Morgan GJ, et al. Assessing response of myeloma bone disease with diffusion-weighted MRI. Br J Radiol. 2012;85(1020):e1198–203. https://doi.org/10.1259/bjr/52759767.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Baur-Melnyk A, Buhmann S, Dürr HR, Reiser M. Role of MRI for the diagnosis and prognosis of multiple myeloma. Eur J Radiol. 2005;55(1):56–63. https://doi.org/10.1016/j.ejrad.2005.01.017.

    Article  PubMed  Google Scholar 

  27. Moulopoulos LA, Dimopoulos MA, Kastritis E, Christoulas D, Gkotzamanidou M, Roussou M, 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. https://doi.org/10.1002/ajh.23258.

    Article  PubMed  Google Scholar 

  28. Rasche L, Angtuaco EJ, Alpe TL, Gershner GH, McDonald JE, Samant RS, et al. The presence of large focal lesions is a strong independent prognostic factor in multiple myeloma. Blood. 2018;132(1):59–66. https://doi.org/10.1182/blood-2018-04-842880.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Rasche L, Kumar M, Gershner G, Samant R, Van Hemert R, Heidemeier A, et al. Lack of spleen signal on diffusion weighted MRI is associated with high tumor burden and poor prognosis in multiple myeloma: a link to extramedullary hematopoiesis? Theranostics. 2019;9(16):4756–63. https://doi.org/10.7150/thno.33289.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Terao T, Machida Y, Tateishi U, Tsushima T, Narita K, Ikeda D, et al. Association of loss of spleen visualization on whole-body diffusion-weighted imaging with prognosis and tumor burden in patients with multiple myeloma. Sci Rep. 2021;11(1):23978. https://doi.org/10.1038/s41598-021-03496-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. 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. https://doi.org/10.2214/ajr.176.1.1760091.

    Article  CAS  PubMed  Google Scholar 

  32. Hillengass J, Ayyaz S, Kilk K, Weber MA, Hielscher T, Shah R, 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. https://doi.org/10.3324/haematol.2012.065359.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Takasu M, Kondo S, Akiyama Y, Takahashi Y, Maeda S, Baba Y, et al. Assessment of early treatment response on MRI in multiple myeloma: comparative study of whole-body diffusion-weighted and lumbar spinal MRI. PLoS One. 2020;15(2): e0229607. https://doi.org/10.1371/journal.pone.0229607.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Terao T, Machida Y, Narita K, Kuzume A, Tabata R, Tsushima T, et al. Total diffusion volume in MRI vs. total lesion glycolysis in PET/CT for tumor volume evaluation of multiple myeloma. Eur Radiol. 2021;31(8):6136–44. https://doi.org/10.1007/s00330-021-07687-2.

    Article  CAS  PubMed  Google Scholar 

  35. Filho AGO, Carneiro BC, Pastore D, Silva IP, Yamashita SR, Consolo FD, et al. Whole-body imaging of multiple myeloma: diagnostic criteria. Radiographics. 2019;39(4):1077–97. https://doi.org/10.1148/rg.2019180096.

    Article  Google Scholar 

  36. Messiou C, Hillengass J, Delorme S, Lecouvet FE, Moulopoulos LA, Collins DJ, et al. Guidelines for acquisition, interpretation, and reporting of whole-body MRI in myeloma: myeloma response assessment and diagnosis system (MY-RADS). Radiology. 2019;291(1):5–13. https://doi.org/10.1148/radiol.2019181949.

    Article  PubMed  Google Scholar 

  37. Belotti A, Ribolla R, Cancelli V, Villanacci A, Angelini V, Chiarini M, et al. Predictive role of diffusion-weighted whole-body MRI (DW-MRI) imaging response according to MY-RADS criteria after autologous stem cell transplantation in patients with multiple myeloma and combined evaluation with MRD assessment by flow cytometry. Cancer Med. 2021;10(17):5859–65. https://doi.org/10.1002/cam4.4136.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Paschali A, Panagiotidis E, Triantafyllou T, Palaska V, Tsirou K, Verrou E, et al. A proposed index of diffuse bone marrow [18F]-FDG uptake and PET skeletal patterns correlate with myeloma prognostic markers, plasma cell morphology, and response to therapy. Eur J Nucl Med Mol Imaging. 2021;48(5):1487–97. https://doi.org/10.1007/s00259-020-05078-1.

    Article  CAS  PubMed  Google Scholar 

  39. Moreau P, Attal M, Caillot D, Macro M, Karlin L, Garderet L, et al. Prospective evaluation of magnetic resonance imaging and [(18)F]fluorodeoxyglucose positron emission tomography-computed tomography at diagnosis and before maintenance therapy in symptomatic patients with multiple myeloma included in the IFM/DFCI 2009 trial: results of the IMAJEM study. J Clin Oncol. 2017;35(25):2911–8. https://doi.org/10.1200/jco.2017.72.2975.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Michaud-Robert AV, Zamagni E, Carlier T, Bailly C, Jamet B, Touzeau C, et al. Glucose metabolism quantified by SUVmax on baseline FDG-PET/CT predicts survival in newly diagnosed multiple myeloma patients: combined harmonized analysis of two prospective phase III trials. Cancers (Basel). 2020;12(9):2532. https://doi.org/10.3390/cancers12092532.

    Article  CAS  Google Scholar 

  41. Moreau P, Zweegman S, Perrot A, Hulin C, Caillot D, Facon T, et al. Evaluation of the prognostic value of positron emission tomography-computed tomography (PET-CT) at diagnosis and follow-up in transplant-eligible newly diagnosed multiple myeloma (TE NDMM) patients treated in the phase 3 Cassiopeia study: results of the Cassiopet companion study. Blood. 2019;134(Suppl 1):692. https://doi.org/10.1182/blood-2019-123143.

    Article  Google Scholar 

  42. Zamagni E, Patriarca F, Nanni C, Zannetti B, Englaro E, Pezzi A, 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. https://doi.org/10.1182/blood-2011-06-361386.

    Article  CAS  PubMed  Google Scholar 

  43. Fonti R, Salvatore B, Quarantelli M, Sirignano C, Segreto S, Petruzziello F, et al. 18F-FDG PET/CT, 99mTc-MIBI, and MRI in evaluation of patients with multiple myeloma. J Nucl Med. 2008;49(2):195–200. https://doi.org/10.2967/jnumed.107.045641.

    Article  PubMed  Google Scholar 

  44. Rama S, Suh CH, Kim KW, Durieux JC, Ramaiya N, Tirumani SH. Comparative performance of whole body MRI and (18)F-FDG PET/CT in evaluation of response to treatment of multiple myeloma: meta-analysis and systematic review. AJR Am J Roentgenol. 2021. https://doi.org/10.2214/ajr.21.26381.

    Article  PubMed  Google Scholar 

  45. Lu YY, Chen JH, Lin WY, Liang JA, Wang HY, Tsai SC, et al. FDG PET or PET/CT for detecting intramedullary and extramedullary lesions in multiple myeloma: a systematic review and meta-analysis. Clin Nucl Med. 2012;37(9):833–7. https://doi.org/10.1097/RLU.0b013e31825b2071.

    Article  PubMed  Google Scholar 

  46. Usmani SZ, Mitchell A, Waheed S, Crowley J, Hoering A, Petty N, et al. Prognostic implications of serial 18-fluoro-deoxyglucose emission tomography in multiple myeloma treated with total therapy 3. Blood. 2013;121(10):1819–23. https://doi.org/10.1182/blood-2012-08-451690.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. McDonald JE, Kessler MM, Gardner MW, Buros AF, Ntambi JA, Waheed S, et al. Assessment of total lesion glycolysis by (18)F FDG PET/CT significantly improves prognostic value of GEP and ISS in myeloma. Clin Cancer Res. 2017;23(8):1981–7. https://doi.org/10.1158/1078-0432.Ccr-16-0235.

    Article  CAS  PubMed  Google Scholar 

  48. Abe Y, Narita K, Kobayashi H, Kitadate A, Takeuchi M, O’Uchi T, et al. Medullary abnormalities in appendicular skeletons detected with (18)F-FDG PET/CT predict an unfavorable prognosis in newly diagnosed multiple myeloma patients with high-risk factors. AJR Am J Roentgenol. 2019;213(4):918–24. https://doi.org/10.2214/ajr.19.21283.

    Article  PubMed  Google Scholar 

  49. Jung SH, Kim K, Kim JS, Kim SJ, Cheong JW, Kim SJ, et al. A prognostic scoring system for patients with multiple myeloma classified as stage II with the Revised International Staging System. Br J Haematol. 2018;181(5):707–10. https://doi.org/10.1111/bjh.14701.

    Article  PubMed  Google Scholar 

  50. Jung SH, Kwon SY, Min JJ, Bom HS, Ahn SY, Jung SY, et al. (18)F-FDG PET/CT is useful for determining survival outcomes of patients with multiple myeloma classified as stage II and III with the Revised International Staging System. Eur J Nucl Med Mol Imaging. 2019;46(1):107–15. https://doi.org/10.1007/s00259-018-4114-0.

    Article  PubMed  Google Scholar 

  51. Cho HJ, Jung SH, Jo JC, Lee YJ, Yoon SE, Park SS, et al. Development of a new risk stratification system for patients with newly diagnosed multiple myeloma using R-ISS and (18)F-FDG PET/CT. Blood Cancer J. 2021;11(12):190. https://doi.org/10.1038/s41408-021-00577-2.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Terao T, Machida Y, Tsushima T, Miura D, Narita K, Kitadate A, et al. Pre-treatment metabolic tumour volume and total lesion glycolysis are superior to conventional positron-emission tomography/computed tomography variables for outcome prediction in patients with newly diagnosed multiple myeloma in clinical practice. Br J Haematol. 2020;191(2):223–30. https://doi.org/10.1111/bjh.16633.

    Article  CAS  PubMed  Google Scholar 

  53. Furukawa Y, Kikuchi J. Molecular basis of clonal evolution in multiple myeloma. Int J Hematol. 2020;111(4):496–511. https://doi.org/10.1007/s12185-020-02829-6.

    Article  PubMed  Google Scholar 

  54. Rasche L, Chavan SS, Stephens OW, Patel PH, Tytarenko R, Ashby C, et al. Spatial genomic heterogeneity in multiple myeloma revealed by multi-region sequencing. Nat Commun. 2017;8(1):268. https://doi.org/10.1038/s41467-017-00296-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Terao T, Machida Y, Hirata K, Kuzume A, Tabata R, Tsushima T, et al. Prognostic impact of metabolic heterogeneity in patients with newly diagnosed multiple myeloma using 18F-FDG PET/CT. Clin Nucl Med. 2021;46(10):790–6. https://doi.org/10.1097/rlu.0000000000003773.

    Article  PubMed  Google Scholar 

  56. Rasche L, Angtuaco E, McDonald JE, Buros A, Stein C, Pawlyn C, et al. Low expression of hexokinase-2 is associated with false-negative FDG-positron emission tomography in multiple myeloma. Blood. 2017;130(1):30–4. https://doi.org/10.1182/blood-2017-03-774422.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Abe Y, Ikeda S, Kitadate A, Narita K, Kobayashi H, Miura D, et al. Low hexokinase-2 expression-associated false-negative (18)F-FDG PET/CT as a potential prognostic predictor in patients with multiple myeloma. Eur J Nucl Med Mol Imaging. 2019;46(6):1345–50. https://doi.org/10.1007/s00259-019-04312-9.

    Article  CAS  PubMed  Google Scholar 

  58. Wu F, Bernard S, Fayad LM, Ilaslan H, Messiou C, Moulopoulos LA, et al. Updates and ongoing challenges in imaging of multiple myeloma: AJR expert panel narrative review. AJR Am J Roentgenol. 2021;217(4):775–85. https://doi.org/10.2214/ajr.21.25878.

    Article  PubMed  Google Scholar 

  59. Bartel TB, Haessler J, Brown TL, Shaughnessy JD Jr, van Rhee F, Anaissie E, et al. F18-fluorodeoxyglucose positron emission tomography in the context of other imaging techniques and prognostic factors in multiple myeloma. Blood. 2009;114(10):2068–76. https://doi.org/10.1182/blood-2009-03-213280.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Korde N, Roschewski M, Zingone A, Kwok M, Manasanch EE, Bhutani M, et al. Treatment with carfilzomib-lenalidomide-dexamethasone with lenalidomide extension in patients with smoldering or newly diagnosed multiple myeloma. JAMA Oncol. 2015;1(6):746–54. https://doi.org/10.1001/jamaoncol.2015.2010.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Zamagni E, Nanni C, Mancuso K, Tacchetti P, Pezzi A, Pantani L, et al. PET/CT improves the definition of complete response and allows to detect otherwise unidentifiable skeletal progression in multiple myeloma. Clin Cancer Res. 2015;21(19):4384–90. https://doi.org/10.1158/1078-0432.Ccr-15-0396.

    Article  CAS  PubMed  Google Scholar 

  62. Cheson BD, Fisher RI, Barrington SF, Cavalli F, Schwartz LH, Zucca E, et al. Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification. J Clin Oncol. 2014;32(27):3059–68. https://doi.org/10.1200/jco.2013.54.8800.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Itti E, Lin C, Dupuis J, Paone G, Capacchione D, Rahmouni A, et al. Prognostic value of interim 18F-FDG PET in patients with diffuse large B-Cell lymphoma: SUV-based assessment at 4 cycles of chemotherapy. J Nucl Med. 2009;50(4):527–33. https://doi.org/10.2967/jnumed.108.057703.

    Article  PubMed  Google Scholar 

  64. Kitadate A, Narita K, Fukumoto K, Terao T, Tsushima T, Kobayashi H, et al. Baseline total lesion glycolysis combined with interim positron emission tomography-computed tomography is a robust predictor of outcome in patients with peripheral T-cell lymphoma. Cancer Med. 2020;9(15):5509–18. https://doi.org/10.1002/cam4.3226.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Bailly C, Carlier T, Jamet B, Eugene T, Touzeau C, Attal M, et al. Interim PET analysis in first-line therapy of multiple myeloma: prognostic value of ΔSUVmax in the FDG-avid patients of the IMAJEM study. Clin Cancer Res. 2018;24(21):5219–24. https://doi.org/10.1158/1078-0432.Ccr-18-0741.

    Article  CAS  PubMed  Google Scholar 

  66. Zamagni E, Nanni C, Dozza L, Carlier T, Bailly C, Tacchetti P, et al. Standardization of (18)F-FDG-PET/CT according to Deauville criteria for metabolic complete response definition in newly diagnosed multiple myeloma. J Clin Oncol. 2021;39(2):116–25. https://doi.org/10.1200/jco.20.00386.

    Article  CAS  PubMed  Google Scholar 

  67. Nanni C, Versari A, Chauvie S, Bertone E, Bianchi A, Rensi M, et al. Interpretation criteria for FDG PET/CT in multiple myeloma (IMPeTUs): final results. IMPeTUs (Italian myeloma criteria for PET USe). Eur J Nucl Med Mol Imaging. 2018;45(5):712–9. https://doi.org/10.1007/s00259-017-3909-8.

    Article  PubMed  Google Scholar 

  68. Nanni C. PET-FDG: impetus. Cancers (Basel). 2020;12(4):1030. https://doi.org/10.3390/cancers12041030.

    Article  CAS  Google Scholar 

  69. Sachpekidis C, Merz M, Raab MS, Bertsch U, Weru V, Kopp-Schneider A, et al. The prognostic significance of [(18)F]FDG PET/CT in multiple myeloma according to novel interpretation criteria (IMPeTUs). EJNMMI Res. 2021;11(1):100. https://doi.org/10.1186/s13550-021-00846-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Spinnato P, Bazzocchi A, Brioli A, Nanni C, Zamagni E, Albisinni U, et al. Contrast enhanced MRI and 18F-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. https://doi.org/10.1016/j.ejrad.2012.06.028.

    Article  CAS  PubMed  Google Scholar 

  71. Rasche L, Alapat D, Kumar M, Gershner G, McDonald J, Wardell CP, et al. Combination of flow cytometry and functional imaging for monitoring of residual disease in myeloma. Leukemia. 2019;33(7):1713–22. https://doi.org/10.1038/s41375-018-0329-0.

    Article  CAS  PubMed  Google Scholar 

  72. Paiva B, Puig N, Cedena MT, Cordon L, Vidriales M-B, Burgos L, et al. Impact of next-generation flow (NGF) minimal residual disease (MRD) monitoring in multiple myeloma (MM): results from the Pethema/GEM2012 Trial. Blood. 2017;130(Suppl 1):905. https://doi.org/10.1182/blood.V130.Suppl_1.905.905.

    Article  Google Scholar 

  73. NCCN Guidelines Version 4.2022 Multiple Myeloma. https://www.nccn.org/professionals/physician_gls/pdf/myeloma.pdf. Accessed 21 Dec 2021.

  74. mSMART stratification for myeloma and risk-adapted therapy. https://www.msmart.org/mm-treatment-guidelines. Accessed 21 Dec 2021.

  75. Palumbo A, Bringhen S, Mateos MV, Larocca A, Facon T, Kumar SK, et al. Geriatric assessment predicts survival and toxicities in elderly myeloma patients: an International Myeloma Working Group report. Blood. 2015;125(13):2068–74. https://doi.org/10.1182/blood-2014-12-615187.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Fonti R, Larobina M, Del Vecchio S, De Luca S, Fabbricini R, Catalano L, et al. Metabolic tumor volume assessed by 18F-FDG PET/CT for the prediction of outcome in patients with multiple myeloma. J Nucl Med. 2012;53(12):1829–35. https://doi.org/10.2967/jnumed.112.106500.

    Article  CAS  PubMed  Google Scholar 

  77. Burns R, Mulé S, Blanc-Durand P, Tofighi M, Belhadj K, Zerbib P, et al. Optimization of whole-body 2-[(18)F]FDG-PET/MRI imaging protocol for the initial staging of patients with myeloma. Eur Radiol. 2021. https://doi.org/10.1007/s00330-021-08388-6.

    Article  PubMed  Google Scholar 

  78. Mulé S, Reizine E, Blanc-Durand P, Baranes L, Zerbib P, Burns R, et al. Whole-body functional MRI and PET/MRI in multiple myeloma. Cancers (Basel). 2020;12(11):3155. https://doi.org/10.3390/cancers12113155.

    Article  CAS  Google Scholar 

  79. Ulaner GA, Sobol NB, O’Donoghue JA, Kirov AS, Riedl CC, Min R, et al. CD38-targeted immuno-PET of multiple myeloma: from xenograft models to first-in-human imaging. Radiology. 2020;295(3):606–15. https://doi.org/10.1148/radiol.2020192621.

    Article  PubMed  Google Scholar 

  80. Matteucci F, Paganelli G, Martinelli G, Cerchione C. PET/CT in multiple myeloma: beyond FDG. Front Oncol. 2020;10: 622501. https://doi.org/10.3389/fonc.2020.622501.

    Article  PubMed  Google Scholar 

  81. Ozaki S, Handa H, Saitoh T, Murakami H, Itagaki M, Asaoku H, et al. Trends of survival in patients with multiple myeloma in Japan: a multicenter retrospective collaborative study of the Japanese Society of Myeloma. Blood Cancer J. 2015;5(9): e349. https://doi.org/10.1038/bcj.2015.79.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Anderson KC, Auclair D, Adam SJ, Agarwal A, Anderson M, Avet-Loiseau H, et al. Minimal residual disease in myeloma: application for clinical care and new drug registration. Clin Cancer Res. 2021. https://doi.org/10.1158/1078-0432.Ccr-21-1059.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Mithraprabhu S, Chen M, Savvidou I, Reale A, Spencer A. Liquid biopsy: an evolving paradigm for the biological characterisation of plasma cell disorders. Leukemia. 2021;35(10):2771–83. https://doi.org/10.1038/s41375-021-01339-6.

    Article  PubMed  Google Scholar 

  84. Yasui H, Kobayashi M, Sato K, Kondoh K, Ishida T, Kaito Y, et al. Circulating cell-free DNA in the peripheral blood plasma of patients is an informative biomarker for multiple myeloma relapse. Int J Clin Oncol. 2021;26(11):2142–50. https://doi.org/10.1007/s10147-021-01991-z.

    Article  CAS  PubMed  Google Scholar 

  85. Costa LJ, Chhabra S, Medvedova E, Dholaria BR, Schmidt TM, Godby KN, et al. Daratumumab, carfilzomib, lenalidomide, and dexamethasone with minimal residual disease response-adapted therapy in newly diagnosed multiple myeloma. J Clin Oncol. 2021. https://doi.org/10.1200/jco.21.01935.

    Article  PubMed  Google Scholar 

  86. Dimopoulos MA, Moreau P, Terpos E, Mateos MV, Zweegman S, Cook G, et al. Multiple myeloma: EHA-ESMO clinical practice guidelines for diagnosis, treatment and follow-up(†). Ann Oncol. 2021;32(3):309–22. https://doi.org/10.1016/j.annonc.2020.11.014.

    Article  CAS  PubMed  Google Scholar 

  87. Caers J, Garderet L, Kortüm KM, O’Dwyer ME, van de Donk N, Binder M, et al. European Myeloma Network recommendations on tools for the diagnosis and monitoring of multiple myeloma: what to use and when. Haematologica. 2018;103(11):1772–84. https://doi.org/10.3324/haematol.2018.189159.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. D’Agostino M, Lahuerta J-J, Wester R, Waage A, Bertsch U, Zamagni E, et al. A new risk stratification model (R2-ISS) in newly diagnosed multiple myeloma: analysis of mature data from 7077 patients collected by European Myeloma Network within harmony big data platform. Blood. 2020;136(Supplement 1):34–7. https://doi.org/10.1182/blood-2020-137021.

    Article  Google Scholar 

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Acknowledgements

We thank Dr. Youichi Machida (Department of Radiology, Kameda Medical Center, Kamogawa, Chiba, Japan) and Prof. Ukihide Tateishi (Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo, Japan) for routine clinical imaging evaluation and their valuable comments for this review. We also thank Editage (http://www.editage.jp) for their English language editing services. No funding was received for this study.

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  1. Division of Hematology/Oncology, Department of Internal Medicine, Kameda Medical Center, 929 Higashi-cho, Kamogawa, Chiba, 296-8602, Japan

    Toshiki Terao & Kosei Matsue

  2. Department of Hematology and Oncology, Okayama University Hospital, 2-5-1, Shikata-cho, Kita-ku, Okayama, 700-8558, Japan

    Toshiki Terao

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  1. Toshiki Terao
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Correspondence to Kosei Matsue.

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Terao, T., Matsue, K. Progress of modern imaging modalities in multiple myeloma. Int J Hematol 115, 778–789 (2022). https://doi.org/10.1007/s12185-022-03360-6

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