Advertisement

Skeletal Radiology

, Volume 47, Issue 3, pp 351–361 | Cite as

Comparison of qualitative and quantitative CT and MRI parameters for monitoring of longitudinal spine involvement in patients with multiple myeloma

  • M. Horger
  • J. Fritz
  • W. M. Thaiss
  • H. Ditt
  • K. Weisel
  • M. Haap
  • Christopher KlothEmail author
Scientific Article

Abstract

Purpose

To compare qualitative and quantitative computed tomography (CT) and magnetic resonance imaging (MRI) parameters for longitudinal disease monitoring of multiple myeloma (MM) of the axial skeleton.

Materials and methods

We included 31 consecutive patients (17 m; mean age 59.20 ± 8.08 years) with MM, who underwent all baseline (n = 31) and at least one or more (n = 47) follow-up examinations consisting of multi-parametric non-enhanced whole-body MRI (WBMRI) and non-enhanced whole-body reduced-dose thin-section MDCT (NEWBMDCT) between 06/2013 and 09/2016. We classified response according to qualitative CT criteria into progression (PD), stable(SD), partial/very good partial (PR/VGPR) and complete response(CR), grouping the latter three together for statistical analysis because CT cannot reliably assess PR and CR. Qualitative MR-response criteria were defined and grouped similarly to CT using longitudinal quantification of signal-intensity changes on T1w/STIR/ T2*w and calculating ADC-values. Standard of reference was the hematological laboratory (M-gradient).

Results

Hematological response categories were CR (14/47, 29.7%), PR (2/47, 4.2%), SD (16/47, 34.0%) and PD (15/47, 29.9%). Qualitative-CT-evaluation showed PD in 12/47 (25.5%) and SD/PR/VGPR/CR in 35/47 (74.5%) cases. These results were confirmed by quantitative-CT in all focal lytic lesions (p < 0.001). Quantitative-CT at sites with diffuse bone involvement showed significant increase of maximum bone attenuation (p < 0.001*) and significant decrease of minimal bone (p < 0.002*) in the SD/PR/VGPR/CR group. Qualitative MRI showed PD in 14/47 (29.7%) and SD/PR/VGPR/CR in 33/47 (70.3%). Quantitative MRI diagnosis showed a statistically significant decrease in signal intensity on short tau inversion recovery sequences (STIR) in bone marrow in patients with diffuse bone marrow involvement achieving SD/PR/VGPR/CR (p < 0.001*).

Conclusion

Imaging response monitoring using MRI is superior to CT only if qualitative parameters are used, whereas there was no definite benefit from using quantitative parameters with either CT or MRI.

Keywords

Multiple myeloma CT MRI Qualitative and quantitative analysis 

Notes

Compliance with ethical standards

Conflict of interest

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: HD is employed by a commercial company (Siemens AG Healthcare Sector). Since the manuscript is based on the application of a new software, the coauthor gave technical support, but he and his organization did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

JF received institutional research funds and speaker’s honorarium from Siemens Healthcare USA and is a scientic advisor of Siemens Healthcare USA. However this did not refer conflicts of interest with respect to the research, authorship, and/or publication of this article.

M.H. has contributed conceptually to the development of this post-processing software but has no financial interest to disclose. The author did not have conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplementary material

256_2017_2827_MOESM1_ESM.docx (15 kb)
Supplemental material Table 8 (DOCX 14 kb)

References

  1. 1.
    Palumbo A, Anderson K. Multiple myeloma. N Engl J Med. 2011;364(11):1046–60.CrossRefPubMedGoogle Scholar
  2. 2.
    Lin C, Luciani A, Belhadj K, Deux JF, Kuhnowski F, Maatouk M, et al. Multiple myeloma treatment response assessment with whole-body dynamic contrast-enhanced MR imaging. Radiology. 2010;254(2):521–31.CrossRefPubMedGoogle Scholar
  3. 3.
    Ferraro R, Agarwal A, Martin-Macintosh EL, Peller PJ, Subramaniam RM. MR imaging and PET/CT in diagnosis and management of multiple myeloma. Radiographics. 2015;35(2):438–54.CrossRefPubMedGoogle Scholar
  4. 4.
    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.CrossRefPubMedGoogle Scholar
  5. 5.
    Dupuis MM, Tuchman SA. Non-secretory multiple myeloma: from biology to clinical management. Onco Targets Ther. 2016;9:7583–90.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Anagnostopoulos A, Hamilos G, Zorzou MP, Grigoraki V, Anagnostou D, Dimopoulos MA. Discordant response or progression in patients with myeloma treated with thalidomide-based regimens. Leuk Lymphoma. 2004;45(1):113–6.CrossRefPubMedGoogle Scholar
  7. 7.
    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.CrossRefPubMedGoogle Scholar
  8. 8.
    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.CrossRefPubMedGoogle Scholar
  9. 9.
    Dutoit JC, Verstraete KL. MRI in multiple myeloma: a pictorial review of diagnostic and post-treatment findings. Insights Imaging. 2016;7(4):553–69.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Terpos E, Kleber M, Engelhardt M, Zweegman S, Gay F, Kastritis E, et al. European myeloma network guidelines for the management of multiple myeloma-related complications. Haematologica. 2015;100(10):1254–66.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Mangiacavalli S, Pezzatti S, Rossini F, Doni E, Cocito F, Bolis S, et al. Implemented myeloma management with whole-body low-dose CT scan: a real life experience. Leuk Lymphoma. 2016;57(7):1539–45.CrossRefPubMedGoogle Scholar
  12. 12.
    Sachpekidis C, Mosebach J, Freitag MT, Wilhelm T, Mai EK, Goldschmidt H, et al. Application of (18)F-FDG PET and diffusion weighted imaging (DWI) in multiple myeloma: comparison of functional imaging modalities. Am J Nucl Med Mol Imaging. 2015;5(5):479–92.PubMedPubMedCentralGoogle Scholar
  13. 13.
    Horger M, Kanz L, Denecke B, Vonthein R, Pereira P, Claussen CD, et al. The benefit of using whole-body, low-dose, nonenhanced, multidetector computed tomography for follow-up and therapy response monitoring in patients with multiple myeloma. Cancer. 2007;109(8):1617–26.CrossRefPubMedGoogle Scholar
  14. 14.
    Koutoulidis V, Fontara S, Terpos E, Zagouri F, Matsaridis D, Christoulas D, et al. Quantitative diffusion-weighted imaging of the bone marrow: an adjunct tool for the diagnosis of a diffuse MR imaging pattern in patients with multiple myeloma. Radiology. 2017;282(2):484–93.CrossRefPubMedGoogle Scholar
  15. 15.
    Rahmouni A, Divine M, Mathieu D, Golli M, Haioun C, Dao T, et al. MR appearance of multiple myeloma of the spine before and after treatment. AJR Am J Roentgenol. 1993;160(5):1053–7.CrossRefPubMedGoogle Scholar
  16. 16.
    Horger M, Thaiss WM, Ditt H, Weisel K, Fritz J, Nikolaou K et al. Improved MDCT monitoring of pelvic myeloma bone disease through the use of a novel longitudinal bone subtraction post-processing algorithm. Eur Radiol. 2017;27(7):2969–77.  https://doi.org/10.1007/s00330-016-4642-6.
  17. 17.
    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.CrossRefPubMedGoogle Scholar
  18. 18.
    Viola P, Wells W. Alignment by maximization of mutual information. Int J Comput Vis. 1997;24(2):137–54.CrossRefGoogle Scholar
  19. 19.
    Viola P, Jones M. Robust real-time face detection. Int J Comput Vis. 2004;57(2):137–54.CrossRefGoogle Scholar
  20. 20.
    Baur-Melnyk A, Buhmann S, Becker C, Schoenberg SO, Lang N, Bartl R, et al. Whole-body MRI versus whole-body MDCT for staging of multiple myeloma. AJR Am J Roentgenol. 2008;190(4):1097–104.CrossRefPubMedGoogle Scholar
  21. 21.
    Durie BG, Kyle RA, Belch A, Bensinger W, Blade J, Boccadoro M, et al. Myeloma management guidelines: a consensus report from the scientific advisors of the International Myeloma Foundation. Hematol J. 2003;4(6):379–98.CrossRefPubMedGoogle Scholar
  22. 22.
    International Myeloma Working Group. Criteria for the classification of monoclonal gammopathies, multiple myeloma and related disorders: a report of the International Myeloma Working Group. Br J Haematol. 2003;121(5):749–57.CrossRefGoogle Scholar
  23. 23.
    Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–74.CrossRefPubMedGoogle Scholar
  24. 24.
    Schabel C, Horger M, Kum S, Weisel K, Fritz J, Ioanoviciu SD, et al. Simplified response monitoring criteria for multiple myeloma in patients undergoing therapy with novel agents using computed tomography. Eur J Radiol. 2016;85(12):2195–9.CrossRefPubMedGoogle Scholar
  25. 25.
    Bannas P, Hentschel HB, Bley TA, Treszl A, Eulenburg C, Derlin T, et al. Diagnostic performance of whole-body MRI for the detection of persistent or relapsing disease in multiple myeloma after stem cell transplantation. Eur Radiol 2012;22(9):2007–12.Google Scholar
  26. 26.
    Khoo MM, Tyler PA, Saifuddin A, Padhani AR. Diffusion-weighted imaging (DWI) in musculoskeletal MRI: a critical review. Skelet Radiol. 2011;40(6):665–81.CrossRefGoogle Scholar
  27. 27.
    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.CrossRefPubMedGoogle Scholar

Copyright information

© ISS 2017

Authors and Affiliations

  • M. Horger
    • 1
  • J. Fritz
    • 2
  • W. M. Thaiss
    • 1
  • H. Ditt
    • 3
  • K. Weisel
    • 4
  • M. Haap
    • 5
  • Christopher Kloth
    • 6
    Email author
  1. 1.Department of Diagnostic and Interventional RadiologyEberhard-Karls-University TübingenTübingenGermany
  2. 2.Johns Hopkins University School of MedicineRussell H. Morgan Department of Radiology and Radiological ScienceBaltimoreUSA
  3. 3.Siemens AG Healthcare, Sector Imaging and Interventional RadiologyForchheimGermany
  4. 4.Department of Internal Medicine IIEberhard-Karls-University TübingenTübingenGermany
  5. 5.Department of Internal Medicine IVEberhard-Karls-University TübingenTübingen, Germany
  6. 6.Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmULMGermany

Personalised recommendations