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Whole-body diffusion-weighted magnetic resonance imaging with apparent diffusion coefficient mapping for staging patients with diffuse large B-cell lymphoma

  • Magnetic Resonance
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Abstract

Objective

To design a whole-body MR protocol using exclusively diffusion-weighted imaging (DWI) with respiratory gating and to assess its value for lesion detection and staging in patients with diffuse large B-cell lymphoma (DLBCL), with integrated FDG PET/CT as the reference standard.

Methods

Fifteen patients underwent both whole-body DWI (b = 50, 400, 800 s/mm2) and PET/CT for pretreatment staging. Lymph node and organ involvement were evaluated by qualitative and quantitative image analysis, including measurement of the mean apparent diffusion coefficient (ADC).

Results

A total of 296 lymph node regions in the 15 patients were analysed. Based on International Working Group size criteria alone, DWI findings matched PET/CT findings in 277 regions (94%) (kappa score = 0.85, P < 0.0001), yielding sensitivity and specificity for DWI lymph node involvement detection of 90% and 94%. Combining visual ADC analysis with size measurement increased DWI specificity to 100% with 81% sensitivity. For organ involvement, the two techniques agreed in all 20 recorded organs (100%). All involved organ lesions showed restricted diffusion. Ann Arbor stages agreed in 14 (93%) of the 15 patients.

Conclusion

Whole-body DWI with ADC analysis can potentially be used for lesion detection and staging in patients with DLBCL.

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References

  1. Cheson BD, Horning SJ, Coiffier B et al (1999) Report of an international workshop to standardize response criteria for non-Hodgkin's lymphomas. NCI Sponsored International Working Group. J Clin Oncol 17:1244–1253

    CAS  Google Scholar 

  2. Kwee TC, Kwee RM, Nievelstein RA (2008) Imaging in staging of malignant lymphoma: a systematic review. Blood 111:504–516

    Article  CAS  PubMed  Google Scholar 

  3. Moog F, Bangerter M, Diederichs CG et al (1997) Lymphoma: role of whole-body 2-deoxy-2-[F-18]fluoro-D-glucose (FDG) PET in nodal staging. Radiology 203:795–800

    CAS  PubMed  Google Scholar 

  4. Moog F, Bangerter M, Diederichs CG et al (1998) Extranodal malignant lymphoma: detection with FDG PET versus CT. Radiology 206:475–481

    CAS  PubMed  Google Scholar 

  5. Schaefer NG, Hany TF, Taverna C et al (2004) Non-Hodgkin lymphoma and Hodgkin disease: coregistered FDG PET and CT at staging and restaging—do we need contrast-enhanced CT? Radiology 232:823–829

    Article  PubMed  Google Scholar 

  6. Cheson BD, Pfistner B, Juweid ME et al (2007) Revised response criteria for malignant lymphoma. J Clin Oncol 25:579–586

    Article  PubMed  Google Scholar 

  7. Juweid ME, Stroobants S, Hoekstra OS et al (2007) Use of positron emission tomography for response assessment of lymphoma: consensus of the Imaging Subcommittee of International Harmonization Project in Lymphoma. J Clin Oncol 25:571–578

    Article  PubMed  Google Scholar 

  8. Schoder H, Noy A, Gonen M et al (2005) Intensity of 18fluorodeoxyglucose uptake in positron emission tomography distinguishes between indolent and aggressive non-Hodgkin's lymphoma. J Clin Oncol 23:4643–4651

    Article  PubMed  Google Scholar 

  9. Hutchings M, Loft A, Hansen M et al (2006) FDG-PET after two cycles of chemotherapy predicts treatment failure and progression-free survival in Hodgkin lymphoma. Blood 107:52–59

    Article  CAS  PubMed  Google Scholar 

  10. Lin C, Itti E, Haioun C et al (2007) Early 18F-FDG PET for prediction of prognosis in patients with diffuse large B-cell lymphoma: SUV-based assessment versus visual analysis. J Nucl Med 48:1626–1632

    Article  PubMed  Google Scholar 

  11. Itti E, Lin C, Dupuis J et al (2009) Prognostic value of interim 18F-FDG PET in patients with diffuse large B-cell lymphoma: SUV-based assessment at four cycles of chemotherapy. J Nucl Med 50:527–533

    Article  PubMed  Google Scholar 

  12. Sumi M, Ichikawa Y, Nakamura T (2007) Diagnostic ability of apparent diffusion coefficients for lymphomas and carcinomas in the pharynx. Eur Radiol 17:2631–2637

    Article  PubMed  Google Scholar 

  13. Nakayama T, Yoshimitsu K, Irie H et al (2004) Usefulness of the calculated apparent diffusion coefficient value in the differential diagnosis of retroperitoneal masses. J Magn Reson Imaging 20:735–742

    Article  PubMed  Google Scholar 

  14. King AD, Ahuja AT, Yeung DK et al (2007) Malignant cervical lymphadenopathy: diagnostic accuracy of diffusion-weighted MR imaging. Radiology 245:806–813

    Article  PubMed  Google Scholar 

  15. Toh CH, Castillo M, Wong AM et al (2008) Primary cerebral lymphoma and glioblastoma multiforme: differences in diffusion characteristics evaluated with diffusion tensor imaging. AJNR Am J Neuroradiol 29:471–475

    Article  PubMed  Google Scholar 

  16. Takahara T, Imai Y, Yamashita T et al (2004) Diffusion weighted whole body imaging with background body signal suppression (DWIBS): technical improvement using free breathing, STIR and high resolution 3D display. Radiat Med 22:275–282

    PubMed  Google Scholar 

  17. Thoeny HC, De Keyzer F (2007) Extracranial applications of diffusion-weighted magnetic resonance imaging. Eur Radiol 17:1385–1393

    Article  PubMed  Google Scholar 

  18. Koh DM, Collins DJ (2007) Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 188:1622–1635

    Article  PubMed  Google Scholar 

  19. Kwee TC, Takahara T, Ochiai R et al (2008) Diffusion-weighted whole-body imaging with background body signal suppression (DWIBS): features and potential applications in oncology. Eur Radiol 18:1937–1952

    Article  PubMed  Google Scholar 

  20. Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia (New York, NY 11:102–125

    CAS  Google Scholar 

  21. Lichy MP, Aschoff P, Plathow C et al (2007) Tumor detection by diffusion-weighted MRI and ADC-mapping–initial clinical experiences in comparison to PET-CT. Invest Radiol 42:605–613

    Article  PubMed  Google Scholar 

  22. Li S, Xue HD, Li J et al (2008) Application of whole body diffusion weighted MR imaging for diagnosis and staging of malignant lymphoma. Chin Med Sci J 23:138–144

    Article  CAS  PubMed  Google Scholar 

  23. Stecco A, Romano G, Negru M et al (2009) Whole-body diffusion-weighted magnetic resonance imaging in the staging of oncological patients: comparison with positron emission tomography computed tomography (PET-CT) in a pilot study. Radiol Med 114:1–17

    Article  CAS  PubMed  Google Scholar 

  24. Kwee TC, Quarles van Ufford HM, Beek FJ et al (2009) Whole-body MRI, including diffusion-weighted imaging, for the initial staging of malignant lymphoma: comparison to computed tomography. Invest Radiol 44:683–690

    Article  PubMed  Google Scholar 

  25. Rahmouni A, Luciani A, Itti E (2005) Quantitative CT analysis for assessing response in lymphoma (Cheson's criteria). Cancer Imaging 5(Spec No A):S102–S106

    Article  PubMed  Google Scholar 

  26. Picardi M, Soricelli A, Pane F et al (2009) Contrast-enhanced harmonic compound US of the spleen to increase staging accuracy in patients with Hodgkin lymphoma: a prospective study. Radiology 251:574–582

    Article  PubMed  Google Scholar 

  27. Koh DM, Takahara T, Imai Y et al (2007) Practical aspects of assessing tumors using clinical diffusion-weighted imaging in the body. Magn Reson Med Sci 6:211–224

    Article  PubMed  Google Scholar 

  28. Nguyen TD, de Rochefort L, Spincemaille P et al (2008) Effective motion-sensitizing magnetization preparation for black blood magnetic resonance imaging of the heart. J Magn Reson Imaging 28:1092–1100

    Article  PubMed  Google Scholar 

  29. Uto T, Takehara Y, Nakamura Y et al (2009) Higher sensitivity and specificity for diffusion-weighted imaging of malignant lung lesions without apparent diffusion coefficient quantification. Radiology 252:247–254

    Article  PubMed  Google Scholar 

  30. Bernstein MA, King KF, Zhou ZJ (2004) Handbook of MRI pulse sequences. Elsevier Academic Press, Amsterdam

    Google Scholar 

  31. Luciani A, Vignaud A, Cavet M et al (2008) Liver cirrhosis: intravoxel incoherent motion MR imaging–pilot study. Radiology 249:891–899

    Article  PubMed  Google Scholar 

  32. Kato H, Kanematsu M, Tanaka O et al (2009) Head and neck squamous cell carcinoma: usefulness of diffusion-weighted MR imaging in the prediction of a neoadjuvant therapeutic effect. Eur Radiol 19:103–109

    Article  PubMed  Google Scholar 

  33. Rini JN, Leonidas JC, Tomas MB et al (2003) 18F-FDG PET versus CT for evaluating the spleen during initial staging of lymphoma. J Nucl Med 44:1072–1074

    PubMed  Google Scholar 

  34. de Jong PA, van Ufford HM, Baarslag HJ et al (2009) CT and 18F-FDG PET for noninvasive detection of splenic involvement in patients with malignant lymphoma. AJR Am J Roentgenol 192:745–753

    Article  PubMed  Google Scholar 

  35. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174

    Article  CAS  PubMed  Google Scholar 

  36. Mori T, Nomori H, Ikeda K et al (2008) Diffusion-weighted magnetic resonance imaging for diagnosing malignant pulmonary nodules/masses: comparison with positron emission tomography. J Thorac Oncol 3:358–364

    Article  PubMed  Google Scholar 

  37. Ho KC, Lin G, Wang JJ et al (2009) Correlation of apparent diffusion coefficients measured by 3T diffusion-weighted MRI and SUV from FDG PET/CT in primary cervical cancer. Eur J Nucl Med Mol Imaging 36:200–208

    Article  PubMed  Google Scholar 

  38. Komori T, Narabayashi I, Matsumura K et al (2007) 2-[Fluorine-18]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography versus whole-body diffusion-weighted MRI for detection of malignant lesions: initial experience. Ann Nucl Med 21:209–215

    Article  PubMed  Google Scholar 

  39. Kwee TC, Takahara T, Koh DM et al (2008) Comparison and reproducibility of ADC measurements in breathhold, respiratory triggered, and free-breathing diffusion-weighted MR imaging of the liver. J Magn Reson Imaging 28:1141–1148

    Article  PubMed  Google Scholar 

  40. Wang J, Takashima S, Takayama F et al (2001) Head and neck lesions: characterization with diffusion-weighted echo-planar MR imaging. Radiology 220:621–630

    Article  CAS  PubMed  Google Scholar 

  41. Pileri SA, Dirnhofer S, Went P et al (2002) Diffuse large B-cell lymphoma: one or more entities? Present controversies and possible tools for its subclassification. Histopathology 41:482–509

    Article  CAS  PubMed  Google Scholar 

  42. Hunt KE, Reichard KK (2008) Diffuse large B-cell lymphoma. Arch Pathol Lab Med 132:118–124

    PubMed  Google Scholar 

  43. Vandecaveye V, De Keyzer F, Vander Poorten V et al (2009) Head and neck squamous cell carcinoma: value of diffusion-weighted MR imaging for nodal staging. Radiology 251:134–146

    Article  PubMed  Google Scholar 

  44. Reese TG, Heid O, Weisskoff RM et al (2003) Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo. Magn Reson Med 49:177–182

    Article  CAS  PubMed  Google Scholar 

  45. A predictive model for aggressive non-Hodgkin's lymphoma. The International Non-Hodgkin's Lymphoma Prognostic Factors Project. N Engl J Med 329:987–994

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Acknowledgements

The authors thank David Young, BSc, for editorial assistance. C.L. was supported by the Association pour la Recherche sur le Cancer. A.V., who assisted in the protocol design, was an employee of Siemens Healthcare. The other authors had full control over the data and the information submitted for publication.

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Correspondence to Alain Rahmouni.

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Lin, C., Luciani, A., Itti, E. et al. Whole-body diffusion-weighted magnetic resonance imaging with apparent diffusion coefficient mapping for staging patients with diffuse large B-cell lymphoma. Eur Radiol 20, 2027–2038 (2010). https://doi.org/10.1007/s00330-010-1758-y

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  • DOI: https://doi.org/10.1007/s00330-010-1758-y

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