Skip to main content

Advertisement

SpringerLink
Log in

Hybrid FDG-PET/MR compared to FDG-PET/CT in adult lymphoma patients

  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

The goal of this study is to evaluate the diagnostic performance of simultaneous FDG-PET/MR including diffusion compared to FDG-PET/CT in patients with lymphoma.

Methods

Eighteen patients with a confirmed diagnosis of non-Hodgkin’s (NHL) or Hodgkin’s lymphoma (HL) underwent an IRB-approved, single-injection/dual-imaging protocol consisting of a clinical FDG-PET/CT and subsequent FDG-PET/MR scan. PET images from both modalities were reconstructed iteratively. Attenuation correction was performed using low-dose CT data for PET/CT and Dixon-MR sequences for PET/MR. Diffusion-weighted imaging was performed. SUVmax was measured and compared between modalities and the apparent diffusion coefficient (ADC) using ROI analysis by an experienced radiologist using OsiriX. Strength of correlation between variables was measured using the Pearson correlation coefficient (r p).

Results

Of the 18 patients included in this study, 5 had HL and 13 had NHL. The median age was 51 ± 14.8 years. Sixty-five FDG-avid lesions were identified. All FDG-avid lesions were visible with comparable contrast, and therefore initial and follow-up staging was identical between both examinations. SUVmax from FDG-PET/MR [(mean ± sem) (21.3 ± 2.07)] vs. FDG-PET/CT (mean 23.2 ± 2.8) demonstrated a strongly positive correlation [r s = 0.95 (0.94, 0.99); p < 0.0001]. There was no correlation found between ADCmin and SUVmax from FDG-PET/MR [r = 0.17(−0.07, 0.66); p = 0.09].

Conclusion

FDG-PET/MR offers an equivalent whole-body staging examination as compared with PET/CT with an improved radiation safety profile in lymphoma patients. Correlation of ADC to SUVmax was weak, understating their lack of equivalence, but not undermining their potential synergy and differing importance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. 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

    Article  PubMed  Google Scholar 

  2. Lin C, Luciani A, Itti E, Haioun C, Rahmouni A (2007) Whole body MRI and PET/CT in haematological malignancies. Cancer Imaging 7(Spec No A):S88

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  4. Delbeke D, Stroobants S, de Kerviler E, et al. (2009) Expert opinions on positron emission tomography and computed tomography imaging in lymphoma. Oncol 14(Suppl 2):30

    Article  Google Scholar 

  5. Brepoels L, Stroobants S, De Wever W, et al. (2007) Hodgkin lymphoma: response assessment by revised international workshop criteria. Leuk Lymphoma 48:1539

    Article  PubMed  Google Scholar 

  6. 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

    Article  CAS  PubMed  Google Scholar 

  7. Jerusalem G, Beguin Y, Fassotte MF, et al. (2000) Persistent tumor 18F-FDG uptake after a few cycles of polychemotherapy is predictive of treatment failure in non-Hodgkin’s lymphoma. Haematologica 85:613

    CAS  PubMed  Google Scholar 

  8. Mikhaeel NG, Timothy AR, O’Doherty MJ, Hain S, Maisey MN (2000) 18-FDG-PET as a prognostic indicator in the treatment of aggressive Non-Hodgkin’s Lymphoma-comparison with CT. Leuk Lymphoma 39:543

    Article  CAS  PubMed  Google Scholar 

  9. Spaepen K, Stroobants S, Dupont P, et al. (2002) Early restaging positron emission tomography with (18)F-fluorodeoxyglucose predicts outcome in patients with aggressive non-Hodgkin’s lymphoma. Ann Oncol 13:1356

    Article  CAS  PubMed  Google Scholar 

  10. Zinzani PL, Rigacci L, Stefoni V, et al. (2012) Early interim 18F-FDG PET in Hodgkin’s lymphoma: evaluation on 304 patients. Eur J Nucl Med Mol Imaging 39:4

    Article  PubMed  Google Scholar 

  11. Hutchings M (2012) How does PET/CT help in selecting therapy for patients with Hodgkin lymphoma? Hematol Educ Progr Am Soc Hematol Am Soc Hematol Edu Progr 2012:322

    Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  13. Pearce MS, Salotti JA, Little MP, et al. (2012) Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet 380:499

    Article  PubMed  PubMed Central  Google Scholar 

  14. Brix G, Henze M, Knopp MV, et al. (2001) Comparison of pharmacokinetic MRI and [18F] fluorodeoxyglucose PET in the diagnosis of breast cancer: initial experience. Eur Radiol 11:2058

    Article  CAS  PubMed  Google Scholar 

  15. Nievelstein RA, Quarles van Ufford HM, Kwee TC, et al. (2012) Radiation exposure and mortality risk from CT and PET imaging of patients with malignant lymphoma. Eur Radiol 22:1946

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Catana C, Guimaraes AR, Rosen BR (2013) PET and MR imaging: the odd couple or a match made in heaven? J Nucl Med 54:815

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Catana C, Wu Y, Judenhofer MS, et al. (2006) Simultaneous acquisition of multislice PET and MR images: initial results with a MR-compatible PET scanner. J Nuclear Med 47:1968

    Google Scholar 

  18. Wehrl HF, Sauter AW, Judenhofer MS, Pichler BJ (2010) Combined PET/MR imaging–technology and applications. Technol Cancer Res Treat 9:5

    Article  CAS  PubMed  Google Scholar 

  19. Punwani S, Prakash V, Bainbridge A, et al. (2010) Quantitative diffusion weighted MRI: a functional biomarker of nodal disease in Hodgkin lymphoma? Cancer Biomark Sect A Dis Mark 7:249

    Google Scholar 

  20. Punwani S, Taylor SA, Saad ZZ, et al. (2013) Diffusion-weighted MRI of lymphoma: prognostic utility and implications for PET/MRI? Eur J Nuclear Med Mol Imaging 40:373

    Article  Google Scholar 

  21. Barajas RF Jr, Rubenstein JL, Chang JS, Hwang J, Cha S (2010) Diffusion-weighted MR imaging derived apparent diffusion coefficient is predictive of clinical outcome in primary central nervous system lymphoma. AJNR Am J Neuroradiol 31:60

    Article  PubMed  Google Scholar 

  22. 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

    Article  PubMed  Google Scholar 

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

    Article  PubMed  Google Scholar 

  24. 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

    Article  PubMed  Google Scholar 

  25. Abdulqadhr G, Molin D, Astrom G, et al. (2011) Whole-body diffusion-weighted imaging compared with FDG-PET/CT in staging of lymphoma patients. Acta Radiol 52:173

    Article  PubMed  Google Scholar 

  26. Gu J, Chan T, Zhang J, et al. (2011) Whole-body diffusion-weighted imaging: the added value to whole-body MRI at initial diagnosis of lymphoma. AJR Am J Roentgenol 197:W384

    Article  PubMed  Google Scholar 

  27. Choi BB, Kim SH, Kang BJ, et al. (2012) Diffusion-weighted imaging and FDG PET/CT: predicting the prognoses with apparent diffusion coefficient values and maximum standardized uptake values in patients with invasive ductal carcinoma. World J Surg Oncol 10:126

    Article  PubMed  PubMed Central  Google Scholar 

  28. Ippolito D, Monguzzi L, Guerra L, et al. (2012) Response to neoadjuvant therapy in locally advanced rectal cancer: assessment with diffusion-weighted MR imaging and 18FDG PET/CT. Abdom Imaging 37:1032

    Article  PubMed  Google Scholar 

  29. Marzolini M, Wong WL, Ardeshna K, Padhani A, D’Sa S (2012) Diffusion-weighted MRI compared to FDG PET-CT in the staging and response assessment of Hodgkin lymphoma. Br J Haematol 156:557

    Article  PubMed  Google Scholar 

  30. Nakajo M, Nakajo M, Kajiya Y, et al. (2012) FDG PET/CT and diffusion-weighted imaging of head and neck squamous cell carcinoma: comparison of prognostic significance between primary tumor standardized uptake value and apparent diffusion coefficient. Clin Nucl Med 37:475

    Article  PubMed  Google Scholar 

  31. Olsen JR, Esthappan J, DeWees T, et al. (2013) Tumor volume and subvolume concordance between FDG-PET/CT and diffusion-weighted MRI for squamous cell carcinoma of the cervix. J Magn Reson Imaging 37:431

    Article  PubMed  Google Scholar 

  32. Heacock L, Weissbrot J, Raad R, et al. (2015) PET/MRI for the evaluation of patients with lymphoma: initial observations. AJR Am J Roentgenol 204:842

    Article  PubMed  PubMed Central  Google Scholar 

  33. Martinez-Moller A, Nekolla SG (2012) Attenuation correction for PET/MR: problems, novel approaches and practical solutions. Z Med Phys 22:299

    Article  PubMed  Google Scholar 

  34. Drzezga A, Souvatzoglou M, Eiber M, et al. (2012) First clinical experience with integrated whole-body PET/MR: comparison to PET/CT in patients with oncologic diagnoses. J Nuclear Med 53:845

    Article  Google Scholar 

  35. Awan UE, Siddiqui N, SaadUllah M, et al. (2013) FDG-PET scan in assessing lymphomas and the application of Deauville Criteria. J Pak Med Assoc 63:725

    PubMed  Google Scholar 

  36. Huda W, Ogden KM, Khorasani MR (2008) Converting dose-length product to effective dose at CT. Radiology 248:995

    Article  PubMed  PubMed Central  Google Scholar 

  37. Huang B, Law MW, Khong PL (2009) Whole-body PET/CT scanning: estimation of radiation dose and cancer risk. Radiology 251:166

    Article  PubMed  Google Scholar 

  38. 1990 Recommendations of the International Commission on Radiological Protection. Annals of the ICRP 1991; 21:1

  39. Zou KH, Tuncali K, Silverman SG (2003) Correlation and simple linear regression. Radiology 227:617

    Article  PubMed  Google Scholar 

  40. The 2007 Recommendations of the International Commission on Radiological Protection. ICRP publication 103. Annals of the ICRP 2007; 37:1

  41. Mcdermott S, Blake MA, Sahani DV, et al. (2012) Maximum SUV: Do Pet/MR and PET/CT differ? Our experience. RSNA

  42. Lyons K, Seghers V, Sorensen JI, et al. (2015) Comparison of standardized uptake values in normal structures between PET/CT and PET/MRI in a tertiary pediatric hospital: a prospective study. AJR Am J Roentgenol 205:1094

    Article  PubMed  Google Scholar 

  43. Lyons K, Seghers V, Williams JL, et al. (2015) Qualitative FDG PET image assessment using automated three-segment MR attenuation correction versus CT attenuation correction in a tertiary pediatric hospital: a prospective study. AJR Am J Roentgenol 205:652

    Article  PubMed  Google Scholar 

  44. Keyes JWJ (1995) SUV: standard uptake or silly useless value? J Nucl Med 36:1836

    PubMed  Google Scholar 

  45. Hamberg LM, Hunter GJ, Alpert NM, et al. (1994) The dose uptake ratio as an index of glucose metabolism: useful parameter or oversimplification? J Nucl Med 35:1308

    CAS  PubMed  Google Scholar 

  46. Mayerhoefer ME, Karanikas G, Kletter K, et al. (2014) Evaluation of diffusion-weighted MRI for pretherapeutic assessment and staging of lymphoma: results of a prospective study in 140 patients. Clin Cancer Res 20:2984

    Article  PubMed  Google Scholar 

  47. 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

    Article  PubMed  Google Scholar 

  48. Wu X, Korkola P, Pertovaara H, et al. (2011) No correlation between glucose metabolism and apparent diffusion coefficient in diffuse large B-cell lymphoma: a PET/CT and DW-MRI study. Eur J Radiol 79:e117

    Article  PubMed  Google Scholar 

  49. Buchbender C, Hartung-Knemeyer V, Heusch P, et al. (2013) Does positron emission tomography data acquisition impact simultaneous diffusion-weighted imaging in a whole-body PET/MRI system? Eur J Radiol 82:380

    Article  PubMed  Google Scholar 

  50. Hirsch FW, Sattler B, Sorge I, et al. (2013) PET/MR in children. Initial clinical experience in paediatric oncology using an integrated PET/MR scanner. Pediatr Radiol 43:860

    Article  PubMed  PubMed Central  Google Scholar 

  51. Stephane V, Samuel B, Vincent D, et al. (2013) Comparison of PET-CT and magnetic resonance diffusion weighted imaging with body suppression (DWIBS) for initial staging of malignant lymphomas. Eur J Radiol 82:2011

    Article  PubMed  Google Scholar 

  52. De Paepe K, Bevernage C, De Keyzer F, et al. (2013) Whole-body diffusion-weighted magnetic resonance imaging at 3 Tesla for early assessment of treatment response in non-Hodgkin lymphoma: a pilot study. Cancer Imaging 13:53

    Article  PubMed  PubMed Central  Google Scholar 

  53. Chawla SC, Federman N, Zhang D, et al. (2010) Estimated cumulative radiation dose from PET/CT in children with malignancies: a 5-year retrospective review. Pediatr Radiol 40:681

    Article  PubMed  Google Scholar 

  54. Tricarico F, Hlavacek AM, Schoepf UJ, et al. (2013) Cardiovascular CT angiography in neonates and children: image quality and potential for radiation dose reduction with iterative image reconstruction techniques. Eur Radiol 23:1306

    Article  PubMed  Google Scholar 

  55. Xiao H, Liu Y, Tan H, et al. (2015) A pilot study using low-dose Spectral CT and ASIR (Adaptive Statistical Iterative Reconstruction) algorithm to diagnose solitary pulmonary nodules. BMC Med Imaging 15:54

    Article  PubMed  PubMed Central  Google Scholar 

  56. Heusch P, Buchbender C, Beiderwellen K, et al. (2013) Standardized uptake values for [(1)(8)F] FDG in normal organ tissues: comparison of whole-body PET/CT and PET/MRI. Eur J Radiol 82:870

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the Martinos Center for Biomedical Imaging, and in specific Lawrence White and Mary Foley for the assistance in performing the clinical trial.

Funding

This study was funded through an internal funding mechanism.

Author information

Authors and Affiliations

  1. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, 02129, USA

    Wendy Atkinson, Ciprian Catana, Grae Arabasz, Onofrio Catalano, Bruce R. Rosen & Alexander R. Guimaraes

  2. Division of Hematology and Oncology, Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA

    Jeremy S. Abramson, Jeffrey Barnes & Ephraim Hochberg

  3. Division of Thoracic Radiology, Department of Radiology, Massachusetts General Hospital, Boston, MA, 02114, USA

    Victorine Muse

  4. Division of Abdominal Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, 02114, USA

    Shanaugh McDermott, Michael A. Blake, Martin Shelly & Alexander R. Guimaraes

  5. Division of Body Imaging, Department of Diagnostic Radiology, Oregon Health Sciences University, 3181 SW Sam Jackson Park Rd., Mail Code L340, Portland, OR, 97239, USA

    Alexander R. Guimaraes

Authors
  1. Wendy Atkinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ciprian Catana
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jeremy S. Abramson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Grae Arabasz
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shanaugh McDermott
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Onofrio Catalano
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Victorine Muse
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Michael A. Blake
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jeffrey Barnes
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Martin Shelly
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Ephraim Hochberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Bruce R. Rosen
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Alexander R. Guimaraes
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alexander R. Guimaraes.

Ethics declarations

Conflicts of interest

Bruce R. Rosen: Siemens Consultant; Alexander R. Guimaraes: Siemens Speakers’ Bureau, Expert Witness; Wendy Atkinson, Ciprian Catana, Jeremy Abramson, Grae Arabasz, Shanaugh McDermott, Onofrio Catalano, Victorine Muse, Michael A Blake, Jeffrey Barnes, Martin Shelly, and Ephraim Hochberg have nothing to declare.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Atkinson, W., Catana, C., Abramson, J.S. et al. Hybrid FDG-PET/MR compared to FDG-PET/CT in adult lymphoma patients. Abdom Radiol 41, 1338–1348 (2016). https://doi.org/10.1007/s00261-016-0638-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-016-0638-6

Keywords

Search

Navigation