OPTIMIZATION OF A WHOLE-BODY MAGNETIC RESONANCE IMAGING PROTOCOL FOR HODGKIN LYMPHOMA STAGING

Objective: to optimize a whole-body magnetic resonance imaging (WBMRI) protocol including diffusion-weighted imaging (DWI) used as a diagnostic complex for Hodgkin lymphoma (HL).

Material and methods. The WBMRI protocol adapted for HL staging and monitoring was tried out on 1.5 T and 3.0 T MRI scanners. The investigation included 128 patients with HL verified by complex clinical, laboratory, and instrumental studies (including computed tomography (CT), positron emission tomography (PET), PET/CT, scintigraphy and radiology of the skeleton, ultrasonography, laboratory tests, and biopsy) and 27 healthy individuals. The diagnostic value of the elaborated protocol was determined comparing with that of 18F-fluorodeoxyglucose PET, the gold standard for diagnosing HL in 63 patients with this condition.

Results. WBMRI showed high sensitivity (99.2%) (97.6–100% confidence interval (CI)) and specificity (99.6%) (99.05–100% CI) in determining the foci of lesion in HL.

Conclusion. The high sensitivity and specificity of WBMRI, which are similar to those of PET, may suggest that this method should be used to estimate the extent of the primary tumor in HL. Within one study, the proposed non-contrast-enhanced WBMRI protocol for 1.5 T and 3.0 T MRI scanners can yield anatomic (T2- WI) and functional (DWI estimating the measured diffusion coefficient) MR images of nodal and extranodal lesions in HL, without increasing time and modernizing equipment and software. The proposed protocol improves the quality of HL radiodiagnosis, by concurrently reducing a patient’s radiation exposure.

1. Новик А.А. Классификация злокачественных лимфом. СПб: ЭЛБИ; 2000. Novik А.А. Classification of malignant lymphomas. St. Petersburg; 2000 (in Russian).

2. Поддубная И.В., Савченко В.Г. (ред.) Росcийские клинические рекомендации по диагностике и лечению лимфопролиферативных заболеваний. М.: Медиа Медика; 2013. Poddubnaya I.V., Savchenko V.G. (eds). Russian clinical recommendations for diagnosis and treatment of lymphoproliferative diseases. Moscow; 2013 (in Russian).

3. Mariotto A.B., Yabroff K.R., Shao Y. et al. Projections of the cost of cancer care in the United States: 2010–2020. J. National Cancer Inst. 2011; 103 (2): 117–28.

4. Давыдов М.И., Аксель Е.М. Статистика злокачественных новообразований в России и странах СНГ в 2005 г. Вестник РОНЦ им. Н.Н. Блохина РАМН. 2007; 18 (2): 1. Davydov M.I., Aksel' E.M. Cancer statistics in Russia and the CIS countries in 2005. Vestnik Rossiyskogo Onkologicheskogo Nauchnogo Tsentra imeni N.N. Blokhina. 2007; 18 (2): 1 (in Russian).

5. Howlader N., Noone A.M., Krapchoet M. et al. SEER Cancer Statistics Review, 1975–2011. [Электронный ресурс]. 2013. Available at: http:// seer.cancer.gov/csr/ 1975_2011/

6. Демина Е.А., Тумян Г.С., Унукова Е.Н. и др. Современные возможности лечения первичных больных лимфомой Ходжкина и причины неудач лечения. Онкогематология. 2007; 2: 24–30. Demina E.A., Tumyan G.S., Unukova E.N. et al. Modern treatment programs for primary Hodgkin`s lymphoma and reasons of treatment failure. Onkogematologiya. 2007; 2: 24–30 (in Russian).

7. Демина Е.А. Лимфома Ходжкина: прогностические признаки сегодня. Современная онкология. 2006; 8 (4): 4–8. Demina Е.А. Hodgkin's lymphoma: prognostic signs today. Sovremennaya onkologiya. 2006; 8 (4): 4–8 (in Russian).

8. Труфанов Г.Е., Рязанов В.В., Дмитращенко А.А. и др. Совмещенная позитронно-эмиссионная и компьютерная томография в онкологии. СПб: Элби-СПб; 2005. Trufanov G.E., Ryazanov V.V., Dmitrashchenko A.A. et al. Combined positron emission tomography and computed tomography in oncology. St. Petersburg: Elbi-SPb; 2005 (in Russian).

9. Nogami M., Nakamoto Y., Sakamoto S. et al. Diagnostic performance of CT, PET, side-by-side, and fused image interpretations for restaging of non-Hodgkin lymphoma. Ann. Nucl. Med. 2007; 21 (4): 189–96.

10. Schöder H., Larson S.M., Yeung H.W.D. PET/CT in oncology: integration into clinical management of lymphoma, melanoma, and gastrointestinal malignancies. J. Nucl. Med. 2004; 45 (Suppl. 1): 72S–81S.

11. Tatsumi M., Kitayama H., Sugahara H. et al. Whole-body hybrid PET with 18F-FDG in the staging of non-Hodgkin’s lymphoma. J. Nucl. Med. 2001; 42 (4): 601–8.

12. Juweid M.E., Stroobants S., Hoekstra O.S. et al.Use of positron emission tomography for response assessment of lymphoma: consensus of the Imaging Subcommittee of International Harmonization Project in Lymphoma. J. Clin. Oncol. 2007; 25 (5): 571–8.

13. Cheson B.D., Fisher R.I., Barrington S.F. et al. Recommendations for initial evaluation, staging, and response assessment of Hodgkin and Non-Hodgkin lymphoma: The Lugano Classification. J. Clin. Oncol. 2014; С. JCO. 2013.54.8800.

14. Cheson B.D., Pfistner B., Juweid M.E. et al. Revised response criteria for malignant lymphoma. J. Clin. Oncol. 2007; 25 (5): 579–86.

15. Зыков Е.М., Поздняков А.В., Костеников Н.А. Рациональное использование ПЭТ и ПЭТ-КТ в онкологии. Практическая онкология. 2014; 15 (1): 31. Zykov E.M., Pozdnyakov A.V., Kostenikov N.A. Rational use of PET and PET-CT in Oncology. Prakticheskaya onkologiya. 2014; 15 (1): 31 (in Russian).

16. Plenge E., Poot D.H.J., Bernsenal M. Super resolution methods in MRI: Can they improve the trade off between resolution, signal to noise ratio, and acquisition time? Magn. Reson. Med. 2012; 68 (6): 1983–93.

17. Haacke E.M., Brown R.W., Thompson M.R. et al. Magnetic resonance imaging: Physical principles and sequence design. New York: Wiley; 1999.

18. Hashemi R.H., Bradley W.G., Lisanti C.J. MRI: the basics. Lippincott: Williams & Wilkins; 2012.

19. McRobbie D.W., Moore E.A., Graves M.J. et al. MRI from picture to proton. Cambridge University Press; 2007.

20. Heidemann R.M., Özsarlak Ö., Parizel P.M. et al. A brief review of parallel magnetic resonance imaging. Eur. Radiol. 2003; 13 (10): 2323–37.

21. Pruessmann K.P. Encoding and reconstruction in parallel MRI. NMR in Biomedicine. 2006; 19 (3): 288–99.

22. Pipe J.G. Motion correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging. Magn. Reson. Med. 1999; 42 (5): 963–9.

23. Lustig M., Donoho D., Pauly J.M. Sparse MRI: The application of compressed sensing for rapid MR imaging. Magn. Reson. Med. 2007; 58 (6): 1182–95.

24. Plenge E., Poot D.H.J., Bernsenal M. Super resolution methods in MRI: Can they improve the trade off between resolution, signal to noise ratio, and acquisition time? Magn. Reson. Med. 2012; 68 (6): 1983–93.

25. Blaimer M. SMASH, SENSE, PILS, GRAPPA: how to choose the optimal method. Top. Magn. Reson. Imag. 2004; 15 (4): 223–36.

26. Малая медицинская энциклопедия. М.: Советская энциклопедия; 1991; 2. Small Medical Encyclopedia. Moscow: Sovetskaya entsiklopediya; 1991; 2 (in Russian).

27. Cutillo A.G., Goodrich K.C., Ganesan K. et al. Alveolar air/tissue interface and nuclear magnetic resonance behavior of normal and edematous lungs. Am. J. Respir. Crit. Care Med. 1995; 151: 1018–26.

28. Yu J.S., Kim K.W., Kim Y.H. et al. Comparison of multishot turbo spin echo and HASTE sequences for T2 weighted MRI of liver lesions. J. Magn. Reson. Med. 1998; 8 (5): 1079–84.

29. Кулаков В.И. Гинекология: национальное руководство. М.: ГЭОТАР-Медиа; 2007: 737–48. Kulakov V.I. Gynecology: national guidelines. Moscow: GEOTAR-Media; 2007: 737–48 (in Russian).

30. Vogt F.M., Herborn C.U., Hunold P. et al. HASTE MRI versus chest radiography in the detection of pulmonary nodules: comparison with MDCT. Am. J. Roentgenol. 2004; 183 (1): 71–8.

31. Delfaut E.M., Beltran J., Johnson G. et al. Fat suppression in MR imaging techniques and pitfalls. Radiographics. 1999; 19 (2): 373–82.

32. Padhani A.R., Liu G., Mu-Koh D. et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009; 11 (2): 102–25.

33. Anderson A.W., Gore J.C. Analysis and correction of motion artifacts in diffusion weighted imaging. Magn. Reson. Med. 1994; 32 (3): 379–87.

34. Basser P.J., Mattiello J., LeBihan D. Estimation of the effective self-diffusion tensor from the NMR spin echo. J. Magn. Reson. Med. Series B. 1994; 103 (3): 247–54.

35. Beaulieu C. The basis of anisotropic water diffusion in the nervous system – a technical review. NMR Biomed. 2002; 15 (78): 435–55.

36. Takahara T., Imai Y., Yamashita T. et al. Diffusion weighted whole body imaging with background body signal suppression (DWIBS): technical improvement using free breathing, STIR and high resolution 3D display. Matrix. 2004; 160 (160): 275–82.

37. Koh D.M., Collins D.J. Diffusionweighted MRI in the body: applications and challenges in oncology. Am. J. Roentgenol. 2007; 188 (6): 1622–35.

38. Kwee T.C., Takahara T., Ochiai R. et al. Diffusion-weighted wholebody imaging with background body signal suppression (DWIBS): features and potential applications in oncology. Eur. Radiol. 2008; 18 (9): 1937–52.