Advertisement

Correlation of apparent diffusion coefficients measured by 3T diffusion-weighted MRI and SUV from FDG PET/CT in primary cervical cancer

  • Kung-Chu Ho
  • Gigin Lin
  • Jiun-Jie Wang
  • Chyong-Huey Lai
  • Chee-Jen Chang
  • Tzu-Chen YenEmail author
Original Article

Abstract

Purpose

Diffusion-weighted magnetic resonance imaging (DWI) and fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) are oncological feasible techniques. Currently, apparent diffusion coefficient (ADC) measured by DWI and standard uptake value (SUV) from FDG PET/CT have similar applications in clinical oncology. The aim of this study was to assess the correlation between ADC and SUV in primary cervical cancer.

Materials and methods

Patients with documented primary cervical cancer were recruited. All participants underwent abdominopelvic DWI at 3T and FDG PET/CT within 2 weeks. For the primary tumor, ADC was measured as minimum ADC (ADCmin) and mean ADC (ADCmean) within the whole tumor by DWI. Maximum SUV (SUVmax) and mean SUV (SUVmean) were measured by FDG PET/CT.

Results

A total of 33 patients were included. There was no significant correlation either between ADCmin and SUVmax or between ADCmean and SUVmean. The relative ADCmin (rADCmin) defined as ADCmin/ADCmean ratio was significantly inversely correlated with the relative SUVmax (rSUVmax) defined as SUVmax/SUVmean ratio (r = –0.526, P = 0.0017) in all study patients. A significantly inverse correlation between rADCmin and rSUVmax was observed in patients with adenocarcinoma/adenosquamous carcinoma (r = –0.685, P = 0.0012) and those with well-to-moderate differentiated tumor (r = –0.631, P = 0.0050). No significant correlation was demonstrated in patients with squamous cell carcinoma or poorly differentiated tumor.

Conclusions

The significantly inverse correlation between rADCmin and rSUVmax in primary cervical tumor suggests that DWI and FDG PET/CT might play a complementary role for the clinical assessment of this cancer type.

Keywords

18F-FDG PET/CT 3T MRI DWI Cervical cancer 

Notes

Acknowledgments

This research was supported by grants from the National Science Council, Taiwan (NSC 95-2314-B-182A-136-MY3) and the Chang Gung Memorial Hospital (CMRPG 340091).

References

  1. 1.
    Nemeth AJ, Henson JW, Mullins ME, Gonzalez RG, Schaefer PW. Improved detection of skull metastasis with diffusion-weighted MR imaging. AJNR Am J Neuroradiol 2007;28:1088–92.PubMedCrossRefGoogle Scholar
  2. 2.
    Nasu K, Kuroki Y, Nawano S, Kuroki S, Tsukamoto T, Yamamoto S, et al. Hepatic metastases: diffusion-weighted sensitivity-encoding versus SPIO-enhanced MR imaging. Radiology 2006;239:122–30.PubMedCrossRefGoogle Scholar
  3. 3.
    Hayashida Y, Hirai T, Morishita S, Kitajima M, Murakami R, Korogi Y, et al. Diffusion-weighted imaging of metastatic brain tumors: comparison with histologic type and tumor cellularity. AJNR Am J Neuroradiol 2006;27:1419–25.PubMedGoogle Scholar
  4. 4.
    Guo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002;224:177–83.PubMedCrossRefGoogle Scholar
  5. 5.
    Herneth AM, Guccione S, Bednarski M. Apparent diffusion coefficient: a quantitative parameter for in vivo tumor characterization. Eur J Radiol 2003;45:208–13.PubMedCrossRefGoogle Scholar
  6. 6.
    Wang J, Takashima S, Takayama F, Kawakami S, Saito A, Matsushita T, et al. Head and neck lesions: characterization with diffusion-weighted echo-planar MR imaging. Radiology 2001;220:621–30.PubMedCrossRefGoogle Scholar
  7. 7.
    Rubesova E, Grell AS, De Maertelaer V, Metens T, Chao SL, Lemort M. Quantitative diffusion imaging in breast cancer: a clinical prospective study. J Magn Reson Imaging 2006;24:319–24.PubMedCrossRefGoogle Scholar
  8. 8.
    Pickles MD, Gibbs P, Sreenivas M, Turnbull LW. Diffusion-weighted imaging of normal and malignant prostate tissue at 3.0T. J Magn Reson Imaging 2006;23:130–4.PubMedCrossRefGoogle Scholar
  9. 9.
    Naganawa S, Sato C, Kumada H, Ishigaki T, Miura S, Takizawa O. Apparent diffusion coefficient in cervical cancer of the uterus: comparison with the normal uterine cervix. Eur Radiol 2005;15:71–8.PubMedCrossRefGoogle Scholar
  10. 10.
    Squillaci E, Manenti G, Di Stefano F, Miano R, Strigari L, Simonetti G. Diffusion-weighted MR imaging in the evaluation of renal tumours. J Exp Clin Cancer Res 2004;23:39–45.PubMedGoogle Scholar
  11. 11.
    Di Costanzo A, Scarabino T, Trojsi F, Giannatempo GM, Popolizio T, Catapano D, et al. Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy. Neuroradiology 2006;48:622–31.PubMedCrossRefGoogle Scholar
  12. 12.
    Hamstra DA, Chenevert TL, Moffat BA, Johnson TD, Meyer CR, Mukherji SK, et al. Evaluation of the functional diffusion map as an early biomarker of time-to-progression and overall survival in high-grade glioma. Proc Natl Acad Sci USA 2005;102:16759–64.PubMedCrossRefGoogle Scholar
  13. 13.
    Patterson DM, Padhani AR, Collins DJ. Technology insight: water diffusion MRI—a potential new biomarker of response to cancer therapy. Nat Clin Pract Oncol 2008;5:220–33.PubMedCrossRefGoogle Scholar
  14. 14.
    Kamel IR, Reyes DK, Liapi E, Bluemke DA, Geschwind JF. Functional MR imaging assessment of tumor response after 90Y microsphere treatment in patients with unresectable hepatocellular carcinoma. J Vasc Interv Radiol 2007;18:49–56.PubMedCrossRefGoogle Scholar
  15. 15.
    Pickles MD, Gibbs P, Lowry M, Turnbull LW. Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer. Magn Reson Imaging 2006;24:843–7.PubMedCrossRefGoogle Scholar
  16. 16.
    Moffat BA, Chenevert TL, Lawrence TS, Meyer CR, Johnson TD, Dong Q, et al. Functional diffusion map: a noninvasive MRI biomarker for early stratification of clinical brain tumor response. Proc Natl Acad Sci USA 2005;102:5524–9.PubMedCrossRefGoogle Scholar
  17. 17.
    Hamstra DA, Rehemtulla A, Ross BD. Diffusion magnetic resonance imaging: a biomarker for treatment response in oncology. J Clin Oncol 2007;25:4104–9.PubMedCrossRefGoogle Scholar
  18. 18.
    Brindle K. New approaches for imaging tumour responses to treatment. Nat Rev Cancer 2008;8:94–107.PubMedCrossRefGoogle Scholar
  19. 19.
    Komori T, Narabayashi I, Matsumura K, Matsuki M, Akagi H, Ogura Y, et al. 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 2007;21:209–15.PubMedCrossRefGoogle Scholar
  20. 20.
    Lichy MP, Aschoff P, Plathow C, Stemmer A, Horger W, Mueller-Horvat C, et al. Tumor detection by diffusion-weighted MRI and ADC-mapping—initial clinical experiences in comparison to PET-CT. Invest Radiol 2007;42:605–13.PubMedCrossRefGoogle Scholar
  21. 21.
    Mitchell DG, Snyder B, Coakley F, Reinhold C, Thomas G, Amendola M, et al. Early invasive cervical cancer: tumor delineation by magnetic resonance imaging, computed tomography, and clinical examination, verified by pathologic results, in the ACRIN 6651/GOG 183 Intergroup Study. J Clin Oncol 2006;24:5687–94.PubMedCrossRefGoogle Scholar
  22. 22.
    Hricak H, Gatsonis C, Coakley FV, Snyder B, Reinhold C, Schwartz LH, et al. Early invasive cervical cancer: CT and MR imaging in preoperative evaluation—ACRIN/GOG comparative study of diagnostic performance and interobserver variability. Radiology 2007;245:491–8.PubMedCrossRefGoogle Scholar
  23. 23.
    Lin G, Ho KC, Wang JJ, Ng KK, Wai YY, Chen YT, et al. Detection of lymph node metastasis in cervical and uterine cancers by diffusion-weighted magnetic resonance imaging at 3T. J Magn Reson Imaging 2008;28:128–35.PubMedCrossRefGoogle Scholar
  24. 24.
    Yen TC, Lai CH. Positron emission tomography in gynecologic cancer. Semin Nucl Med 2006;36:93–104.PubMedCrossRefGoogle Scholar
  25. 25.
    Xue F, Lin LL, Dehdashti F, Miller TR, Siegel BA, Grigsby PW. F-18 fluorodeoxyglucose uptake in primary cervical cancer as an indicator of prognosis after radiation therapy. Gynecol Oncol 2006;101:147–51.PubMedCrossRefGoogle Scholar
  26. 26.
    Yen TC, See LC, Lai CH, Tsai CS, Chao A, Hsueh S, et al. Standardized uptake value in para-aortic lymph nodes is a significant prognostic factor in patients with primary advanced squamous cervical cancer. Eur J Nucl Med Mol Imaging 2008;35:493–501.PubMedCrossRefGoogle Scholar
  27. 27.
    Schwarz JK, Siegel BA, Dehdashti F, Grigsby PW. Association of posttherapy positron emission tomography with tumor response and survival in cervical carcinoma. JAMA 2007;298:2289–95.PubMedCrossRefGoogle Scholar
  28. 28.
    Hickeson M, Yun M, Matthies A, Zhuang H, Adam LE, Lacorte L, et al. Use of a corrected standardized uptake value based on the lesion size on CT permits accurate characterization of lung nodules on FDG-PET. Eur J Nucl Med Mol Imaging 2002;29:1639–47.PubMedCrossRefGoogle Scholar
  29. 29.
    Soret M, Bacharach SL, Buvat I. Partial-volume effect in PET tumor imaging. J Nucl Med 2007;48:932–45.PubMedCrossRefGoogle Scholar
  30. 30.
    Miller TR, Grigsby PW. Measurement of tumor volume by PET to evaluate prognosis in patients with advanced cervical cancer treated by radiation therapy. Int J Radiat Oncol Biol Phys 2002;53:353–9.PubMedGoogle Scholar
  31. 31.
    Biehl KJ, Kong FM, Dehdashti F, Jin JY, Mutic S, El Naqa I, et al. 18F-FDG PET definition of gross tumor volume for radiotherapy of non-small cell lung cancer: is a single standardized uptake value threshold approach appropriate? J Nucl Med 2006;47:1808–12.PubMedGoogle Scholar
  32. 32.
    Meyer M. Standardized uptake values of 18F-FDG uptake by lung neoplasms: a meta-analysis of 437 cases. J Nucl Med 2007;48(Suppl 2):352P.Google Scholar
  33. 33.
    Xing D, Papadakis NG, Huang CL, Lee VM, Carpenter TA, Hall LD. Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. Magn Reson Imaging 1997;15:771–84.PubMedCrossRefGoogle Scholar
  34. 34.
    King AD, Ahuja AT, Yeung DK, Fong DK, Lee YY, Lei KI, et al. Malignant cervical lymphadenopathy: diagnostic accuracy of diffusion-weighted MR imaging. Radiology 2007;245:806–13.PubMedCrossRefGoogle Scholar
  35. 35.
    Vandecaveye V, De Keyzer F, Nuyts S, Deraedt K, Dirix P, Hamaekers P, et al. Detection of head and neck squamous cell carcinoma with diffusion weighted MRI after (chemo)radiotherapy: correlation between radiologic and histopathologic findings. Int J Radiat Oncol Biol Phys 2007;67:960–71.PubMedGoogle Scholar
  36. 36.
    Thie JA. Understanding the standardized uptake value, its methods, and implications for usage. J Nucl Med 2004;45:1431–4.PubMedGoogle Scholar
  37. 37.
    Gregoire V, Haustermans K, Geets X, Roels S, Lonneux M. PET-based treatment planning in radiotherapy: A new standard? J Nucl Med 2007;48:68S–77S.PubMedGoogle Scholar
  38. 38.
    Ahn PH, Garg MK. Positron emission tomography/computed tomography for target delineation in head and neck cancers. Semin Nucl Med 2008;38:141–8.PubMedCrossRefGoogle Scholar
  39. 39.
    Cornfeld DM, Weinreb JC. MR imaging of the prostate: 1.5T versus 3T. Magn Reson Imaging Clin N Am 2007;15:433–48.PubMedCrossRefGoogle Scholar
  40. 40.
    Habermann CR, Gossrau P, Kooijman H, Graessner J, Cramer MC, Kaul MG, et al. Monitoring of gustatory stimulation of salivary glands by diffusion-weighted MR imaging: comparison of 1.5T and 3T. AJNR Am J Neuroradiol 2007;28:1547–51.PubMedCrossRefGoogle Scholar
  41. 41.
    Naganawa S, Kawai H, Fukatsu H, Sakurai Y, Aoki I, Miura S, et al. Diffusion-weighted imaging of the liver: technical challenges and prospects for the future. Magn Reson Med Sci 2005;4:175–86.PubMedCrossRefGoogle Scholar
  42. 42.
    Bos R, van Der Hoeven JJ, van Der Wall E, van Der Groep P, van Diest PJ, Comans EF, et al. Biologic correlates of (18)fluorodeoxyglucose uptake in human breast cancer measured by positron emission tomography. J Clin Oncol 2002;20:379–87.PubMedCrossRefGoogle Scholar
  43. 43.
    Higashi T, Tamaki N, Torizuka T, Nakamoto Y, Sakahara H, Kimura T, et al. FDG uptake, GLUT-1 glucose transporter and cellularity in human pancreatic tumors. J Nucl Med 1998;39:1727–35.PubMedGoogle Scholar
  44. 44.
    Ito K, Kato T, Ohta T, Tadokoro M, Yamada T, Ikeda M, et al. Fluorine-18 fluoro-2-deoxyglucose positron emission tomography in recurrent rectal cancer: relation to tumour size and cellularity. Eur J Nucl Med 1996;23:1372–7.PubMedCrossRefGoogle Scholar
  45. 45.
    Kim HS, Kim SY. A prospective study on the added value of pulsed arterial spin-labeling and apparent diffusion coefficients in the grading of gliomas. AJNR Am J Neuroradiol 2007;28:1693–9.PubMedCrossRefGoogle Scholar
  46. 46.
    Higano S, Yun X, Kumabe T, Watanabe M, Mugikura S, Umetsu A, et al. Malignant astrocytic tumors: clinical importance of apparent diffusion coefficient in prediction of grade and prognosis. Radiology 2006;241:839–46.PubMedCrossRefGoogle Scholar
  47. 47.
    Murakami R, Sugahara T, Nakamura H, Hirai T, Kitajima M, Hayashida Y, et al. Malignant supratentorial astrocytoma treated with postoperative radiation therapy: prognostic value of pretreatment quantitative diffusion-weighted MR imaging. Radiology 2007;243:493–9.PubMedCrossRefGoogle Scholar
  48. 48.
    Camara E, Bodammer N, Rodriguez-Fornells A, Tempelmann C. Age-related water diffusion changes in human brain: a voxel-based approach. Neuroimage 2007;34:1588–99.PubMedCrossRefGoogle Scholar
  49. 49.
    Rovaris M, Iannucci G, Cercignani M, Sormani MP, De Stefano N, Gerevini S, et al. Age-related changes in conventional, magnetization transfer, and diffusion-tensor MR imaging findings: study with whole-brain tissue histogram analysis. Radiology 2003;227:731–8.PubMedCrossRefGoogle Scholar
  50. 50.
    Matoba M, Tonami H, Kondou T, Yokota H, Higashi K, Toga H, et al. Lung Carcinoma: diffusion-weighted MR imaging—preliminary evaluation with apparent diffusion coefficient. Radiology 2007;243:570–77.PubMedCrossRefGoogle Scholar
  51. 51.
    Zhang J, Mazaheri Tehrani Y, Wang L, Ishill NM, Schwartz LH, Hricak H. Renal masses: characterization with diffusion-weighted MR imaging—a preliminary experience. Radiology 2008;247:458–64.PubMedCrossRefGoogle Scholar
  52. 52.
    King AD, Ahuja AT, Yeung DKW, Fong DKY, Lee YYP, Lei KIK, et al. Malignant cervical lymphadenopathy: diagnostic accuracy of diffusion-weighted MR imaging. Radiology 2007;245:806–13.PubMedCrossRefGoogle Scholar
  53. 53.
    Vesselle H, Schmidt RA, Pugsley JM, Li M, Kohlmyer SG, Vallires E, et al. Lung cancer proliferation correlates with [F-18]fluorodeoxyglucose uptake by positron emission tomography. Clin Cancer Res 2000;6:3837–44.PubMedGoogle Scholar
  54. 54.
    Hutchings M, Loft A, Hansen M, Ralfkiaer E, Specht L. Different histopathological subtypes of Hodgkin lymphoma show significantly different levels of FDG uptake. Hematol Oncol 2006;24:146–50.PubMedCrossRefGoogle Scholar
  55. 55.
    Judenhofer MS, Wehrl HF, Newport DF, Catana C, Siegel SB, Becker M, et al. Simultaneous PET-MRI: a new approach for functional and morphological imaging. Nat Med 2008;14:459–65.PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Kung-Chu Ho
    • 1
  • Gigin Lin
    • 2
  • Jiun-Jie Wang
    • 1
    • 2
  • Chyong-Huey Lai
    • 3
  • Chee-Jen Chang
    • 4
  • Tzu-Chen Yen
    • 1
    Email author
  1. 1.Department of Nuclear Medicine and Molecular Imaging CenterChang Gung Memorial Hospital and Chang Gung UniversityKueishanTaiwan
  2. 2.Department of Medical Imaging and InterventionChang Gung Memorial Hospital and Chang Gung UniversityTaoyuanTaiwan
  3. 3.Division of Gynecologic Oncology, Department of Obstetrics and GynecologyChang Gung Memorial Hospital and Chang Gung UniversityTaoyuanTaiwan
  4. 4.Division of Biostatistics, Resources Center for Clinical ResearchChang Gung Memorial Hospital and Chang Gung UniversityTaoyuanTaiwan

Personalised recommendations