Tumor Biology

, Volume 36, Issue 7, pp 5515–5522 | Cite as

The clinical value of dynamic contrast-enhanced MRI in differential diagnosis of malignant and benign ovarian lesions

  • Xian Li
  • Jun-Li Hu
  • Lai-Min Zhu
  • Xin-Hai Sun
  • Hua-Qiang Sheng
  • Ning Zhai
  • Xi-Bin Hu
  • Chu-Ran Sun
  • Bin Zhao
Research Article


Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used in preoperative diagnosis of various tumors. We investigated the clinical value of DCE-MRI in differential diagnosis of malignant and benign ovarian lesions. The study involved 48 subjects with surgical pathology-confirmed ovarian tumors with solid components. Early dynamic phase enhancement performances of the ovarian lesions in patients were assessed, including the enhancement pattern, time-signal intensity curve (TIC), signal intensity rate at the initial 60 s (SI60), time to peak within 200 s (TTP200), and slope ratio. There were significant differences in enhancement patterns between benign and malignant ovarian tumors (P < 0.05). A total of 30 malignant tumors (30/31) displayed type I TIC, 8 benign tumors (8/13) showed type III TIC, and significant differences were found in TIC type between malignant and benign ovarian lesions (P < 0.01). Benign ovarian tumors showed lower SI60 (%) and slope ratio, as well as significantly prolonged TTP20, compared to malignant ovarian tumors (all P < 0.01). The microvessel count (MVC) of malignant tumors was significantly higher than that of benign tumors (P < 0.05). Receiver operating characteristic (ROC) curve analyses revealed that DCE-MRI provided an optimal diagnostic performance with threshold values of SI60 at 83.40 %, TTP200 at 77.65 s, and slope ratio at 4.12. These findings revealed that DCE-MRI provides critical information required for differential diagnosis of malignant and benign ovarian lesions.


Magnetic resonance imaging Dynamic contrast-enhanced magnetic resonance imaging Ovarian lesions Enhancement Time-signal intensity curve 



We would like to acknowledge the helpful comments on this paper received from our reviewers.

Conflicts of interest



  1. 1.
    Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin. 2013;63(1):11–30.CrossRefPubMedGoogle Scholar
  2. 2.
    Chornokur G, Amankwah EK, Schildkraut JM, Phelan CM. Global ovarian cancer health disparities. Gynecol Oncol. 2013;129(1):258–64.CrossRefPubMedGoogle Scholar
  3. 3.
    Lowe KA, Chia VM, Taylor A, O’Malley C, Kelsh M, Mohamed M, et al. An international assessment of ovarian cancer incidence and mortality. Gynecol Oncol. 2013;130(1):107–14.CrossRefPubMedGoogle Scholar
  4. 4.
    Chiang YC, Chen CA, Chiang CJ, Hsu TH, Lin MC, You SL, et al. Trends in incidence and survival outcome of epithelial ovarian cancer: 30-year national population-based registry in Taiwan. J Gynecol Oncol. 2013;24(4):342–51.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Wong KH, Mang OW, Au KH, Law SC. Incidence, mortality, and survival trends of ovarian cancer in Hong Kong, 1997 to 2006: a population-based study. Hong Kong Med J. 2012;18(6):466–74.PubMedGoogle Scholar
  6. 6.
    Lutz AM, Willmann JK, Drescher CW, Ray P, Cochran FV, Urban N, et al. Early diagnosis of ovarian carcinoma: is a solution in sight? Radiology. 2011;259(2):329–45.CrossRefPubMedGoogle Scholar
  7. 7.
    Gentry-Maharaj A, Menon U. Screening for ovarian cancer in the general population. Best Pract Res Clin Obstet Gynaecol. 2012;26(2):243–56.CrossRefPubMedGoogle Scholar
  8. 8.
    Cesario S. Advances in the early detection of ovarian cancer: how to hear the whispers early. Nurs Womens Health. 2010;14(3):222–34.CrossRefPubMedGoogle Scholar
  9. 9.
    Medeiros LR, Rosa DD, da Rosa MI, Bozzetti MC. Accuracy of ultrasonography with color Doppler in ovarian tumor: a systematic quantitative review. Int J Gynecol Cancer. 2009;19(7):1214–20.CrossRefPubMedGoogle Scholar
  10. 10.
    Nam EJ, Yun MJ, Oh YT, Kim JW, Kim JH, Kim S, et al. Diagnosis and staging of primary ovarian cancer: correlation between PET/CT, Doppler US, and CT or MRI. Gynecol Oncol. 2010;116(3):389–94.CrossRefPubMedGoogle Scholar
  11. 11.
    Yuan Y, Gu ZX, Tao XF, Liu SY. Computer tomography, magnetic resonance imaging, and positron emission tomography or positron emission tomography/computer tomography for detection of metastatic lymph nodes in patients with ovarian cancer: a meta-analysis. Eur J Radiol. 2012;81(5):1002–6.CrossRefPubMedGoogle Scholar
  12. 12.
    Medeiros LR, Freitas LB, Rosa DD, Silva FR, Silva LS, Birtencourt LT, et al. Accuracy of magnetic resonance imaging in ovarian tumor: a systematic quantitative review. Am J Obstet Gynecol. 2011;204(1):67–e1-10.CrossRefPubMedGoogle Scholar
  13. 13.
    Bazot M, Darai E, Nassar-Slaba J, Lafont C, Thomassin-Naggara I. Value of magnetic resonance imaging for the diagnosis of ovarian tumors: a review. J Comput Assist Tomogr. 2008;32(5):712–23.CrossRefPubMedGoogle Scholar
  14. 14.
    Sala E, Rockall A, Rangarajan D, Kubik-Huch RA. The role of dynamic contrast-enhanced and diffusion weighted magnetic resonance imaging in the female pelvis. Eur J Radiol. 2010;76(3):367–85.CrossRefPubMedGoogle Scholar
  15. 15.
    Heye T, Davenport MS, Horvath JJ, Feuerlein S, Breault SR, Bashir MR, et al. Reproducibility of dynamic contrast-enhanced MR imaging. Part I. Perfusion characteristics in the female pelvis by using multiple computer-aided diagnosis perfusion analysis solutions. Radiology. 2013;266(3):801–11.CrossRefPubMedGoogle Scholar
  16. 16.
    Yankeelov TE, Gore JC. Dynamic contrast enhanced magnetic resonance imaging in oncology: theory, data acquisition, analysis, and examples. Curr Med Imaging Rev. 2009;3(2):91–107.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Cuenod CA, Balvay D. Perfusion and vascular permeability: basic concepts and measurement in DCE-CT and DCE-MRI. Diagn Interv Imaging. 2013;94(12):1187–204.CrossRefPubMedGoogle Scholar
  18. 18.
    Tofts PS. T1-weighted DCE imaging concepts: modelling, acquisition and analysis. Signal. 2010;500(450):400.Google Scholar
  19. 19.
    Kyriazi S, Kaye SB, deSouza NM. Imaging ovarian cancer and peritoneal metastases—current and emerging techniques. Nat Rev Clin Oncol. 2010;7(7):381–93.CrossRefPubMedGoogle Scholar
  20. 20.
    Chen W, Giger ML, Bick U, Newstead GM. Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI. Med Phys. 2006;33(8):2878–87.CrossRefPubMedGoogle Scholar
  21. 21.
    Do RK, Rusinek H, Taouli B. Dynamic contrast-enhanced MR imaging of the liver: current status and future directions. Magn Reson Imaging Clin N Am. 2009;17(2):339–49.CrossRefPubMedGoogle Scholar
  22. 22.
    Moon M, Cornfeld D, Weinreb J. Dynamic contrast-enhanced breast MR imaging. Magn Reson Imaging Clin N Am. 2009;17(2):351–62.CrossRefPubMedGoogle Scholar
  23. 23.
    Thomassin-Naggara I, Cuenod CA, Darai E, Marsault C, Bazot M. Dynamic contrast-enhanced MR imaging of ovarian neoplasms: current status and future perspectives. Magn Reson Imaging Clin N Am. 2008;16(4):661–72. ix.CrossRefPubMedGoogle Scholar
  24. 24.
    Thomassin-Naggara I, Darai E, Nassar-Slaba J, Cortez A, Marsault C, Bazot M. Value of dynamic enhanced magnetic resonance imaging for distinguishing between ovarian fibroma and subserous uterine leiomyoma. J Comput Assist Tomogr. 2007;31(2):236–42.CrossRefPubMedGoogle Scholar
  25. 25.
    Pannu HK, Ma W, Zabor EC, Moskowitz CS, Barakat RR, Hricak H. Enhancement of ovarian malignancy on clinical contrast enhanced MRI studies. ISRN Obstet Gynecol. 2013;2013:979345.CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Glas J, Seiderer J, Bues S, Stallhofer J, Fries C, Olszak T, et al. IRGM variants and susceptibility to inflammatory bowel disease in the German population. PLoS One. 2013;8(1):e54338.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Chase DM, Sill MW, Monk BJ, Chambers MD, Darcy KM, Han ES, et al. Changes in tumor blood flow as measured by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may predict activity of single agent bevacizumab in recurrent epithelial ovarian (EOC) and primary peritoneal cancer (PPC) patients: an exploratory analysis of a gynecologic oncology group phase II study. Gynecol Oncol. 2012;126(3):375–80.CrossRefPubMedGoogle Scholar
  28. 28.
    Priest AN, Gill AB, Kataoka M, McLean MA, Joubert I, Graves MJ, et al. Dynamic contrast-enhanced MRI in ovarian cancer: initial experience at 3 tesla in primary and metastatic disease. Magn Reson Med. 2010;63(4):1044–9.CrossRefPubMedGoogle Scholar
  29. 29.
    Welti J, Loges S, Dimmeler S, Carmeliet P. Recent molecular discoveries in angiogenesis and antiangiogenic therapies in cancer. J Clin Invest. 2013;123(8):3190–200.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Yang J, Kim JH, Im GH, Heo H, Yoon S, Lee J, et al. Evaluation of antiangiogenic effects of a new synthetic candidate drug KR-31831 on xenografted ovarian carcinoma using dynamic contrast enhanced MRI. Korean J Radiol. 2011;12(5):602–10.CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Dilks P, Narayanan P, Reznek R, Sahdev A, Rockall A. Can quantitative dynamic contrast-enhanced MRI independently characterize an ovarian mass? Radiology. 2008;20(9):2176–83. 32.Google Scholar
  32. 32.
    Thomassin-Naggara I, Bazot M, Darai E, Callard P, Thomassin J, Cuenod CA. Epithelial ovarian tumors: value of dynamic contrast-enhanced MR imaging and correlation with tumor angiogenesis. Radiology. 2008;248(1):148–59.CrossRefPubMedGoogle Scholar
  33. 33.
    Bernardin L, Dilks P, Liyanage S, Miquel ME, Sahdev A, Rockall A. Effectiveness of semi-quantitative multiphase dynamic contrast-enhanced MRI as a predictor of malignancy in complex adnexal masses: radiological and pathological correlation. Eur Radiol. 2012;22(4):880–90.CrossRefPubMedGoogle Scholar
  34. 34.
    Thomassin-Naggara I, Darai E, Cuenod CA, Rouzier R, Callard P, Bazot M. Dynamic contrast-enhanced magnetic resonance imaging: a useful tool for characterizing ovarian epithelial tumors. J Magn Reson Imaging. 2008;28(1):111–20.CrossRefPubMedGoogle Scholar
  35. 35.
    Inan N, Arslan A, Akansel G, Anik Y, Balci NC, Demirci A. Dynamic contrast enhanced MRI in the differential diagnosis of adrenal adenomas and malignant adrenal masses. Eur J Radiol. 2008;65(1):154–62.CrossRefPubMedGoogle Scholar
  36. 36.
    Fukunaga T, Fujii S, Inoue C, Kato A, Chikumi J, Kaminou T, et al. Accuracy of semiquantitative dynamic contrast-enhanced mri for differentiating type II from type I endometrial carcinoma. J Magn Reson Imaging 2014. doi: 10.1002/jmri.24730
  37. 37.
    Chang YC, Huang YH, Huang CS, Chang PK, Chen JH, Chang RF. Classification of breast mass lesions using model-based analysis of the characteristic kinetic curve derived from fuzzy c-means clustering. Magn Reson Imaging. 2012;30(3):312–22.CrossRefPubMedGoogle Scholar
  38. 38.
    Onxley JD, Yoo DS, Muradyan N, MacFall JR, Brizel DM, Craciunescu OI. Comprehensive population-averaged arterial input function for dynamic contrast-enhanced vmagnetic resonance imaging of head and neck cancer. Int J Radiat Oncol Biol Phys. 2014;89(3):658–65.CrossRefPubMedGoogle Scholar
  39. 39.
    Hansford BG, Karademir I, Peng Y, Jiang Y, Karczmar G, Thomas S, et al. Dynamic contrast-enhanced MR imaging features of the normal central zone of the prostate. Acad Radiol. 2014;21(5):569–77.CrossRefPubMedGoogle Scholar
  40. 40.
    Park MY, Jee WH, Kim SK, Lee SY, Jung JY. Preliminary experience using dynamic MRI at 3.0 Tesla for evaluation of soft tissue tumors. Korean J Radiol. 2013;14(1):102–9.CrossRefPubMedGoogle Scholar
  41. 41.
    Poncelet E, Delpierre C, Kerdraon O, Lucot JP, Collinet P, Bazot M. Value of dynamic contrast-enhanced MRI for tissue characterization of ovarian teratomas: correlation with histopathology. Clin Radiol. 2013;68(9):909–16.CrossRefPubMedGoogle Scholar
  42. 42.
    Hak S, Cebulla J, Huuse EM, Davies Cde L, Mulder WJ, Larsson HB, et al. Periodicity in tumor vasculature targeting kinetics of ligand-functionalized nanoparticles studied by dynamic contrast enhanced magnetic resonance imaging and intravital microscopy. Angiogenesis. 2014;17(1):93–107.CrossRefPubMedGoogle Scholar
  43. 43.
    Padhani AR, Dzik-Jurasz A. Perfusion MR imaging of extracranial tumor angiogenesis. Top Magn Reson Imaging. 2004;15(1):41–57.CrossRefPubMedGoogle Scholar
  44. 44.
    Cuenod CA, Fournier L, Balvay D, Guinebretiere JM. Tumor angiogenesis: pathophysiology and implications for contrast-enhanced MRI and CT assessment. Abdom Imaging. 2006;31(2):188–93.CrossRefPubMedGoogle Scholar
  45. 45.
    Padhani AR, Leach MO. Antivascular cancer treatments: functional assessments by dynamic contrast-enhanced magnetic resonance imaging. Abdom Imaging. 2005;30(3):324–41.CrossRefPubMedGoogle Scholar
  46. 46.
    Tang HS, Feng YJ, Yao LQ. Angiogenesis, vasculogenesis, and vasculogenic mimicry in ovarian cancer. Int J Gynecol Cancer. 2009;19(4):605–10.CrossRefPubMedGoogle Scholar
  47. 47.
    Pickles MD, Manton DJ, Lowry M, Turnbull LW. Prognostic value of pre-treatment DCE-MRI parameters in predicting disease free and overall survival for breast cancer patients undergoing neoadjuvant chemotherapy. Eur J Radiol. 2009;71(3):498–505.CrossRefPubMedGoogle Scholar
  48. 48.
    Jackson A, O’Connor JP, Parker GJ, Jayson GC. Imaging tumor vascular heterogeneity and angiogenesis using dynamic contrast-enhanced magnetic resonance imaging. Clin Cancer Res. 2007;13(12):3449–59.CrossRefPubMedGoogle Scholar
  49. 49.
    Yang X, Knopp MV. Quantifying tumor vascular heterogeneity with dynamic contrast-enhanced magnetic resonance imaging: a review. J Biomed Biotechnol. 2011;2011:732848.PubMedPubMedCentralGoogle Scholar
  50. 50.
    Leach MO, Morgan B, Tofts PS, Buckley DL, Huang W, Horsfield MA, et al. Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging. Eur Radiol. 2012;22(7):1451–64.CrossRefPubMedGoogle Scholar

Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2015

Authors and Affiliations

  • Xian Li
    • 1
    • 4
  • Jun-Li Hu
    • 2
  • Lai-Min Zhu
    • 3
  • Xin-Hai Sun
    • 3
  • Hua-Qiang Sheng
    • 3
  • Ning Zhai
    • 3
  • Xi-Bin Hu
    • 3
  • Chu-Ran Sun
    • 4
  • Bin Zhao
    • 1
  1. 1.Shandong Medical Imaging Research InstituteShandong UniversityJinanChina
  2. 2.Department of UltrasonographyAffiliated Hospital of Jining Medical UniversityJiningChina
  3. 3.Department of RadiologyAffiliated Hospital of Jining Medical UniversityJiningChina
  4. 4.Department of RadiologyJining Medical UniversityJiningChina

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