Abdominal Radiology

, Volume 44, Issue 7, pp 2557–2571 | Cite as

MRI of cervical cancer with a surgical perspective: staging, prognostic implications and pitfalls

  • Patricia BalcacerEmail author
  • Arvind Shergill
  • Babak Litkouhi


Learning objectives

Magnetic resonance imaging (MRI) of the pelvis is the most reliable imaging modality for staging, treatment planning, and follow-up of cervical cancer; and its findings may now be incorporated into the International Federation of Gynecology and Obstetrics Federation (FIGO) 2018 clinical staging of cervical cancer. It is imperative that radiologists are familiar with the imaging appearance of the different stages of cervical cancer as well as the post-treatment changes and imaging pitfalls given the respective clinical manifestations, treatment regimens, and prognosis of an accurate diagnosis. In addition to the different stages of cervical cancer, we address the imaging techniques for diagnosis, staging and treatment implications as well as the changes of the new FIGO staging system.


The use of MRI to diagnose and stage cervical cancer is steadily increasing and the new FIGO stagi ng system, previously based on clinical examination, now allows the staging or change of staging based on the imaging findings. MRI can evaluate the extent of disease because of its excellent contrast resolution for pelvic tissues and organs, high accuracy and detailed elaboration of the cervical/uterovaginal anatomy.


Relevant anatomy, including normal MRI appearance of the cervix, parametria and pelvic ligaments; different stages of cervical cancer on MRI with prognostic and therapeutic implications; MRI sequences, other imaging modalities used in the staging and follow-up, treatment of different stages and the appearance of the cervix and cervical cancer post-treatment. Since clinical implications and therapeutic strategies for cervical cancer treatment vary tremendously according to degree of tumor extension, familiarity with relevant MRI techniques and findings is essential for radiologists.


It is important that radiologists interpreting pelvic MRI are aware with the different stages of cervical cancer to provide useful information regarding treatment and prognosis. Pitfalls regarding the interpretation of tumor extension can interfere with an accurate diagnosis and have significant therapeutic implications.


Cervical cancer FIGO cervical staging Cervical cancer staging 



  1. 1.
    Bhatla N, Berek JS, Cuello Fredes M, Denny LA, Grenman S, Karunaratne K, et al. Revised FIGO staging for carcinoma of the cervix uteri. Int J Gynaecol Obstet. 2019 Jan 17;68(16-20):394.Google Scholar
  2. 2.
    Ferlay J, Shin H-R, Bray F, Forman D, Mathers C, Parkin DM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. Wiley Subscription Services, Inc., A Wiley Company; 2010 Jun 17;127(12):2893–917.Google Scholar
  3. 3.
    Herrington CS. Recent advances in molecular gynaecological pathology. Histopathology. Blackwell Publishing Ltd; 2009 Sep;55(3):243–9.Google Scholar
  4. 4.
    Li N, Franceschi S, Howell-Jones R, Snijders PJF, Clifford GM. Human papillomavirus type distribution in 30,848 invasive cervical cancers worldwide: Variation by geographical region, histological type and year of publication. Int J Cancer. Wiley Subscription Services, Inc., A Wiley Company; 2011 Feb 15;128(4):927–35.Google Scholar
  5. 5.
    Wingo SN, Gallardo TD, Akbay EA, Liang M-C, Contreras CM, Boren T, et al. Somatic LKB1 mutations promote cervical cancer progression. Aziz SA, editor. PLOS ONE. 2009;4(4):e5137.Google Scholar
  6. 6.
    Bahrami A, Hasanzadeh M, Shahidsales S, Farazestanian M, Hassanian SM, Moetamani Ahmadi M, et al. Genetic susceptibility in cervical cancer: From bench to bedside. J Cell Physiol. 2018 Mar;233(3):1929–39.Google Scholar
  7. 7.
    Kurman RJ. Blaustein’s Pathology of the Female Genital Tract. Kurman RJ, editor. New York, NY: Springer Science & Business Media; 2011, p155-191.Google Scholar
  8. 8.
    Choi SH, Kim SH, Choi HJ, Park BK, Lee HJ. Preoperative magnetic resonance imaging staging of uterine cervical carcinoma: results of prospective study. Journal of Computer Assisted Tomography. 2004 Sep;28(5):620–7.Google Scholar
  9. 9.
    Ma DJ, Zhu J-M, Grigsby PW. Change in T2-fat saturation MRI correlates with outcome in cervical cancer patients. Int J Radiat Oncol Biol Phys. 2011 Dec 1;81(5):e707–12.Google Scholar
  10. 10.
    Thomsen HS. Guidelines for Contrast Media from the European Society of Urogenital Radiology. American Journal of Roentgenology. American Roentgen Ray Society; 2003 Dec;181(6):1463–71.Google Scholar
  11. 11.
    Jalaguier-Coudray A, Villard-Mahjoub R, Delouche A, Delarbre B, Lambaudie E, Houvenaeghel G, et al. Value of Dynamic Contrast-enhanced and Diffusion-weighted MR Imaging in the Detection of Pathologic Complete Response in Cervical Cancer after Neoadjuvant Therapy: A Retrospective Observational Study. Radiology. Radiological Society of North America; 2017 Aug;284(2):432–42.Google Scholar
  12. 12.
    Vincens E, Balleyguier C, Rey A, Uzan C, Zareski E, Gouy S, et al. Accuracy of magnetic resonance imaging in predicting residual disease in patients treated for stage IB2/II cervical carcinoma with chemoradiation therapy. Cancer. 2008 Oct 15;113(8):2158–65.Google Scholar
  13. 13.
    Dhoot NM, Kumar V, Shinagare A, Kataki AC, Barmon D, Bhuyan U. Evaluation of carcinoma cervix using magnetic resonance imaging: correlation with clinical FIGO staging and impact on management. J Med Imaging Radiat Oncol. Blackwell Publishing Asia; 2012 Feb;56(1):58–65.Google Scholar
  14. 14.
    Houvenaeghel G, Lelievre L, Buttarelli M, Jacquemier J, Carcopino X, Viens P, et al. Contribution of surgery in patients with bulky residual disease after chemoradiation for advanced cervical carcinoma. Eur J Surg Oncol. 2007 May;33(4):498–503.Google Scholar
  15. 15.
    Balleyguier C, Sala E, Da Cunha T, Bergman A, Brkljacic B, Danza F, et al. Staging of uterine cervical cancer with MRI: guidelines of the European Society of Urogenital Radiology. Eur Radiol. Springer-Verlag; 2011 May;21(5):1102–10.Google Scholar
  16. 16.
    Lin G, Ho K-C, Wang J-J, Ng K-K, Wai Y-Y, Chen Y-T, et al. Detection of lymph node metastasis in cervical and uterine cancers by diffusion-weighted magnetic resonance imaging at 3T. J Magn Reson Imaging. Wiley Subscription Services, Inc., A Wiley Company; 2008 Jul;28(1):128–35.Google Scholar
  17. 17.
    Malayeri AA, Khouli El RH, Zaheer A, Jacobs MA, Corona-Villalobos CP, Kamel IR, et al. Principles and applications of diffusion-weighted imaging in cancer detection, staging, and treatment follow-up. RadioGraphics. Radiological Society of North America; 2011 Oct;31(6):1773–91.Google Scholar
  18. 18.
    NaNakamura K, Joja I, Nagasaka T, Fukushima C, Kusumoto T, Seki N, et al. The mean apparent diffusion coefficient value (ADCmean) on primary cervical cancer is a predictive marker for disease recurrence. Gynecologic Oncology. 2012 Dec;127(3):478–83.Google Scholar
  19. 19.
    McVeigh PZ, Syed AM, Milosevic M, Fyles A, Haider MA. Diffusion-weighted MRI in cervical cancer. Eur Radiol. Springer-Verlag; 2008 Jan 12;18(5):1058–64.Google Scholar
  20. 20.
    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. Springer-Verlag; 2004 Nov 5;15(1):71–8.Google Scholar
  21. 21.
    Heo SH, Shin SS, Kim JW, Lim HS, Jeong YY, Kang WD, et al. Pre-Treatment Diffusion-Weighted MR Imaging for Predicting Tumor Recurrence in Uterine Cervical Cancer Treated with Concurrent Chemoradiation: Value of Histogram Analysis of Apparent Diffusion Coefficients. Korean Journal of Radiology. 2013;14(4):616.Google Scholar
  22. 22.
    Thomeer MG, Gerestein C, Spronk S, van Doorn HC, van der Ham E, Hunink MG. Clinical examination versus magnetic resonance imaging in the pretreatment staging of cervical carcinoma: systematic review and meta-analysis. Eur Radiol. Springer-Verlag; 2013 Jul;23(7):2005–18.Google Scholar
  23. 23.
    Kraljević Z, Visković K, Ledinsky M, Zadravec D, Grbavac I, Bilandzija M, et al. Primary uterine cervical cancer: correlation of preoperative magnetic resonance imaging and clinical staging (FIGO) with histopathology findings. Coll Antropol. 2013 Jun;37(2):561–8.Google Scholar
  24. 24.
    Kim M, Suh DH, Kim K, Lee HJ, Kim YB, No JH. Magnetic Resonance Imaging as a Valuable Tool for Predicting Parametrial Invasion in Stage IB1 to IIA2 Cervical Cancer. Int J Gynecol Cancer. 2017 Feb;27(2):332–8.Google Scholar
  25. 25.
    Atcı N, Özgür T, Öztürk F, Dolapçıoğlu KS. Utility of intravaginal ultrasound gel for local staging of cervical carcinoma on MRI. Clin Imaging. 2016 Dec;40(6):1104–7.Google Scholar
  26. 26.
    Csutak C, Ordeanu C, Nagy VM, Pop DC, Bolboaca SD, Badea R, et al. A prospective study of the value of pre- and post-treatment magnetic resonance imaging examinations for advanced cervical cancer. Clujul Med. 2016;89(3):410–8.Google Scholar
  27. 27.
    Gill BS, Kim H, Houser CJ, Kelley JL III, Sukumvanich P, Edwards RP, et al. Extended Clinical Outcomes of 3D High-Dose-Rate Intracavitary Brachytherapy with MRI-Based Planning for Treatment of Cervical Cancer. Brachytherapy. 2014 Mar;13:S33.Google Scholar
  28. 28.
    Testa AC, Moro F, Pasciuto T, Moruzzi MC, Di Legge A, Fuoco G, et al. PRospective Imaging of CErvical cancer and neoadjuvant treatment (PRICE) study: role of ultrasound to assess residual tumor in locally advanced cervical cancer patients undergoing chemoradiation and radical surgery. Ultrasound Obstet Gynecol. 2018 Jul;52(1):110–8.Google Scholar
  29. 29.
    Testa AC, Di Legge A, De Blasis I, Moruzzi MC, Bonatti M, Collarino A, et al. Imaging techniques for the evaluation of cervical cancer. Best Practice & Research Clinical Obstetrics & Gynaecology. 2014 Jul;28(5):741–68.Google Scholar
  30. 30.
    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 Dec 20;24(36):5687–94.Google Scholar
  31. 31.
    Rockall AG, Qureshi M, Papadopoulou I, Saso S, Butterfield N, Thomassin-Naggara I, et al. Role of Imaging in Fertility-sparing Treatment of Gynecologic Malignancies. RadioGraphics. Radiological Society of North America; 2016 Nov;36(7):2214–33.Google Scholar
  32. 32.
    Peters WA, Liu PY, Barrett RJ, Stock RJ, Monk BJ, Berek JS, et al. Concurrent chemotherapy and pelvic radiation therapy compared with pelvic radiation therapy alone as adjuvant therapy after radical surgery in high-risk early-stage cancer of the cervix. JCO. 2000 Apr;18(8):1606–13.Google Scholar
  33. 33.
    Matsuo K, Machida H, Mandelbaum RS, Konishi I, Mikami M. Validation of the 2018 FIGO cervical cancer staging system. Gynecologic Oncology. 2019 Jan;152(1):87–93.Google Scholar
  34. 34.
    Kaur H, Silverman PM, Iyer RB, Verschraegen CF, Eifel PJ, Charnsangavej C. Diagnosis, staging, and surveillance of cervical carcinoma. American Journal of Roentgenology. American Roentgen Ray Society; 2003 Jun;180(6):1621–31.Google Scholar
  35. 35.
    Rockall AG, Ghosh S, Alexander-Sefre F, Babar S, Younis MTS, Naz S, et al. Can MRI rule out bladder and rectal invasion in cervical cancer to help select patients for limited EUA? Gynecologic Oncology. 2006 May;101(2):244–9.Google Scholar
  36. 36.
    Monk BJ, Tian C, Rose PG, Lanciano R. Which clinical/pathologic factors matter in the era of chemoradiation as treatment for locally advanced cervical carcinoma? Analysis of two Gynecologic Oncology Group (GOG) trials. Gynecologic Oncology. 2007 May;105(2):427–33.Google Scholar
  37. 37.
    Shen G, Zhou H, Jia Z, Deng H. Diagnostic performance of diffusion-weighted MRI for detection of pelvic metastatic lymph nodes in patients with cervical cancer: a systematic review and meta-analysis. Br J Radiol. The British Institute of Radiology; 2015 Aug;88(1052):20150063.Google Scholar
  38. 38.
    Bouchard-Fortier G, Reade CJ, Covens A. Non-radical surgery for small early-stage cervical cancer. Is it time? Gynecologic Oncology. 2014 Mar;132(3):624–7.Google Scholar
  39. 39.
    Kato R, Hasegawa K, Torii Y, Udagawa Y, Fukasawa I. Factors affecting platinum sensitivity in cervical cancer. Oncol Lett. Spandidos Publications; 2015 Dec;10(6):3591–8.Google Scholar
  40. 40.
    Leblanc E, Narducci F, Frumovitz M, Lesoin A, Castelain B, Baranzelli MC, et al. Therapeutic value of pretherapeutic extraperitoneal laparoscopic staging of locally advanced cervical carcinoma. Gynecologic Oncology. 2007 May;105(2):304–11.Google Scholar
  41. 41.
    Atahan Il, Onal C, Ozyar E, Yiliz F, Selek U, Kose F. Long-term outcome and prognostic factors in patients with cervical carcinoma: a retrospective study. International Journal of Gynecological Cancer. Blackwell Publishing Inc; 2007 Jul;17(4):833–42.Google Scholar
  42. 42.
    Sironi S, Buda A, Picchio M, Perego P, Moreni R, Pellegrino A, et al. Lymph node metastasis in patients with clinical early-stage cervical cancer: detection with integrated FDG PET/CT. Radiology. Radiological Society of North America; 2006 Jan;238(1):272–9.Google Scholar
  43. 43.
    McMahon CJ, Rofsky NM, Pedrosa I. Lymphatic Metastases from Pelvic Tumors: Anatomic Classification, Characterization, and Staging. Radiology. Radiological Society of North America, Inc; 2010 Jan;254(1):31–46.Google Scholar
  44. 44.
    Kim JK, Kim KA, Park B-W, Kim N, Cho K-S. Feasibility of diffusion-weighted imaging in the differentiation of metastatic from nonmetastatic lymph nodes: early experience. J Magn Reson Imaging. 2008 Sep;28(3):714–9.Google Scholar
  45. 45.
    Kim HS, Kim CK, Park BK, Huh SJ, Kim B. Evaluation of therapeutic response to concurrent chemoradiotherapy in patients with cervical cancer using diffusion-weighted MR imaging. J Magn Reson Imaging. 2013 Jan;37(1):187–93.Google Scholar
  46. 46.
    Kuang F, Yan Z, Li H, Feng H. Diagnostic accuracy of diffusion-weighted MRI for differentiation of cervical cancer and benign cervical lesions at 3.0T: Comparison with routine MRI and dynamic contrast-enhanced MRI. J Magn Reson Imaging. John Wiley & Sons, Ltd; 2015 Oct;42(4):1094–9.Google Scholar
  47. 47.
    McEvoy SH, Nougaret S, Abu-Rustum NR, Vargas HA, Sadowski EA, Menias CO, et al. Fertility-sparing for young patients with gynecologic cancer: How MRI can guide patient selection prior to conservative management. Abdominal Radiology. 3rd ed. Springer US; 2017 May 20;42(10):2488–512.Google Scholar
  48. 48.
    Schwarz JK, Rader JS, Huettner PC, Watson MA, Grigsby PW. Molecular Characterization of FDG-PET Metabolic Response in Cervical Cancer. International Journal of Radiation Oncology*Biology*Physics. 2007 Nov;69(3):S115.Google Scholar
  49. 49.
    Mongula JE, Bakers FCH, Vöö S, Lutgens L, van Gorp T, Kruitwagen RFPM, et al. Positron emission tomography-magnetic resonance imaging (PET-MRI) for response assessment after radiation therapy of cervical carcinoma: a pilot study. EJNMMI Res. SpringerOpen; 2018 Jan 2;8(1):1.Google Scholar
  50. 50.
    Siva S, Deb S, Young RJ, Hicks RJ, Callahan J, Bressel M, et al. 18F-FDG PET/CT following chemoradiation of uterine cervix cancer provides powerful prognostic stratification independent of HPV status: a prospective cohort of 105 women with mature survival data. Eur J Nucl Med Mol Imaging. 2015 Nov;42(12):1825–32.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Patricia Balcacer
    • 1
    Email author
  • Arvind Shergill
    • 1
  • Babak Litkouhi
    • 2
  1. 1.Division of Abdominal Imaging, Department of RadiologyBeth Israel Deaconess Medical Center- Harvard Medical SchoolBostonUSA
  2. 2.Department of Obstetrics, Gynecology, and Reproductive SciencesYale School of MedicineNew HavenUSA

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