La radiologia medica

, Volume 121, Issue 11, pp 838–846 | Cite as

Evaluation of diffusion-weighted imaging (DWI) and MR spectroscopy (MRS) as early response biomarkers in cervical cancer patients

  • Stefania RizzoEmail author
  • Valentina Buscarino
  • Daniela Origgi
  • Paul Summers
  • Sara Raimondi
  • Roberta Lazzari
  • Fabio Landoni
  • Massimo Bellomi



To prospectively assess whether choline levels and Apparent Diffusion Coefficient (ADC) values within cervical cancers before, during, and after non-surgical therapy are predictive of tumour response.

Patients and methods

Patients undergoing MR examination for staging of cervical cancer, candidate for non-surgical therapy, were prospectively enrolled. According to the status at the end of therapies, patients were divided into responders and non-responders. The final outcome after a 5-year follow-up was classified as No Evidence of Disease (NED) or Progression of Disease (PD). Baseline values of mean ADC and Cho/H2O were compared between responders and non-responders, as well as between patients with NED and PD. The percent variation of ADC and Cho/H2O values over time was compared. P values <0.05 were considered significant.


16 patients were included. There was no significant difference at baseline between responders (n = 12) and non-responders (n = 4), nor between NED (n = 11) PD patients (n = 5), in ADC values and Cho/H2O ratio. There was no significant difference in percent variation of ADC values and of Cho/H2O, comparing responders and non-responders. There was a significant increase in absolute values of ADC from the initial to mid-therapy MRI (p = 0.0001), while Cho/H2O was stable (p value: 0.61). In the four non-responders, the ADC increase was not significant (p value: 0.25), while it was significant in the 11 responders (p value: 0.001). Values of spectroscopy were stable in both responders and non-responders.


High increases of ADC values from baseline to mid-therapy MR reflect response to therapies. There were no significant variations in choline/water ratios over time.


MR spectroscopy DWI Cervical cancer Response biomarkers 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Statement of human rights

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


  1. 1.
    Siegel RL, Miller KD, Jemal A (2015) CA Cancer J Clin. Jan-Feb;65(1):5-29. doi: 10.3322/caac.21254 Cancer statistics, 2015
  2. 2.
    Klostergaard J, Parga K, Raptis RG (2010) Current and future applications of magnetic resonance imaging (MRI) to breast and ovarian cancer patient management. PR Health Sci J 29(3):223–231Google Scholar
  3. 3.
    Koh DM, Collins DJ (2007) Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 188(6):1622–1635CrossRefPubMedGoogle Scholar
  4. 4.
    Heo SH, Shin SS, Kim JW, Lim HS, Jeong YY, Kang WD et al (2013) 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 J Radiol 14(4):616–625CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Shah N, Sattar A, Benanti M, Hollander S, Cheuck L (2006) Magnetic resonance spectroscopy as an imaging tool for cancer: a review of the literature. J Am Osteopath Assoc 106:23–27PubMedGoogle Scholar
  6. 6.
    Pinker K, Stadlbauer A, Bogner W, Gruber S, Helbich TH (2012) Molecular imaging of cancer: MR spectroscopy and beyond. Eur J Radiol Mar;81(3):566–577Google Scholar
  7. 7.
    Payne GS, Schmidt M, Morgan VA, Giles S, Bridges J, Ind T, DeSouza NM (2010) Evaluation of magnetic resonance diffusion and spectroscopy measurements as predictive biomarkers in stage 1 cervical cancer. Gynecol Oncol Feb;116(2):246–52Google Scholar
  8. 8.
    Schwarz AJ, Maisey NR, Collins DJ, Cunningham D, Huddart R, Leach MO (2002) Early in vivo detection of metabolic response: a pilot study of 1H MR spectroscopy in extracranial lymphoma and germ cell tumours. Br J Radiol Dec;75(900): 959–66Google Scholar
  9. 9.
    Haddadin IS, McIntosh A, Meisamy S, Corum C, Styczynski Snyder AL, Powell NJ, et al (2009) Metabolite quantification and high-field MRS in breast cancer. NMR Biomed 22(1):65–76Google Scholar
  10. 10.
    Meisamy S, Bolan PJ, Baker EH et al (2004) Neoadjuvant chemotherapy of locally advanced breast cancer: predicting response with in vivo (1)H MR spectroscopy—a pilot study at 4 T. Radiology 233(2):424–431CrossRefPubMedGoogle Scholar
  11. 11.
    Pecorelli S, Zigliani L, Odicino F (2009) Revised FIGO staging for carcinoma of the cervix. Int J Gynaecol Obstet 105:107–108CrossRefPubMedGoogle Scholar
  12. 12.
    Zhao M, Pipe JG, Bonnett J, Evelhoch JL (1996) Early detection of treatment response by diffusion-weighted 1H-NMR spectroscopy in a murine tumour in vivo. Br J Cancer 73:61–64CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Huang MQ, Nelson DS, Pickup S, Qiao H, Delikatny EJ, Poptani H et al (2007) In vivo monitoring response to chemotherapy of human diffuse large B-cell lymphoma xenografts in SCID mice by 1H and 31P MRS. Acad Radiol 14:1531–1539CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Morse DL, Raghunand N, Sadarangani P, Murthi S, Job C, Day S et al (2007) Response of choline metabolites to docetaxel therapy is quantified in vivo by localized (31)P MRS of human breast cancer xenografts and in vitro by high-resolution (31)P NMR spectroscopy of cell extracts. Magn Reson Med 58:270–280CrossRefPubMedGoogle Scholar
  15. 15.
    Manton DJ, Chaturvedi A, Hubbard A, Lind MJ, Lowry M, Maraveyas A et al (2006) Neoadjuvant chemotherapy in breast cancer: early response prediction with quantitative MR imaging and spectroscopy. Br J Cancer 94:427–435CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Wu B, Peng WJ, Wang PJ, Gu YJ, Li WT, Zhou LP et al (2006) In vivo 1H magnetic resonance spectroscopy in evaluation of hepatocellular carcinoma and its early response to transcatheter arterial chemoembolization. Chin Med Sci J 21:258–264PubMedGoogle Scholar
  17. 17.
    Preul MC, Caramanos Z, Villemure JG, Shenouda G, LeBlanc R, Langleben A et al (2000) Using proton magnetic resonance spectroscopic imaging to predict in vivo the response of recurrent malignant gliomas to tamoxifen chemotherapy. Neurosurgery 46:306–318CrossRefPubMedGoogle Scholar
  18. 18.
    Booth SJ, Pickles MD, Turnbull LW (2009) In vivo magnetic resonance spectroscopy of gynaecological tumours at 3.0 Tesla. BJOG 116(2):300–303CrossRefPubMedGoogle Scholar
  19. 19.
    Mahon MM, Cox IJ, Dina R et al (2004) (1) H magnetic resonance spectroscopy of preinvasive and invasive cervical cancer: in vivo-ex vivo profiles and effect of tumor load. J Magn Reson Imaging 19(3):356–364CrossRefPubMedGoogle Scholar
  20. 20.
    deSouza NM, McIndoe GA, Soutter WP, Krausz T, Chui KM, Hughes C et al (1998) Value of magnetic resonance imaging with an endovaginal receiver coil in the preoperative assessment of Stage I and IIa cervical neoplasia. Br J Obstet Gynaecol 105(5):500–507CrossRefPubMedGoogle Scholar
  21. 21.
    Allen JR, Prost RW, Griffith OW, Erickson SJ, Erickson BA (2001) In vivo proton (H1) magnetic resonance spectroscopy for cervical carcinoma. Am J Clin Oncol 24(5):522–529CrossRefPubMedGoogle Scholar
  22. 22.
    Zhu M, Fischl AS, Trowbridge MA, Shannon HE (2012) Reproducibility of total choline/water ratios in mouse U87MG xenograft tumors by 1H-MRS. J Magn Reson Imaging 36(2):459–467CrossRefPubMedGoogle Scholar
  23. 23.
    Hamstra DA, Rehemtulla A, Ross BD (2007) Diffusion magnetic resonance imaging: abiomarker for treatment response in oncology. J Clin Oncol 25:4104–4109CrossRefPubMedGoogle Scholar
  24. 24.
    Koh DM, Padhani AR (2006) Diffusion-weighted MRI. A new functional clinical technique for tumour imaging. Br J Radiol 79:633–635CrossRefPubMedGoogle Scholar
  25. 25.
    Pickles MD, Gibbs P, Lowry M, Turnbull LW (2006) Diffusion changes precede sizereduction in neoadjuvant treatment of breast cancer. Magn Reson Imaging 24:843–847CrossRefPubMedGoogle Scholar
  26. 26.
    Deng J, Miller FH, Rhee TK, Sato KT, Mulcahy MF, Kulik LM et al (2006) Diffusion weighted MR imaging for determination of hepatocellular carcinoma response toyttrium-90 radioembolization. J Vasc Interv Radiol 17:1195–1200CrossRefPubMedGoogle Scholar
  27. 27.
    Naganawa S, Sato C, Kumada H, Ishigaki T, Miura S, Takizawa O (2005) Apparent diffusion coefficient in cervical cancer of the uterus: comparison with the normal uterine cervix. Eur Radiol 15:71–78CrossRefPubMedGoogle Scholar
  28. 28.
    Rizzo S, Summers P, Raimondi S, Belmonte M, Maniglio M, Landoni F, Colombo N, Bellomi M (2011) Diffusion-weighted MR imaging in assessing cervical tumour response to nonsurgical therapy. Radiol Med 116(5):766–780CrossRefPubMedGoogle Scholar
  29. 29.
    McVeigh PZ, Syed AM, Milosevic M, Fyles A, Haider MA (2008) Diffusion weighted MRI in cervical cancer. Eur Radiol 18:1058–1064CrossRefPubMedGoogle Scholar
  30. 30.
    Harry VN, Semple SI, Gilbert FJ, Parkin DE (2008) Diffusion-weighted magnetic resonance imaging in the early detection of response to chemoradiation in cervical cancer. Gynecol Oncol 111(2):213–220CrossRefPubMedGoogle Scholar
  31. 31.
    Das S, Chandramohan A (2015) Rami Reddy JK, Mukhopadhyay S, Kumar RM, Isiah R, John S, Oommen R, Jeyaseelan V. Role of conventional and diffusion weighted MRI in predicting treatment response after low dose radiation and chemotherapy in locally advanced carcinoma cervix. Radiother Oncol 117(2):288–293CrossRefPubMedGoogle Scholar
  32. 32.
    SEER Stat Fact Sheets: Cervix Uteri Cancer (2016). Accessed 12/05/2016
  33. 33.
    Osman M (2014) The role of neoadjuvant chemotherapy in the management of locally advanced cervix cancer: a systematic review.Oncol Rev. Sep 23;8(2):250. doi: 10.4081/oncol.2014.250. eCollection 2014
  34. 34.
    Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Italian Society of Medical Radiology 2016

Authors and Affiliations

  • Stefania Rizzo
    • 1
    Email author
  • Valentina Buscarino
    • 2
  • Daniela Origgi
    • 3
  • Paul Summers
    • 1
  • Sara Raimondi
    • 4
  • Roberta Lazzari
    • 5
  • Fabio Landoni
    • 6
  • Massimo Bellomi
    • 1
    • 7
  1. 1.Department of RadiologyEuropean Institute of OncologyMilanItaly
  2. 2.Department of Health SciencesUniversity of MilanMilanItaly
  3. 3.Medical PhysicsEuropean Institute of OncologyMilanItaly
  4. 4.Division of Epidemiology and BiostatisticsEuropean Institute of OncologyMilanItaly
  5. 5.Department of RadiotherapyEuropean Institute of OncologyMilanItaly
  6. 6.Department of GynaecologyEuropean Institute of OncologyMilanItaly
  7. 7.Department of OncologyUniversity of MilanMilanItaly

Personalised recommendations