European Radiology

, Volume 24, Issue 6, pp 1327–1338 | Cite as

MR diffusion imaging for preoperative staging of myometrial invasion in patients with endometrial cancer: a systematic review and meta-analysis

  • Anita Andreano
  • Gilda Rechichi
  • Paola Rebora
  • Sandro Sironi
  • Maria Grazia Valsecchi
  • Stefania Galimberti
Magnetic Resonance



To compare the diagnostic accuracy of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MR imaging in detecting deep myometrial invasion in endometrial cancer, using surgical-pathological staging as reference standard.


After searching a wide range of electronic databases and screening titles/abstracts, we obtained full papers for potentially eligible studies and evaluated according to predefined inclusion criteria. Quality assessment was conducted by adapting the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) checklist. From each study, we extracted information on diagnostic performance of DW and DCE sequences. After exploring heterogeneity, we adopted a bivariate generalized linear mixed model to compare the effect of the two MR sequences jointly on sensitivity and specificity.


Nine studies (442 patients) were considered. Significant evidence of heterogeneity was found only for specificity, both in DW and DCE imaging (I 2  = 70.8 % and 70.6 %). Pooled sensitivity of DW and DCE was 0.86 and specificity did not significantly differ (p = 0.16) between the two sequences (DW = 0.86 and DCE = 0.82). No difference was found between 3-T and 1.5-T MR. There was no evidence of publication bias.


MR diagnostic accuracy in presurgical detection of deep myometrial infiltration in endometrial cancer is high. DCE and DW imaging do not differ in sensitivity and specificity.

Key Points

Myometrial invasion is the most important morphological prognostic feature of endometrial cancer

MR diagnostic accuracy in presurgical detection of deep myometrial infiltration is high

MR examination including T2 and DCE imaging is considered the reference standard

DW imaging has been increasingly employed with heterogeneous results

This meta-analysis shows that DCE and DW do not differ in diagnostic accuracy


Endometrial neoplasms Magnetic resonance imaging Diffusion magnetic resonance imaging Meta-analysis Review 

Abbreviations and acronyms


apparent diffusion coefficient


Akaike information criterion


confidence interval


computed tomography


dynamic contrast-enhanced


diagnostic odds ratio




effective sample size


International Federation of Gynecology and Obstetrics


generalized linear mixed model

LR+ and LR−

positive and negative likelihood ratio


magnetic resonance


Quality Assessment of Diagnostic Accuracy Studies-2


receiver operating characteristic


signal to noise ratio





We thanks Laura Colombo for her thoughtful help during bibliographic research and Liu Xiaoqiu for her translation from Chinese.

The scientific guarantor of this publication is Maria Grazia Valsecchi. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. Three of the authors have significant statistical expertise. Institutional review board approval was not required because the manuscript is a meta-analysis of already published studies and there are no patient level data. Written informed consent was not required for this study because the manuscript is a meta-analysis and there are no patient level data. Methodology: meta-analysis, performed at one institution.

Supplementary material

330_2014_3139_MOESM1_ESM.doc (86 kb)
ESM 1 (DOC 86 kb)


  1. 1.
    Ferlay J, Shin H-R, Bray F, Forman D, Mathers C, Parkin DM (2010) Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer 127:2893–2917PubMedCrossRefGoogle Scholar
  2. 2.
    American Cancer Society (2013) Cancer facts & figures. Accessed 20 Oct 2013
  3. 3.
    Ferlay J, Steliarova-Foucher E, Lortet-Tieulent J et al (2013) Cancer incidence and mortality patterns in Europe: estimates for 40 countries in 2012. Eur J Cancer 49:1374–1403PubMedCrossRefGoogle Scholar
  4. 4.
    Amant F, Mirza MR, Creutzberg CL (2012) Cancer of the corpus uteri. Int J Gynaecol Obstet 119:S110–S117PubMedCrossRefGoogle Scholar
  5. 5.
    Ludwig H (1995) Prognostic factors in endometrial cancer. Int J Gynecol Obstet 49:S1–S7CrossRefGoogle Scholar
  6. 6.
    Larson DM, Connor GP, Broste SK, Krawisz BR, Johnson KK (1996) Prognostic significance of gross myometrial invasion with endometrial cancer. Obstet Gynecol 88:394–398PubMedCrossRefGoogle Scholar
  7. 7.
    Creasman WT, Morrow CP, Bundy BN, Homesley HD, Graham JE, Heller PB (1987) Surgical pathologic spread patterns of endometrial cancer. A Gynecologic Oncology Group Study. Cancer 60:2035–2041PubMedCrossRefGoogle Scholar
  8. 8.
    Kinkel K, Kaji Y, Yu KK, Segal MR, Lu Y, Powell CB et al (1999) Radiologic staging in patients with endometrial cancer: a meta-analysis. Radiology 212:711–718PubMedCrossRefGoogle Scholar
  9. 9.
    Kinkel K, Forstner R, Danza FM et al (2009) Staging of endometrial cancer with MRI: guidelines of the European Society of Urogenital Imaging. Eur Radiol 19:1565–1574PubMedCrossRefGoogle Scholar
  10. 10.
    Hricak H, Stern JL, Fisher MR, Shapeero LG, Winkler ML, Lacey CG (1987) Endometrial carcinoma staging by MR imaging. Radiology 162:297–305PubMedGoogle Scholar
  11. 11.
    Frei KA, Kinkel K, Bonél HM, Lu Y, Zaloudek C, Hricak H (2000) Prediction of deep myometrial invasion in patients with endometrial cancer: clinical utility of contrast-enhanced MR imaging–a meta-analysis and Bayesian analysis. Radiology 216:444–449PubMedCrossRefGoogle Scholar
  12. 12.
    Lee JH, Dubinsky T, Andreotti RF et al (2011) ACR Appropriateness Criteria® pretreatment evaluation and follow-up of endometrial cancer of the uterus. Ultrasound Q 27:139–145PubMedCrossRefGoogle Scholar
  13. 13.
    Hricak H, Hamm B, Semelka RC et al (1991) Carcinoma of the uterus: use of gadopentetate dimeglumine in MR imaging. Radiology 181:95–106PubMedGoogle Scholar
  14. 14.
    Haldorsen IS, Husby JA, Werner HMJ et al (2012) Standard 1.5-T MRI of endometrial carcinomas: modest agreement between radiologists. Eur Radiol 22:1601–1611PubMedCrossRefGoogle Scholar
  15. 15.
    Sala E, Rockall AG, Freeman SJ, Mitchell DG, Reinhold C (2013) The added role of MR imaging in treatment stratification of patients with gynecologic malignancies: what the radiologist needs to know. Radiology 266:717–740PubMedCrossRefGoogle Scholar
  16. 16.
    Wakefield JC, Downey K, Kyriazi S, deSouza NM (2013) New MR techniques in gynecologic cancer. AJR Am J Roentgenol 200:249–260PubMedCrossRefGoogle Scholar
  17. 17.
    Padhani AR, Miles KA (2010) Multiparametric imaging of tumor response to therapy. Radiology 256:348–364PubMedCrossRefGoogle Scholar
  18. 18.
    Patterson DM, Padhani AR, Collins DJ (2008) Technology insight: water diffusion MRI - a potential new biomarker of response to cancer therapy. Nat Clin Pract Oncol 5:220–233PubMedCrossRefGoogle Scholar
  19. 19.
    Hellman RN (2011) Gadolinium-induced nephrogenic systemic fibrosis. Semin Nephrol 31:310–316PubMedCrossRefGoogle Scholar
  20. 20.
    Song F, Parekh S, Hooper L et al (2010) Dissemination and publication of research findings: an updated review of related biases. Heal Technol Assess Winch Engl 14:1–193Google Scholar
  21. 21.
    Parekh-Bhurke S, Kwok CS, Pang C, Hooper L, Loke YK, Ryder JJ et al (2011) Uptake of methods to deal with publication bias in systematic reviews has increased over time, but there is still much scope for improvement. J Clin Epidemiol 64:349–357PubMedCrossRefGoogle Scholar
  22. 22.
    Haynes RB, Kastner M, Wilczynski NL, Team H (2005) Developing optimal search strategies for detecting clinically sound and relevant causation studies in EMBASE. BMC Med Inf Decis Mak 5:8–14CrossRefGoogle Scholar
  23. 23.
    Leeflang MMG, Scholten RJPM, Rutjes AWS, Reitsma JB, Bossuyt PMM (2006) Use of methodological search filters to identify diagnostic accuracy studies can lead to the omission of relevant studies. J Clin Epidemiol 59:234–240PubMedCrossRefGoogle Scholar
  24. 24.
    De Vet HCW, Eisinga A, Riphagen II, Aertgeerts B, Pewsner D (2008) Chapter 7: searching for studies. In: Cochrane handbook for systematic reviews of diagnostic test accuracy version 0.4. Cochrane Collaboration. Accessed 20 Oct 2013
  25. 25.
    Devillé WL, Buntinx F, Bouter LM, Montori VM, de Vet HCW, van der Windt DAWM et al (2002) Conducting systematic reviews of diagnostic studies: didactic guidelines. BMC Med Res Methodol 2:9–21PubMedCentralPubMedCrossRefGoogle Scholar
  26. 26.
    Whiting PF, Rutjes AWS, Westwood ME, Mallett S, Deeks JJ, Reitsma JB et al (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155:529–536PubMedCrossRefGoogle Scholar
  27. 27.
    Creasman W (2009) Revised FIGO staging for carcinoma of the endometrium. Int J Gynaecol Obstet 105:109PubMedCrossRefGoogle Scholar
  28. 28.
    Dinnes J, Deeks J, Kirby J, Roderick P (2005) A methodological review of how heterogeneity has been examined in systematic reviews of diagnostic test accuracy. Heal Technol Assess 9:1–113Google Scholar
  29. 29.
    Higgins JPT, Thompson SG, Deeks JJ, Altman DG (2003) Measuring inconsistency in meta-analyses. BMJ 327:557–560PubMedCentralPubMedCrossRefGoogle Scholar
  30. 30.
    Chu H, Guo H, Zhou Y (2010) Bivariate random effects meta-analysis of diagnostic studies using generalized linear mixed models. Med Decis Mak 30:499–508CrossRefGoogle Scholar
  31. 31.
    Deeks JJ, Macaskill P, Irwig L (2005) The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol 58:882–893PubMedCrossRefGoogle Scholar
  32. 32.
    Sterne JA, Gavaghan D, Egger M (2000) Publication and related bias in meta-analysis: power of statistical tests and prevalence in the literature. J Clin Epidemiol 53:1119–1129PubMedCrossRefGoogle Scholar
  33. 33.
    Bharwani N, Miquel ME, Sahdev A et al (2011) Diffusion-weighted imaging in the assessment of tumour grade in endometrial cancer. Br J Radiol 84:997–1004PubMedCentralPubMedCrossRefGoogle Scholar
  34. 34.
    Masroor I, Zeeshan M, Afzal S, Ahmad N, Shafqat G (2010) Diffusion weighted MR imaging [DWI] and ADC values in endometrial carcinoma. J Coll Physicians Surg Pak 20:709–713PubMedGoogle Scholar
  35. 35.
    Inada Y, Matsuki M, Nakai G et al (2009) Body diffusion-weighted MR imaging of uterine endometrial cancer: Is it helpful in the detection of cancer in nonenhanced MR imaging? Eur J Radiol 70:122–127PubMedCrossRefGoogle Scholar
  36. 36.
    Kisu I, Banno K, Lin LY et al (2013) Preoperative and intraoperative assessment of myometrial invasion in endometrial cancer: comparison of magnetic resonance imaging and frozen section. Acta Obstet Gynecol Scand 92:525–535PubMedCrossRefGoogle Scholar
  37. 37.
    Zhang P, Tang Y, Li W, Hui N (2011) Value of magnetic resonance imaging in preoperative staging of endometrial carcinoma of early stage. Shanghai Jiaotong Daxue Xuebao 31:477–480Google Scholar
  38. 38.
    An Q, Yang J, Zhu Y (2012) Diffusion weighted imaging and contrast-enhanced magnetic resonance imaging in the evaluation of early stage endometrial cancer. Acta Acad Med Sin 34:486–491Google Scholar
  39. 39.
    Tamai K, Koyama T, Saga T et al (2007) Diffusion-weighted MR imaging of uterine endometrial cancer. J Magn Reson Imaging 26:682–687PubMedCrossRefGoogle Scholar
  40. 40.
    Shen S-H, Chiou Y-Y, Wang JH et al (2008) Diffusion-weighted single-shot echo-planar imaging with parallel technique in assessment of endometrial cancer. AJR Am J Roentgenol 190:481–488PubMedCrossRefGoogle Scholar
  41. 41.
    Takeuchi M, Matsuzaki K, Nishitani H (2009) Diffusion-weighted magnetic resonance imaging of endometrial cancer: differentiation from benign endometrial lesions and preoperative assessment of myometrial invasion. Acta Radiol Stockh Swed 50:947–953Google Scholar
  42. 42.
    Lin G, Ng KK, Chang CJ et al (2009) Myometrial invasion in endometrial cancer: diagnostic accuracy of diffusion-weighted 3.0-T MR imaging–initial experience. Radiology 250:784–792PubMedCrossRefGoogle Scholar
  43. 43.
    Rechichi G, Galimberti S, Signorelli M, Perego P, Valsecchi MG, Sironi S (2010) Myometrial invasion in endometrial cancer: diagnostic performance of diffusion-weighted MR imaging at 1.5-T. Eur Radiol 20:754–762PubMedCrossRefGoogle Scholar
  44. 44.
    Beddy P, Moyle P, Kataoka M et al (2012) Evaluation of depth of myometrial invasion and overall staging in endometrial cancer: comparison of diffusion-weighted and dynamic contrast-enhanced MR imaging. Radiology 262:530–537PubMedCrossRefGoogle Scholar
  45. 45.
    Ren C, Xue H, Li S et al (2012) Clinical application of magnetic resonance imaging in preoperative evaluation of endometrial cancer. Zhongguo Yi Xue Ke Xue Yuan Xue Bao 34:455–460PubMedGoogle Scholar
  46. 46.
    Dogan D, Inan N, Sarisoy HT et al (2013) Preoperative evaluation of myometrial invasion in endometrial carcinoma: diagnostic performance of 3 T MRI. Abdom Imaging 38:388–396PubMedCrossRefGoogle Scholar
  47. 47.
    Seo JM, Kim CK, Choi D, Kwan Park B (2013) Endometrial cancer: utility of diffusion-weighted magnetic resonance imaging with background body signal suppression at 3 T. J Magn Reson Imaging 37:1151–1159PubMedCrossRefGoogle Scholar
  48. 48.
    Hori M, Kim T, Onishi H et al (2013) Endometrial cancer: preoperative staging using three-dimensional T2-weighted turbo spin-echo and diffusion-weighted MR imaging at 3.0 T: a prospective comparative study. Eur Radiol 23:2296–2305PubMedCrossRefGoogle Scholar
  49. 49.
    Kido A, Fujimoto K, Okada T, Togashi K (2013) Advanced MRI in malignant neoplasms of the uterus. J Magn Reson Imaging 37:249–264PubMedCrossRefGoogle Scholar
  50. 50.
    Beddy P, O’Neill AC, Yamamoto AK, Addley HC, Reinhold C, Sala E (2012) FIGO staging system for endometrial cancer: added benefits of MR imaging. Radiographics 32:241–254PubMedCrossRefGoogle Scholar
  51. 51.
    Whittaker CS, Coady A, Culver L, Rustin G, Padwick M, Padhani AR (2009) Diffusion-weighted MR imaging of female pelvic tumors: a pictorial review. Radiographics 29:759–774PubMedCrossRefGoogle Scholar
  52. 52.
    Creasman WT, Odicino F, Maisonneuve P et al (2006) Carcinoma of the corpus uteri. FIGO 26th annual report on the results of treatment in gynecological cancer. Int J Gynaecol Obstet 95:S105–S143PubMedCrossRefGoogle Scholar
  53. 53.
    Merkle EM, Dale BM (2006) Abdominal MRI at 3.0 T: the basics revisited. AJR Am J Roentgenol 186:1524–1532PubMedCrossRefGoogle Scholar
  54. 54.
    Takahara T, Imai Y, Yamashita T, Yasuda S, Nasu S, Van Cauteren M (2004) Diffusion weighted whole body imaging with background body signal suppression (DWIBS): technical improvement using free breathing, STIR and high resolution 3D display. Radiat Med 22:275–282PubMedGoogle Scholar
  55. 55.
    Kilickesmez O, Bayramoglu S, Inci E, Cimilli T, Kayhan A (2009) Quantitative diffusion-weighted magnetic resonance imaging of normal and diseased uterine zones. Acta Radiol Stockh Swed 50:340–347Google Scholar
  56. 56.
    Macaskill P, Gatsonis S, Deeks J, Harbord R, Takwoingi Y (2010) Chapter 10: analysing and presenting results. Cochrane handbook systematic reviews of diagnostic test accuracy version 10. Cochrane Collaboration. Accessed 20 Oct 2013
  57. 57.
    Rechichi G, Galimberti S, Oriani M et al (2013) ADC maps in the prediction of pelvic lymph nodal metastatic regions in endometrial cancer. Eur Radiol 23:65–74PubMedCrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2014

Authors and Affiliations

  • Anita Andreano
    • 1
  • Gilda Rechichi
    • 2
  • Paola Rebora
    • 1
  • Sandro Sironi
    • 1
    • 2
  • Maria Grazia Valsecchi
    • 1
  • Stefania Galimberti
    • 1
  1. 1.Center of Biostatistics for Clinical Epidemiology, Department of Health SciencesUniversity of Milano-BicoccaMonzaItaly
  2. 2.Department of RadiologyS. Gerardo HospitalMonza, MBItaly

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