Diagnostic performance of MR imaging in evaluating prognostic factors in patients with cervical cancer: a meta-analysis

  • Meiling Xiao
  • Bicong Yan
  • Ying Li
  • Jingjing Lu
  • Jinwei QiangEmail author



This study aims to determine the diagnostic performance of conventional magnetic resonance imaging (MRI) in assessing the distance between the tumor and the internal os, stromal infiltration, lymph node metastasis, and parametrial invasion in patients with cervical cancer.


A systematic English-language literature search of conventional MRI in the evaluation of human cervical cancer was performed in the PubMed, Cochrane Library, Embase, and Web of Science databases from 1995 to 2018. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and positive and negative likelihood ratios (PLR and NLR) of all studies were calculated. The results were then plotted in a hierarchical summary receiver operating characteristic (HSROC) plot, and meta-regression and subgroup analyses of the parametrial invasion were also performed.


The pooled sensitivity, specificity, DOR, PLR, and NLR were 86%, 97%, 167.91, 24.74, and 0.15, respectively, in evaluating the internal os involvement (6 studies, 454 patients); 87%, 91%, 73.41, 10.22, and 0.14, respectively, in evaluating the stromal infiltration (11 studies, 672 patients); 51%, 89%, 8.63, 4.72, and 0.55, respectively, in evaluating the lymph node metastasis (15 studies, 997 patients); and 75%, 92%, 34.01, 9.38, and 0.28, respectively, in evaluating the parametrial invasion (19 studies, 1748 patients). The meta-regression of the parametrial invasion showed that the application of contrast enhancement was a significant factor affected the heterogeneity (p = 0.039).


Conventional MRI can accurately evaluate the distance between the tumor and the internal os, as well as stromal infiltration, and performs well in diagnosing the parametrial invasion. However, this method exhibited a limited ability in diagnosing the lymph node metastasis.

Key Points

• MRI can help clinicians to accurately assess the distance between the tumor and the internal os, stromal infiltration, and parametrial invasion in patients with uterine cervical neoplasms.

• MRI exhibits a limited ability in diagnosing the lymph node metastasis.

• Management of patients with uterine cervical neoplasms becomes more appropriate.


Magnetic resonance imaging Cervical cancer Lymph node metastasis Parametrial invasion Meta-analysis 



Area under the curve




Confidence interval


Diffusion-weighted imaging


Diagnostic odds ratio


International Federation of Gynecology and Obstetrics


Hierarchical summary receiver operating characteristic


Magnetic resonance imaging


Negative likelihood ratios


Positive likelihood ratios


Preferred Reporting Items for Systematic Reviews and Meta-Analyses


Quality Assessment of Diagnostic Accuracy Studies-2


Radical trachelectomy


Funding information

This study has received funding from the National Natural Science Foundation of China (No. 81471628) and the Shanghai Municipal Commission of Health and Family Planning, China (No. 2013SY075 and No. ZK2015A05).

Compliance with ethical standards


The scientific guarantor of this publication is Jinwei Qiang.

Conflict of interest

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.

Statistics and biometry

One of the authors (Ying Li) has significant statistical expertise.

Informed consent

Written informed consent was not required for this study due to the nature of the study, which was a meta-analysis.

Ethical approval

Institutional Review Board approval was not required for this study due to the nature of the study, which was a meta-analysis.


• Meta-analysis

• Performed at one institution

Supplementary material

330_2019_6461_MOESM1_ESM.docx (350 kb)
ESM 1 (DOCX 349 kb)


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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Meiling Xiao
    • 1
  • Bicong Yan
    • 1
  • Ying Li
    • 1
  • Jingjing Lu
    • 1
  • Jinwei Qiang
    • 1
    Email author
  1. 1.Department of Radiology, Jinshan HospitalFudan UniversityShanghaiChina

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