Skip to main navigation Skip to search Skip to main content

Prediction of histological grade of endometrial cancer by means of MRI

  • Matteo Bonatti*
  • , Beatrice Pedrinolla
  • , Adam Jerzy Cybulski
  • , Fabio Lombardo
  • , Giovanni Negri
  • , Sergio Messini
  • , Tiziana Tagliaferri
  • , Riccardo Manfredi
  • , Giampietro Bonatti
  • *Corresponding author
  • Regional Hospital of Bolzano
  • University of Verona

Research output: Contribution to journalArticle

Abstract

Objectives: To evaluate the ability of MRI in predicting histological grade of endometrial cancer (EC). Methods: IRB-approved retrospective study; requirement for informed consent was waived. 90 patients with histologically proven EC who underwent preoperative MRI and surgery at our Institution between Sept2011 and Nov2016 were included. Myometrial invasion (50%) was assessed. Neoplasm and uterus volumes were estimated according to the ellipsoid formula; neoplasm/uterus volume ratio (N/U) was calculated. ADC maps were generated and histogram analysis was performed using commercially available software. MRI parameters were compared with the definitive histological grade (G1 = 28 patients, G2 = 29, G3 = 33) using ANOVA and Tukey-Kramer tests. Results: Deep myometrial invasion was significantly more frequent in G2-G3 lesions than in G1 ones (p < 0,005). N/U ratio was significantly higher for high-grade neoplasms (mean 0,08 for G1, 0,16 for G2 and 0,21 in G3; P = 0,002 for G1 vs. G2-G3); a cut off value of 0,13 enabled to distinguish G1 from G2-G3 lesions with 50% sensibility and 89% specificity. ADC values didn't show any statistically significant correlation with tumour grade. Conclusions: N/U ratio >0.13 and deep myometrial invasion are significantly correlated with high grade EC, whereas ADC values are not useful for predicting EC grade.
Original languageEnglish
Pages (from-to)44-50
Number of pages7
JournalEuropean Journal of Radiology
Volume103
Issue number2018
DOIs
Publication statusPublished - 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

Keywords

  • 80 and over
  • Adult
  • Aged
  • Diffusion magnetic resonance imaging
  • Endometrial Neoplasms
  • Endometrial neoplasms
  • Endometrium
  • Female
  • Humans
  • Magnetic Resonance Imaging
  • Magnetic resonance imaging
  • Middle Aged
  • Neoplasm Grading
  • Neoplasm grading
  • Nuclear Medicine and Imaging
  • Radiology
  • Retrospective Studies
  • Sensitivity and Specificity
  • Uterus

Fingerprint

Dive into the research topics of 'Prediction of histological grade of endometrial cancer by means of MRI'. Together they form a unique fingerprint.

Cite this