Biomarkers Endometrium

The following list has been reviewed and approved by the European Society of Urogenital Radiology’s (ESUR)’s Women’s Pelvic Imaging Group.

 

UTERUS

Technique

Level of
evidence1!

Single centre/
Multicentre/
metaanalysis

Indication

Patient prep

Data acquisition
requirements

Image processing
algorithm

Recommended
biomarkers/
primary end-point

Size/ Morphology

 

 

12-5!

Single centre & Multicentre

Detection, staging, treatment response

IM antiperistaltic agent

Sagittal, axial and coronal oblique
DWI recommended
DCE

Manual documentation by trained observer


Recommended
biomarkers/ secondary
end-point

DCE-MRI

 

15-9!

Single centre

Staging

IM antiperistaltic agent

3D fat-saturated T1W 2min30s after contrast medium administration

Manual documentation by trained observer

DWI (visual)

 

15, 10!

Single centre

Staging

IM antiperistaltic agent

At least 2 b-values (b=0-50 and b=800-1000 s/mm2)

Manual documentation by trained observer

             

Biomarkers in development/
exploratory not
recommended

ADC and ADC histogram

111, 12!
213, 14!
315, 16!

Single centre

Differentiation benign and malignant, staging, histopathological tumour features

IM antiperistaltic agent

At least 2 b-values (b=0-50 and b=800-1000 s/mm2)

Monoexponential data fit, first order histogram parameters

Multiparametric MR

 

317!

Single centre

Staging and histopathological tumour features

IM antiperistaltic agent

At least 2 b-values (b=0-50 and b=800-1000 s/mm2)

Monoexponentional data fit, first order histogram parameters

Radiomics

 

318!

Single centre

Histopathological tumour features

IM anitperistaltic agent

T2W, DWI and dynamic DCEs

No consensus available

  1. Schweitzer ME. Evidence level. J Magn Reson Imaging. 2016;43(3):543-543. doi:10.1002/jmri.25187
  2. Hricak H, Rubinstein L V, Gherman GM, Karstaedt N. MR imaging evaluation of endometrial carcinoma: results of an NCI cooperative study. Radiology. 1991;179(3):829-832. doi:10.1148/radiology.179.3.2028000
  3. Hricak H, Stern JL, Fisher MR, Shapeero LG, Winkler ML, Lacey CG. Endometrial carcinoma staging by MR imaging. Radiology. 1987;162(2):297-305. doi:10.1148/radiology.162.2.3797641
  4. Nougaret S, Horta M, Sala E, et al. Endometrial Cancer MRI staging: Updated Guidelines of the European Society of Urogenital Radiology. Eur Radiol. July 2018. doi:10.1007/s00330-018-5515-y
  5. Lavaud P, Fedida B, Canlorbe G, Bendifallah S, Darai E, Thomassin-Naggara I. Preoperative MR imaging for ESMO-ESGO-ESTRO classification of endometrial cancer. Diagn Interv Imaging. 2018 Jun;99(6):387-396. doi: 10.1016/j.diii.2018.01.010. Epub 2018 Feb 19. PubMed PMID: 29472031.
  6. Hricak H, Hamm B, Semelka RC, et al. Carcinoma of the uterus: use of gadopentetate dimeglumine in MR imaging. Radiology. 1991;181(1):95-106. doi:10.1148/radiology.181.1.1887062
  7. Yamashita Y, Harada M, Sawada T, Takahashi M, Miyazaki K, Okamura H. Normal uterus and FIGO stage I endometrial carcinoma: dynamic gadolinium-enhanced MR imaging. Radiology. 1993;186(2):495-501. doi:10.1148/radiology.186.2.8421757
  8. Frei KA, Kinkel K, Bonél HM, Lu Y, Zaloudek C, Hricak H. Prediction of Deep Myometrial Invasion in Patients with Endometrial Cancer: Clinical Utility of Contrast-enhanced MR Imaging-A Meta-analysis and Bayesian Analysis. Radiology. 2000;216(2):444-449. doi:10.1148/radiology.216.2.r00au17444
  9. Sironi S, Colombo E, Villa G, et al. Myometrial invasion by endometrial carcinoma: assessment with plain and gadolinium-enhanced MR imaging. Radiology. 1992;185(1):207-212. doi:10.1148/radiology.185.1.1523309
  10. Rechichi G, Galimberti S, Signorelli M, Perego P, Valsecchi MG, Sironi S. Myometrial invasion in endometrial cancer: diagnostic performance of diffusion-weighted MR imaging at 1.5-T. Eur Radiol. 2010;20(3):754-762. doi:10.1007/s00330-009-1597-x
  11. Kim H-J, Lee S-Y, Shin YR, Park CS, Kim K. The Value of Diffusion-Weighted Imaging in the Differential Diagnosis of Ovarian Lesions: A Meta-Analysis. Cao C, ed. PLoS One. 2016;11(2):e0149465. doi:10.1371/journal.pone.0149465
  12. Nakamura K, Imafuku N, Nishida T, et al. Measurement of the minimum apparent diffusion coefficient (ADCmin) of the primary tumor and CA125 are predictive of disease recurrence for patients with endometrial cancer. Gynecol Oncol. 2012;124(2):335-339. doi:10.1016/J.YGYNO.2011.10.014
  13. Tamai K, Koyama T, Saga T, et al. Diffusion-weighted MR imaging of uterine endometrial cancer. J Magn Reson Imaging. 2007;26(3):682-687. doi:10.1002/jmri.20997
  14. Shen S-H, Chiou Y-Y, Wang J-H, et al. Diffusion-Weighted Single-Shot Echo-Planar Imaging with Parallel Technique in Assessment of Endometrial Cancer. Am J Roentgenol. 2008;190(2):481-488. doi:10.2214/AJR.07.2155
  15. Fujii S, Matsusue E, Kigawa J, et al. Diagnostic accuracy of the apparent diffusion coefficient in differentiating benign from malignant uterine endometrial cavity lesions: initial results. Eur Radiol. 2008;18(2):384-389. doi:10.1007/s00330-007-0769-9
  16. Woo S, Cho JY, Kim SY, Kim SH. Histogram analysis of apparent diffusion coefficient map of diffusion-weighted MRI in endometrial cancer: a preliminary correlation study with histological grade. Acta radiol. 2014;55(10):1270-1277. doi:10.1177/0284185113514967
  17. Nougaret S, Reinhold C, Alsharif SS, et al. Endometrial Cancer: Combined MR Volumetry and Diffusion-weighted Imaging for Assessment of Myometrial and Lymphovascular Invasion and Tumor Grade. Radiology. 2015;276(3):797-808. doi:10.1148/radiol.15141212
  18. Ueno Y, Forghani B, Forghani R, et al. Endometrial Carcinoma: MR Imaging–based Texture Model for Preoperative Risk Stratification—A Preliminary Analysis. Radiology. 2017;284(3):748-757. doi:10.1148/radiol.2017161950

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