4.5 Article

Preoperative MR imaging for ESMO-ESGO-ESTRO classification of endometrial cancer

期刊

DIAGNOSTIC AND INTERVENTIONAL IMAGING
卷 99, 期 6, 页码 387-396

出版社

ELSEVIER MASSON, CORP OFF
DOI: 10.1016/j.diii.2018.01.010

关键词

Endometriat cancer; Tumor size; Magnetic resonance imaging (MRI); Tumor grade; Lymphovascular space invasion

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Objective: To retrospectively investigate whether magnetic resonance imaging (MRI) findings could contribute to predict histologic type, tumor grade and lymphovascular space invasion LVSI) to improve preoperative assessment of endometrial cancer using the European Society for Medical Oncology (ESMO) European Society for Radiotherapy & Oncology (ESTRO) and European Society of Gynecological Oncology (ESGO) classification. Methods: Between January 2008 and August 2014, 104 women (mean age, 65 +/- 11 [SD] years; range, 32-84 years) with International Federation of Gynecology and Obstetrics (FIGO) stage I endometrial cancer underwent preoperative MRI of the pelvis. Two independent readers evaluated tumor heterogeneity and measured tumor size on T2-weighted, diffusion-weighted and T1-weighted images obtained after gadolinium chelate administration at 2 minutes. The apparent diffusion coefficient (ADC) was generated from pixel ADC from the whole tumor volume. Results: A short axis> 24 mm on MRI was associated with histopathologic type 2, grade 3 tumor and presence of LVSI (P<0.01). There were no significant differences in minimum, mean and maximum ADC between presence/absence of LVSI. In 9.1% women (9/99), the accuracy of the ESMO-ESGO-ESTRO classification with the inclusion of the MRI short-axis criterion was higher than that of the conventional ESMO classification to predict high-risk recurrence endometrial cancer (P=0.02). Conclusion: Tumor size reflects histologic type, tumor grade and LVSI in endometrial cancer. FIGO stage 1 endometrial cancer > 24 mm should be classified preoperatively in the high-intermediate or high-risk recurrence risk groups. (C) 2018 Societe francaise de radiologie. Published by Elsevier Masson SAS. All rights reserved.

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