Preoperative diffusion-weighted magnetic resonance imaging and intraoperative frozen sections for predicting the tumor grade in endometrioid endometrial cancer

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Abstract

Objective: The histological tumor grade is a strong predictor of nodal metastasis in endometrial cancer; as such, an accurate pre-or intraoperative diagnosis is important for performing lymphadenectomy. Methods: Ninety-one patients with endometrioid endometrial cancer were imaged on DW-MRI with the apparent diffusion coefficient (ADC) calculated and a frozen section (FS) diagnosis made before and at hysterectomy. The diagnostic accuracy for predicting the tumor grade for diffusion weighted magnetic resonance inaging (DW-MRI) and the FS diagnosis compared to the ultimate histologic status was analyzed. Results: Among 91 patients with endometrioid endometrial cancer, high-grade (endometrioid G3) tumors had lower ADC values than low-grade (endometrioid G1/2) tumors. The cut-off of the mean ADCmean values for predicting high-grade tumors resulted in 743×10-6 mm2/sec according to the receiver operating characteristic curve. The true positive rates of ADC values and FSs for the prediction of high-grade tumors did not differ to a statistically significant extent (73.3% vs. 66.7%, p=0.7), however, the true negative rate of ADC values for the prediction of low-grade tumors was significantly lower than that of the FSs (64.5% vs. 98.7%, p=0.01). The kappa statistics of ADC values and FSs were 0.23 and 0.73, respectively. Of note, all five patients with high-grade tumors for whom intraoperative FSs indicated low-grade tumors were predicted to have high-grade tumors on preoperative DW-MRI. Conclusion: A FS diagnosis is more suitable for predicting high-grade tumors than DW-MRI; however, physicians should pay close attention to tumors with low ADC values on preoperative DW-MRI.

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Tanaka, T., Terai, Y., Fujiwara, S., Tanaka, Y., Sasaki, H., Tsunetoh, S., … Ohmichi, M. (2018). Preoperative diffusion-weighted magnetic resonance imaging and intraoperative frozen sections for predicting the tumor grade in endometrioid endometrial cancer. Oncotarget, 9(93), 36575–36584. https://doi.org/10.18632/oncotarget.26366

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