OBJECTIVE: To assess the value of volumetric ADC histogram metrics in evaluating the histological subtype and grade of endometrial cancer.
METHODS: Preoperative MRI datasets of 317 patients with endometrial cancer were used to obtain volumetric ADC histogram metrics (tumour volume; minADC, maxADC and meanADC; 10th, 25th, 50th, 75th and 90th percentiles of ADC; skewness; and kurtosis). The Mann-Whitney test or Student\'s t-test was used to compare the difference in ADC histogram metrics between endometrioid adenocarcinomas (EACs) and
serous endometrial cancers (SECs) and between different tumour grades (G1, G2, G3). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the performance of ADC histogram metrics or combined models in predicting the tumour subtype and grade.
RESULTS: SECs showed a significantly larger tumour volume (P < 0.001) and lower meanADC, 50th, 75th and 90th percentiles of ADC than EACs (all P < 0.05). MinADC, maxADC, meanADC, 10th, 25th, 50th, 75th, 90th percentiles of ADC were significantly higher in G1 than in G2 and G3 EACs (all P < 0.05), while were not significantly different between G2 and G3 EACs (all P > 0.05). A tumour volume ≥ 7.752 cm3 allowed for the prediction of SECs, with an AUC of 0.765 (0.714-0.810). A meanADC ≥ 0.892 × 10-3 mm2/s enabled to discriminate G1 from G2 and G3 EACs, with an AUC of 0.818 (0.769-0.861).
CONCLUSIONS: Volumetric ADC histogram analysis is helpful for non-invasive preoperatively predicting the subtype of endometrial cancer and differentiating G1 from G2 and G3 EACs.