Endometrial Carcinoma: Texture Analysis of Apparent Diffusion Coefficient Maps and Its Correlation with Histopathologic Findings and Prognosis.

Purpose: To determine the feasibility of texture analysis (TA) of apparent diffusion coefficient (ADC) maps for predicting histologic grade (HG) and recurrence-free survival (RFS) in patients with endometrial carcinoma (EMC). Materials and
Methods: One hundred twenty-one patients with EMC were examined by using a 1.5-T MRI system and diffusion-weighted imaging (DWI) with b values of 0 and 1000 sec/mm2. Software with volumes of interest on ADC maps was used to extract 45 texture features including higher-order texture features. Receiver operating characteristic analysis was performed to compare the diagnostic performance of the random forest (RF) model and ADC values for HG and recurrence.
Results: Area under the curve (AUC) for predicting high-grade EMCs was significantly larger for RF model than for ADC values (0.967 vs 0.898; P = .0336). AUC for predicting recurrence was larger for the RF model than for ADC values (0.890 vs 0.875; P = .7248), although the difference was not significant. Mean RFS was significantly shorter for high-grade EMCs than for low-grade EMCs (P = .0002; hazard ratio, 4.9) and for ADC values less than or equal to 0.802 × 10-3 mm2/sec than for ADC values greater than 0.802 × 10-3 mm2/sec (P < .0001; hazard ratio, 32.9). RF model showed that the mean RFS was significantly shorter for the presence of recurrence than for its absence (P < .0001; hazard ratio, 94.7).
Conclusion: TA of ADC maps had significantly higher diagnostic performance than did ADC values for predicting HG and was a more useful indicator than HG and ADC values for predicting RFS in patients with EMC.Keywords: Comparative Studies, Genital/Reproductive, MR-Diffusion Weighted Imaging, MR-Imaging, Neoplasms-Primary, Pathology, Pelvis, Tissue Characterization, Uterus© RSNA, 2019. 2019 by the Radiological Society of North America, Inc.