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Endometrial Carcinoma: Texture Analysis of Apparent Diffusion Coefficient Maps and Its Correlation with
Ichiro Yamada1, Naoyuki Miyasaka1, Daisuke Kobayashi1
1Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.M., K.W., N.O., A.W.), Human Pathology (D.K., Y.E.), and Oral and Maxillofacial Radiology (J.S.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan.
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.
