Jiang-Ning Dong1 and Bin Shi1
1The First Affiliated Hospital of USTC, Anhui Provincial Cancer Hospital, Hefei, China
1The First Affiliated Hospital of USTC, Anhui Provincial Cancer Hospital, Hefei, China
The combination of IVIM-DWI and T2WI-based texture features had good predictive performance to evaluate different histological types of cervical carcinoma, especially for cervical squamous cell carcinoma and adenocarcinoma.
Fig. 2 Box-plots of IVIM-DWI Parameters.
Panels A-D represent ADC, D, D* and f values for G-1 (cervical squamous cell carcinoma), G-2 (cervical adenocarcinoma) and G-3 (cervical small cell carcinoma), respectively (p ＜ 0.05).
Fig. 3 ROC Curves of Regression Model for G-1 Compared to G-2, and Individual Independent factors (D, D* and Gray Level Variance).