Abstract

The objective of this study was to evaluate whether whole-uterine magnetic resonance imaging (MRI) radiomic features can predict myometrial invasion (MI) depth in endometrial cancer (EC). The preoperative 3.0 T magnetic resonance examinations of EC patients were retrospectively reviewed. Whole-uterus segmentation was performed, and features were extracted based on sagittal T2-weighted imaging (T2WI) and axial diffusion-weighted imaging (DWI). The logistic regression (LR) classifier algorithm was used to establish the radiomic model, which was verified by ten times five-fold cross-validation. The areas under the receiver operating characteristic (ROC) curves (AUCs) were assessed by the DeLong test to compare differences among the models based on different sequences. The LR model was compared with the subjective diagnosis results by the Chi-square test. Of the 163 EC patients included, 44 had deep myometrial invasion (DMI). The feature consistency of the whole uterus was higher than that of the lesion (P < 0.05). The sagittal T2WI, axial DWI, and combined models had AUCs of 0.76, 0.80, and 0.85 in the validation set, respectively. The DeLong test showed that there were no significant differences in AUCs among the models (P > 0.05). The single-sequence LR models had lower specificity and accuracy than the corresponding subjective diagnostic results (P < 0.05), while the sensitivity was higher (P > 0.05). The combined model included 24 radiomic features, and the accuracy, sensitivity, and specificity were 0.83, 0.77, and 0.85 for DMI, respectively. There was no significant difference compared with subjective diagnosis (P > 0.05). Whole-uterine MRI radiomic features based on sagittal T2WI and axial DWI show potential in predicting MI in EC.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.