USMRI Radiomics-based Model for Predicting the Degree of Placental Implantation and Develop Radiomics-based Prediction Models

Abstract Background:To investigate the ability of ultrasound/MRI-based radiomics signature for preoperatively predicting the degree of placental implantation and develop radiomics‑based prediction models. Methods: From January 2016 to December 2020,Clinicopathological characteristics, prenatal ultrasound images, and MRI radiomics features of 132 pregnant women with placental implantation at Xiangyang NO.1 people's Hospital were retrospectively reviewed.In the training set of 100 patients, ultrasound/MRI radiomics model, Clinicopathological model, and combined model were developed by multivariate logistic regression analysis to predict the degree of placental implantation,and the prediction performance of different models were compared using the Delong test. The developed models were validated by assessing their prediction performance in test set of 33 patients.Results:Multivariate logistic regression analysis identified history of abortion、history of endometrial injury、blurred boundary between the uterine serosa and bladder to construct combined model for predicting degree of placental implantation [the area under the curve (AUC) = 0.931; 95% CI 0.874-0.968].While the AUC of clinical model and ultrasound/MRI radiomics model were 0.858 (95% CI 0.787-0.913) and 0.709 (95% CI 0.624-0.785), respectively. The AUC of the combined model was significantly higher than that of the radiomics model (p ＜0.001) or clinical model (p = 0.0015) in training set.In test set, the combined model also showed higher prediction performance. Conclusions:Ultrasound/MRI-based radiomics signature is a powerful predictor for early degree of placental implantation. Ultrasound/MRI radiomics (constructed with Complete placenta previa、blurred boundary between the placenta and myometrium、blurred boundary between the uterine serosa and bladder) and combined model (constructed with history of abortion、history of endometrial injury、blurred boundary between the uterine serosa and bladder) can improve the accuracy for predicting the early degree of placental implantation.