The diagnostic value of multiple schemes of MRI standard features combined with risk factors and ultrasound for Placenta accreta spectrum

This study aims to identify the most diagnostically valuable features among the 11 MRI features of Placenta accreta spectrum (PAS) described in the joint consensus statement by the Society of Abdominal Radiology (SAR) and the European Society of Urogenital Radiology (ESUR), and to evaluate the diagnostic efficacy of MRI, risk factors, and ultrasound (US) used alone or in combination for prenatal PAS diagnosis. This retrospective study included 199 pregnant women who delivered at Zhengzhou Central Hospital from November 2018 to December 2022. Standardized evaluations of Risk Factors, US, and MRI features were conducted, and subjects were divided into PAS (89 cases) and non-PAS groups (110 cases). Chi-square tests, logistic regression, and the Bootstrap method were used to identify MRI features with intergroup differences. Diagnostic scheme efficacy was compared using the area under the curve (AUC), and improvements were assessed using the net reclassification improvement index (NRI) and integrated discrimination improvement index (IDI). The final diagnosis of PAS was based on surgical and/or pathological findings according to the International Federation of Gynecology and Obstetrics (FIGO) criteria. Three Risk Factors (caesarean delivery (CD) history, placenta previa, advanced maternal age) and three MRI features (T2-dark intraplacental bands, Loss of retroplacental T2-hypointense line, and Asymmetric shape/thickening of the placenta) showed statistical differences. The AUC for Risk Factors, US, and MRI alone was > 0.8. Combined schemes (MRI + US and MRI + US + Risk Factors) had higher efficacy, with MRI + US + Risk Factors demonstrating the highest efficacy. This study identifies three key standardized MRI features and three key risk factors to simplify clinical application. For high-risk pregnant women, a multimodal approach combining risk assessment, ultrasound, and standardized MRI features produced the highest diagnostic performance, but prospective external validation is required before broader clinical implementation.