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Nomogram model based on magnetic resonance imaging and clinical factors for prenatal diagnosis of placenta accreta spectrum disorders

Jingjing Zhong(1), Qin Zhang(2), Peipei Lin(3), Dandan Miao(4), Honggang Yin(5),


(1) Department of Radiology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, 226001, Jiangsu, China
(2) Department of Radiology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, 226001, Jiangsu, China
(3) Department of Radiology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, 226001, Jiangsu, China
(4) Department of Radiology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, 226001, Jiangsu, China
(5) Department of Radiology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, 226001, Jiangsu, China
Corresponding Author

Abstract


This study aimed to develop a magnetic resonance imaging (MRI) and clinical factor-based nomogram for prenatal diagnosis of placenta accreta spectrum disorders (PAS). Clinical and MRI data from pregnant women were retrospectively analyzed and split into training (70%) and validation (30%) sets. Binary logistic regression identified age, placenta previa, T2 dark band, placental/uterine bulge, loss of T2 hypointense interface, myometrial thinning, and abnormal placental bed vessels as significant predictors of PAS. A nomogram incorporating these factors demonstrated strong diagnostic performance via ROC analysis (AUC >0.8), calibration curves, and decision curve analysis (DCA) in both training and validation sets. The model showed high accuracy and clinical utility, supporting its use in prenatal PAS diagnosis

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