Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa

Purpose: To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis (TA) features could be useful in assessing the presence of placenta accreta spectrum (PAS) in patients with placenta previa (PP). The hypothesis is that TA features may reflect histological abnormalities underlying PAS in patients with PP thus helping in differentiating positive from negative cases.