• Rodrigo Pamplona Polizio, Fernando Ide Yamauchi, Renata Franco Pimentel Mendes, Stela Verzinhasse Peres, Mario Macoto Kondo, and FranciscoRossana Pulcineli VieiraRPVDepartamento de Obstetrícia e Ginecologia do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brazil..
• Departamento de Radiologia e Diagnóstico por Imagem do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brazil. Electronic address: rodrigo.polizio@hc.fm.usp.br.
• Clinics (Sao Paulo). 2022 Jan 1; 77: 100027100027.

ObjectiveTo evaluate objective criteria of Magnetic Resonance Imaging (MRI) of Placenta Accreta Spectrum disorder (PAS) analyzing interobserver agreement and to derive a model including imaging and clinical variables to predict PAS.MethodsA retrospective review including patients submitted to MRI with suspicious findings of PAS on ultrasound. Exclusion criteria were lack of pathology or surgical information and missing or poor-quality MRI. Two radiologists analyzed six MRI features, and significant clinical data were also recorded. PAS confirmed on pathology or during intraoperative findings were considered positive for the primary outcome. Variables were tested through logistic regression models.ResultsFinal study included 96 patients with a mean age of 33 years and 73.0% of previous C-sections. All MRI features were significantly associated with PAS for both readers. After logistic regression fit, including MRI signs with a moderate or higher interobserver agreement, intraplacental T2 dark band was the most significant radiologic criteria, and ROC analysis resulted in an AUC = 0.782. After including the most relevant clinical data (previous C-section) to the model, the ROC analysis improved to an AUC = 0.893.ConclusionSimplified objective criteria on MRI, including intraplacental T2 dark band associated with clinical information of previous C-sections, had the highest accuracy and was used for a predictive model of PAS.Copyright © 2022 HCFMUSP. Published by Elsevier España, S.L.U. All rights reserved.

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