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Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model

OBJECTIVE: To 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. METHODS: A retrospective review including patients submitted to M...

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Autores principales: Polizio, Rodrigo Pamplona, Yamauchi, Fernando Ide, Mendes, Renata Franco Pimentel, Peres, Stela Verzinhasse, Kondo, Mario Macoto, Francisco, Rossana Pulcineli Vieira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8971588/
https://www.ncbi.nlm.nih.gov/pubmed/35364517
http://dx.doi.org/10.1016/j.clinsp.2022.100027
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author Polizio, Rodrigo Pamplona
Yamauchi, Fernando Ide
Mendes, Renata Franco Pimentel
Peres, Stela Verzinhasse
Kondo, Mario Macoto
Francisco, Rossana Pulcineli Vieira
author_facet Polizio, Rodrigo Pamplona
Yamauchi, Fernando Ide
Mendes, Renata Franco Pimentel
Peres, Stela Verzinhasse
Kondo, Mario Macoto
Francisco, Rossana Pulcineli Vieira
author_sort Polizio, Rodrigo Pamplona
collection PubMed
description OBJECTIVE: To 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. METHODS: A 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. RESULTS: Final 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. CONCLUSION: Simplified 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.
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spelling pubmed-89715882022-04-05 Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model Polizio, Rodrigo Pamplona Yamauchi, Fernando Ide Mendes, Renata Franco Pimentel Peres, Stela Verzinhasse Kondo, Mario Macoto Francisco, Rossana Pulcineli Vieira Clinics (Sao Paulo) Original Articles OBJECTIVE: To 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. METHODS: A 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. RESULTS: Final 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. CONCLUSION: Simplified 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. Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo 2022-03-29 /pmc/articles/PMC8971588/ /pubmed/35364517 http://dx.doi.org/10.1016/j.clinsp.2022.100027 Text en © 2022 HCFMUSP. Published by Elsevier España, S.L.U. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Original Articles
Polizio, Rodrigo Pamplona
Yamauchi, Fernando Ide
Mendes, Renata Franco Pimentel
Peres, Stela Verzinhasse
Kondo, Mario Macoto
Francisco, Rossana Pulcineli Vieira
Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model
title Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model
title_full Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model
title_fullStr Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model
title_full_unstemmed Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model
title_short Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model
title_sort magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: predictor model
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8971588/
https://www.ncbi.nlm.nih.gov/pubmed/35364517
http://dx.doi.org/10.1016/j.clinsp.2022.100027
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