Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Clinics |
Texto Completo: | https://www.revistas.usp.br/clinics/article/view/213297 |
Resumo: | 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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Clinics |
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Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor modelPlacenta accretePlacenta previaCesarean sectionMagnetic resonance imagingObjective: 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 Clínicas, Faculdade de Medicina, Universidade de São Paulo2022-03-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/clinics/article/view/21329710.1016/j.clinsp.2022.100027Clinics; Vol. 77 (2022); 100027Clinics; v. 77 (2022); 100027Clinics; Vol. 77 (2022); 1000271980-53221807-5932reponame:Clinicsinstname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/clinics/article/view/213297/195251Copyright (c) 2023 Clinicsinfo:eu-repo/semantics/openAccessPolizio, Rodrigo PamplonaYamauchi, Fernando IdeMendes, Renata Franco PimentelPeres, Stela VerzinhasseKondo, Mario MacotoFrancisco, Rossana Pulcineli Vieira2023-07-06T13:04:56Zoai:revistas.usp.br:article/213297Revistahttps://www.revistas.usp.br/clinicsPUBhttps://www.revistas.usp.br/clinics/oai||clinics@hc.fm.usp.br1980-53221807-5932opendoar:2023-07-06T13:04:56Clinics - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
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 |
spellingShingle |
Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model Polizio, Rodrigo Pamplona Placenta accrete Placenta previa Cesarean section Magnetic resonance imaging |
title_short |
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_sort |
Magnetic resonance imaging and previous cesarean section in placenta accrete spectrum disorder: Predictor model |
author |
Polizio, Rodrigo Pamplona |
author_facet |
Polizio, Rodrigo Pamplona Yamauchi, Fernando Ide Mendes, Renata Franco Pimentel Peres, Stela Verzinhasse Kondo, Mario Macoto Francisco, Rossana Pulcineli Vieira |
author_role |
author |
author2 |
Yamauchi, Fernando Ide Mendes, Renata Franco Pimentel Peres, Stela Verzinhasse Kondo, Mario Macoto Francisco, Rossana Pulcineli Vieira |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Polizio, Rodrigo Pamplona Yamauchi, Fernando Ide Mendes, Renata Franco Pimentel Peres, Stela Verzinhasse Kondo, Mario Macoto Francisco, Rossana Pulcineli Vieira |
dc.subject.por.fl_str_mv |
Placenta accrete Placenta previa Cesarean section Magnetic resonance imaging |
topic |
Placenta accrete Placenta previa Cesarean section Magnetic resonance imaging |
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. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-03-29 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/clinics/article/view/213297 10.1016/j.clinsp.2022.100027 |
url |
https://www.revistas.usp.br/clinics/article/view/213297 |
identifier_str_mv |
10.1016/j.clinsp.2022.100027 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/clinics/article/view/213297/195251 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2023 Clinics info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2023 Clinics |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo |
publisher.none.fl_str_mv |
Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo |
dc.source.none.fl_str_mv |
Clinics; Vol. 77 (2022); 100027 Clinics; v. 77 (2022); 100027 Clinics; Vol. 77 (2022); 100027 1980-5322 1807-5932 reponame:Clinics instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Clinics |
collection |
Clinics |
repository.name.fl_str_mv |
Clinics - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
||clinics@hc.fm.usp.br |
_version_ |
1800222766576697344 |