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Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI

OBJECTIVES: Postcontrast magnetic resonance imaging (MRI) is important for the differentiation between low-grade (WHO I) and high-grade (WHO II/III) meningiomas. However, nephrogenic systemic fibrosis and cerebral gadolinium deposition are major concerns for postcontrast MRI. This study aimed to dev...

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Autores principales: Yao, Yuan, Xu, Yifan, Liu, Shihe, Xue, Feng, Wang, Bao, Qin, Shanshan, Sun, Xiubin, He, Jingzhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9752076/
https://www.ncbi.nlm.nih.gov/pubmed/36530973
http://dx.doi.org/10.3389/fonc.2022.1053089
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author Yao, Yuan
Xu, Yifan
Liu, Shihe
Xue, Feng
Wang, Bao
Qin, Shanshan
Sun, Xiubin
He, Jingzhen
author_facet Yao, Yuan
Xu, Yifan
Liu, Shihe
Xue, Feng
Wang, Bao
Qin, Shanshan
Sun, Xiubin
He, Jingzhen
author_sort Yao, Yuan
collection PubMed
description OBJECTIVES: Postcontrast magnetic resonance imaging (MRI) is important for the differentiation between low-grade (WHO I) and high-grade (WHO II/III) meningiomas. However, nephrogenic systemic fibrosis and cerebral gadolinium deposition are major concerns for postcontrast MRI. This study aimed to develop and validate an accessible risk-scoring model for this differential diagnosis using the clinical characteristics and radiological features of precontrast MRI. METHODS: From January 2019 to October 2021, a total of 231 meningioma patients (development cohort n = 137, low grade/high grade, 85/52; external validation cohort n = 94, low-grade/high-grade, 60/34) were retrospectively included. Fourteen types of demographic and radiological characteristics were evaluated by logistic regression analyses in the development cohort. The selected characteristics were applied to develop two distinguishing models using nomograms, based on full MRI and precontrast MRI. Their distinguishing performances were validated and compared using the external validation cohort. RESULTS: One demographic characteristic (male), three precontrast MRI features (intratumoral cystic changes, lobulated and irregular shape, and peritumoral edema), and one postcontrast MRI feature (absence of a dural tail sign) were independent predictive factors for high-grade meningiomas. The area under the receiver operating characteristic (ROC) curve (AUC) values of the two distinguishing models (precontrast–postcontrast nomogram vs. precontrast nomogram) in the development cohort were 0.919 and 0.898 and in the validation cohort were 0.922 and 0.878. DeLong’s test showed no statistical difference between the AUC values of the two distinguishing models (p = 0.101). CONCLUSIONS: An accessible risk-scoring model based on the demographic characteristics and radiological features of precontrast MRI is sufficient to distinguish between low-grade and high-grade meningiomas, with a performance equal to that of a full MRI, based on radiological features.
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spelling pubmed-97520762022-12-16 Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI Yao, Yuan Xu, Yifan Liu, Shihe Xue, Feng Wang, Bao Qin, Shanshan Sun, Xiubin He, Jingzhen Front Oncol Oncology OBJECTIVES: Postcontrast magnetic resonance imaging (MRI) is important for the differentiation between low-grade (WHO I) and high-grade (WHO II/III) meningiomas. However, nephrogenic systemic fibrosis and cerebral gadolinium deposition are major concerns for postcontrast MRI. This study aimed to develop and validate an accessible risk-scoring model for this differential diagnosis using the clinical characteristics and radiological features of precontrast MRI. METHODS: From January 2019 to October 2021, a total of 231 meningioma patients (development cohort n = 137, low grade/high grade, 85/52; external validation cohort n = 94, low-grade/high-grade, 60/34) were retrospectively included. Fourteen types of demographic and radiological characteristics were evaluated by logistic regression analyses in the development cohort. The selected characteristics were applied to develop two distinguishing models using nomograms, based on full MRI and precontrast MRI. Their distinguishing performances were validated and compared using the external validation cohort. RESULTS: One demographic characteristic (male), three precontrast MRI features (intratumoral cystic changes, lobulated and irregular shape, and peritumoral edema), and one postcontrast MRI feature (absence of a dural tail sign) were independent predictive factors for high-grade meningiomas. The area under the receiver operating characteristic (ROC) curve (AUC) values of the two distinguishing models (precontrast–postcontrast nomogram vs. precontrast nomogram) in the development cohort were 0.919 and 0.898 and in the validation cohort were 0.922 and 0.878. DeLong’s test showed no statistical difference between the AUC values of the two distinguishing models (p = 0.101). CONCLUSIONS: An accessible risk-scoring model based on the demographic characteristics and radiological features of precontrast MRI is sufficient to distinguish between low-grade and high-grade meningiomas, with a performance equal to that of a full MRI, based on radiological features. Frontiers Media S.A. 2022-12-01 /pmc/articles/PMC9752076/ /pubmed/36530973 http://dx.doi.org/10.3389/fonc.2022.1053089 Text en Copyright © 2022 Yao, Xu, Liu, Xue, Wang, Qin, Sun and He https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Yao, Yuan
Xu, Yifan
Liu, Shihe
Xue, Feng
Wang, Bao
Qin, Shanshan
Sun, Xiubin
He, Jingzhen
Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI
title Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI
title_full Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI
title_fullStr Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI
title_full_unstemmed Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI
title_short Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI
title_sort predicting the grade of meningiomas by clinical–radiological features: a comparison of precontrast and postcontrast mri
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9752076/
https://www.ncbi.nlm.nih.gov/pubmed/36530973
http://dx.doi.org/10.3389/fonc.2022.1053089
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