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The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion

OBJECTIVE: The preoperative MRI scans of meningiomas were analyzed based on the 2021 World Health Organization (WHO) Central Nervous System (CNS) Guidelines, and the efficacy of MRI features in diagnosing WHO grades and brain invasion was analyzed. MATERIALS AND METHODS: The data of 675 patients wit...

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Autores principales: Jiang, Jun, Yu, Juan, Liu, Xiajing, Deng, Kan, Zhuang, Kaichao, Lin, Fan, Luo, Liangping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890055/
https://www.ncbi.nlm.nih.gov/pubmed/36741697
http://dx.doi.org/10.3389/fonc.2022.1100350
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author Jiang, Jun
Yu, Juan
Liu, Xiajing
Deng, Kan
Zhuang, Kaichao
Lin, Fan
Luo, Liangping
author_facet Jiang, Jun
Yu, Juan
Liu, Xiajing
Deng, Kan
Zhuang, Kaichao
Lin, Fan
Luo, Liangping
author_sort Jiang, Jun
collection PubMed
description OBJECTIVE: The preoperative MRI scans of meningiomas were analyzed based on the 2021 World Health Organization (WHO) Central Nervous System (CNS) Guidelines, and the efficacy of MRI features in diagnosing WHO grades and brain invasion was analyzed. MATERIALS AND METHODS: The data of 675 patients with meningioma who underwent MRI in our hospital from 2006 to 2022, including 108 with brain invasion, were retrospectively analyzed. Referring to the WHO Guidelines for the Classification of Central Nervous System Tumors (Fifth Edition 2021), 17 features were analyzed, with age, sex and meningioma MRI features as risk factors for evaluating WHO grade and brain invasion. The risk factors were identified through multivariable logistic regression analysis, and their receiver operating characteristic (ROC) curves for predicting WHO grades and brain invasion were generated, and the area under the curve (AUC), sensitivity and specificity were calculated. RESULTS: Univariate analysis showed that sex, tumor size, lobulated sign, peritumoral edema, vascular flow void, bone invasion, tumor-brain interface, finger-like protrusion and mushroom sign were significant for diagnosing meningioma WHO grades, while these features and ADC value were significant for predicting brain invasion (P < 0.05). Multivariable logistic regression analysis showed that the lobulated sign, tumor-brain interface, finger-like protrusion, mushroom sign and bone invasion were independent risk factors for diagnosing meningioma WHO grades, while the above features, tumor size and ADC value were independent risk factors for diagnosing brain invasion (P < 0.05). The tumor-brain interface had the highest efficacy in evaluating WHO grade and brain invasion, with AUCs of 0.779 and 0.860, respectively. Combined, the variables had AUCs of 0.834 and 0.935 for determining WHO grade and brain invasion, respectively. CONCLUSION: Preoperative MRI has excellent performance in diagnosing meningioma WHO grade and brain invasion, while the tumor-brain interface serves as a key factor. The preoperative MRI characteristics of meningioma can help predict WHO grade and brain invasion, thus facilitating complete lesion resection and improving patient prognosis.
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spelling pubmed-98900552023-02-02 The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion Jiang, Jun Yu, Juan Liu, Xiajing Deng, Kan Zhuang, Kaichao Lin, Fan Luo, Liangping Front Oncol Oncology OBJECTIVE: The preoperative MRI scans of meningiomas were analyzed based on the 2021 World Health Organization (WHO) Central Nervous System (CNS) Guidelines, and the efficacy of MRI features in diagnosing WHO grades and brain invasion was analyzed. MATERIALS AND METHODS: The data of 675 patients with meningioma who underwent MRI in our hospital from 2006 to 2022, including 108 with brain invasion, were retrospectively analyzed. Referring to the WHO Guidelines for the Classification of Central Nervous System Tumors (Fifth Edition 2021), 17 features were analyzed, with age, sex and meningioma MRI features as risk factors for evaluating WHO grade and brain invasion. The risk factors were identified through multivariable logistic regression analysis, and their receiver operating characteristic (ROC) curves for predicting WHO grades and brain invasion were generated, and the area under the curve (AUC), sensitivity and specificity were calculated. RESULTS: Univariate analysis showed that sex, tumor size, lobulated sign, peritumoral edema, vascular flow void, bone invasion, tumor-brain interface, finger-like protrusion and mushroom sign were significant for diagnosing meningioma WHO grades, while these features and ADC value were significant for predicting brain invasion (P < 0.05). Multivariable logistic regression analysis showed that the lobulated sign, tumor-brain interface, finger-like protrusion, mushroom sign and bone invasion were independent risk factors for diagnosing meningioma WHO grades, while the above features, tumor size and ADC value were independent risk factors for diagnosing brain invasion (P < 0.05). The tumor-brain interface had the highest efficacy in evaluating WHO grade and brain invasion, with AUCs of 0.779 and 0.860, respectively. Combined, the variables had AUCs of 0.834 and 0.935 for determining WHO grade and brain invasion, respectively. CONCLUSION: Preoperative MRI has excellent performance in diagnosing meningioma WHO grade and brain invasion, while the tumor-brain interface serves as a key factor. The preoperative MRI characteristics of meningioma can help predict WHO grade and brain invasion, thus facilitating complete lesion resection and improving patient prognosis. Frontiers Media S.A. 2023-01-18 /pmc/articles/PMC9890055/ /pubmed/36741697 http://dx.doi.org/10.3389/fonc.2022.1100350 Text en Copyright © 2023 Jiang, Yu, Liu, Deng, Zhuang, Lin and Luo 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
Jiang, Jun
Yu, Juan
Liu, Xiajing
Deng, Kan
Zhuang, Kaichao
Lin, Fan
Luo, Liangping
The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion
title The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion
title_full The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion
title_fullStr The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion
title_full_unstemmed The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion
title_short The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion
title_sort efficacy of preoperative mri features in the diagnosis of meningioma who grade and brain invasion
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890055/
https://www.ncbi.nlm.nih.gov/pubmed/36741697
http://dx.doi.org/10.3389/fonc.2022.1100350
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