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

Abstract

ObjectiveThe 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 methodsThe 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.ResultsUnivariate 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.ConclusionPreoperative 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.

Multiparameter MRI-based radiomics nomogram for preoperative prediction of brain invasion in atypical meningioma:a multicentre study

“…The reason for this is that the new, revised criteria include BI as an independent, histological criterion for diagnosing AM. Formerly WHO grade 1 meningioma patients were included as having AM once the new BI-based criterion was applied to them, resulting in an increase of 1–10% in the incidence of AM [ 23 , 34 ], as well as an increase in the proportion of BI in AM. In terms of clinical risk factors for BI in AM, our study found that patient sex, age, tumor location, and V Tumor were not involved, consistent with the findings of several studies [ 8 , 29 ].…”

“…Several previous studies explored the correlation between BI and imaging features, such as peritumoral edema (PE), enhanced heterogeneity and irregular tumor shape, which were the independent risk predictors of BI [ 19 – 23 ]. Radiomics is an emerging image processing method developed in recent years that allows high-throughput extraction and quantitative analysis of radiomics features in images that cannot be identified by the naked eye [ 24 , 25 ].…”

Surgical Management of High-Grade Meningiomas

“…There are several suggestive radiographic features that may be used to differentiate high-grade from benign meningiomas, including a lower apparent diffusion coefficient (reflecting higher cellularity), the radiographic sign of “mushrooming”, and high signal intensity on fluid-attenuated inversion recovery (FLAIR) sequences. A definitive pathological grade, however, cannot be established radiographically [ 4 , 5 ].…”

Wichtige Neuerungen in der WHO-Klassifikation der ZNS-Tumoren mit neuroradiologischer Relevanz

“…In einer aktuellen retrospektiven Studie von 675 Patienten mit einem Meningeom fanden sich 108 Fälle mit Hirninvasion des Tumors. Dabei konnten statistisch das Ausmaß des peritumoralen Ödems, die Größe des Tumors und niedrige ADC-Werte als unabhängige Prädiktoren für die Wahrscheinlichkeit des Nachweises einer Hirninvasion ermittelt werden [19].…”