ArticleNeuroradiology2020
Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously treated meningiomas.
Article in Neuroradiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 13 citations in OpenAlex.
- Multiparametric analysis using MRI after preoperative embolization in meningioma: a preliminary study.Radiological physics and technology · 2026Article
- Multi-parametric MRI-based machine learning model for prediction of WHO grading in patients with meningiomas.European radiology · 2024Article
- Are there predilection sites for intracranial meningioma? A population-based atlas.Neurosurgical review · 2022Article
- Predicting the grade of meningiomas by clinical-radiological features: A comparison of precontrast and postcontrast MRI.Frontiers in oncology · 2022Article
- Intravoxel incoherent motion as a tool to detect early microstructural changes in meningiomas treated with proton therapy.Neuroradiology · 2021Article
- PET/MR Imaging of Somatostatin Receptor Expression and Tumor Vascularity in Meningioma: Implications for Pathophysiology and Tumor Outcomes.Frontiers in oncology · 2021Article
- Brain MRI Radiomic First-Order Features for Presurgical Prediction of Meningioma Grading.Journal of neuroimaging : official journal of the American Society of NeuroimagingArticle
- Differentiation of Low and High-Grade Meningiomas Using Transfer Learning on MR Images.Healthcare technology lettersArticle
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Authors and funding
14 authors at 6 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
purposeMeningiomas are mainly benign tumors, though a considerable proportion shows aggressive behaviors histologically consistent with atypia/anaplasia. Histopathological grading is usually assessed through invasive procedures, which is not always feasible due to the inaccessibility of the lesion or to treatment contraindications. Therefore, we propose a multi-parametric MRI assessment as a predictor of meningioma histopathological grading.
methodsSeventy-three patients with 74 histologically proven and previously treated meningiomas were retrospectively enrolled (42 WHO I, 24 WHO II, 8 WHO III) and studied with MRI including T2 TSE, FLAIR, Gradient Echo, DWI, and pre- and post-contrast T1 sequences. Lesion masks were segmented on post-contrast T1 sequences and rigidly registered to ADC maps to extract quantitative parameters from conventional DWI and intravoxel incoherent motion model assessing tumor perfusion. Two expert neuroradiologists assessed morphological features of meningiomas with semi-quantitative scores.
resultsUnivariate analysis showed different distributions (p < 0.05) of quantitative diffusion parameters (Wilcoxon rank-sum test) and morphological features (Pearson's chi-square; Fisher's exact test) among meningiomas grouped in low-grade (WHO I) and higher grade forms (WHO II/III); the only exception consisted of the tumor-brain interface. A multivariate logistic regression, combining all parameters showing statistical significance in the univariate analysis, allowed discrimination between the groups of meningiomas with high sensitivity (0.968) and specificity (0.925). Heterogeneous contrast enhancement and low ADC were the best independent predictors of atypia and anaplasia.
conclusionOur multi-parametric MRI assessment showed high sensitivity and specificity in predicting histological grading of meningiomas. Such an assessment may be clinically useful in characterizing lesions without histological diagnosis. Key points • When surgery and biopsy are not feasible, parameters obtained from both conventional and diffusion-weighted MRI can predict atypia and anaplasia in meningiomas with high sensitivity and specificity. • Low ADC values and heterogeneous contrast enhancement are the best predictors of higher grade meningioma.
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