Evidence map›Paper›PMID 41518389›Full record

ArticleNeuroradiology2026

Diagnostic Value of Routine MRI Parameters in Identifying High-Grade Intracranial Meningiomas.

Mariana Duarte Gomes, Henrique Manuel Campos Cardoso, Rita Coutinho, Miguel Quintas-Neves

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Article in Neuroradiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Mariana Duarte GomesDepartment of Neuroradiology, Unidade Local de Saúde de Braga, Braga, Portugal.
Henrique Manuel Campos CardosoLife and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.
Rita CoutinhoDepartment of Neuroradiology, Unidade Local de Saúde de Braga, Braga, Portugal.
Miguel Quintas-NevesDepartment of Neuroradiology, Unidade Local de Saúde de Braga, Braga, Portugal. mlqneves@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate whether preoperative MRI features can accurately predict WHO grade 2/3 meningiomas using routinely available imaging parameters. MATERIALS AND

methodsThis retrospective single-centre study included 282 patients (mean age 58.4 ± 13.4 years; 176 women) who underwent surgery for histologically confirmed meningiomas between 2010 and 2024. Preoperative MRI was assessed for tumour volume, peritumoral oedema, heterogeneous enhancement, cystic components, midline shift, and normalized apparent diffusion coefficient (NADC). Univariable and multivariable logistic regression analyses identified independent predictors of high-grade meningiomas (WHO grade 2/3). Model performance was evaluated with ROC curve analysis.

resultsAmong 282 meningiomas, 78% were WHO grade 1 and 22% were grade 2 or 3. High-grade tumours were significantly associated with tumour volume ≥ 45 cc (p= 0.016), presence of cystic components (p = 0.005), midline shift > 3 mm (p = 0.024), and NADC < 1.07 (p = 0.028). These features remained independently associated with higher grade in the multivariable model. The resulting model achieved an AUC of 0.768 (95% CI: 0.689-0.847), with 75.5% sensitivity and 62.8% specificity at the optimal threshold.

conclusionWe obtained a multivariable MRI-based model combining morphologic and diffusion features that potentially enables preoperative risk stratification of meningiomas and supports surgical decision-making. Further validation in prospective, multicentre cohorts is warranted.

Indexed as

Magnetic Resonance ImagingMeningeal NeoplasmsMeningiomaAgedFemaleHumansMaleMiddle AgedNeoplasm GradingRetrospective StudiesSensitivity and SpecificityApparent diffusion coefficientMeningiomaMRIPreoperative risk stratificationTumour grading

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.