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Purpose <p>To evaluate whether preoperative MRI features can accurately predict WHO grade 2/3 meningiomas using routinely available imaging parameters. </p> Materials and methods <p>This 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.</p> Results <p>Among 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 (<i>p</i>= 0.016), presence of cystic components (<i>p</i> = 0.005), midline shift &gt; 3 mm (<i>p</i> = 0.024), and NADC &lt; 1.07 (<i>p </i>= 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.</p> Conclusion <p>We 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.</p>

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

  • 期刊论文

  • 发表日期：

    2026年1月10日

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

摘要

Purpose

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

Materials and methods

This 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.

Results

Among 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.

Conclusion

We 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.