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Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously treated meningiomas

  • Diagnostic Neuroradiology
  • Published:
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Abstract

Purpose

Meningiomas 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.

Methods

Seventy-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.

Results

Univariate 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.

Conclusion

Our 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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Abbreviations

CE:

Contrast enhancement

HGM:

High-grade meningioma

LGM:

Low-grade meningioma

IVIM:

Intravoxel incoherent motion

VIBE:

Volumetric interpolated breath-hold examination

PTE:

Peritumoral edema

CapE:

Capsular enhancement

TBI:

Tumor-brain interface

AUC:

Area under the curve

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Acknowledgements

The authors would like to thank our patients and their families for participating in our research.

Funding

No funding was received for this study.

Author information

Authors and Affiliations

  1. Department of Clinical Surgical Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy

    Simone Sacco, Francesco Ballati, Clara Gaetani & Lorenzo Preda

  2. Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA, USA

    Simone Sacco

  3. Department of Radiology, Valduce Hospital, Como, Italy

    Pascal Lomoro

  4. Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy

    Lisa Maria Farina, Ana Bacila & Stefano Bastianello

  5. Diagnostic Imaging Unit, National Center of Oncological Hadrontherapy (CNAO), Strada Campeggi, 53, 27100, Pavia, PV, Italy

    Sara Imparato & Lorenzo Preda

  6. Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy

    Chiara Paganelli, Giulia Buizza & Guido Baroni

  7. Radiotherapy Unit, National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy

    Alberto Iannalfi & Francesca Valvo

  8. Bioengineering Unit, National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy

    Guido Baroni

  9. Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy

    Stefano Bastianello

Authors
  1. Simone Sacco
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  2. Francesco Ballati
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  3. Clara Gaetani
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  9. Giulia Buizza
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  10. Alberto Iannalfi
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  13. Stefano Bastianello
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  14. Lorenzo Preda
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Corresponding author

Correspondence to Lorenzo Preda.

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Sacco, S., Ballati, F., Gaetani, C. et al. Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously treated meningiomas. Neuroradiology 62, 1441–1449 (2020). https://doi.org/10.1007/s00234-020-02476-y

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