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Can MRI predict meningioma consistency?: a correlation with tumor pathology and systematic review

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Abstract

Tumor consistency is a critical factor that influences operative strategy and patient counseling. Magnetic resonance imaging (MRI) describes the concentration of water within living tissues and as such, is hypothesized to predict aspects of their biomechanical behavior. In meningiomas, MRI signal intensity has been used to predict the consistency of the tumor and its histopathological subtype, though its predictive capacity is debated in the literature. We performed a systematic review of the PubMed database since 1990 concerning MRI appearance and tumor consistency to assess whether or not MRI can be used reliably to predict tumor firmness. The inclusion criteria were case series and clinical studies that described attempts to correlate preoperative MRI findings with tumor consistency. The relationship between the pre-operative imaging characteristics, intraoperative findings, and World Health Organization (WHO) histopathological subtype is described. While T2 signal intensity and MR elastography provide a useful predictive measure of tumor consistency, other techniques have not been validated. T1-weighted imaging was not found to offer any diagnostic or predictive value. A quantitative assessment of T2 signal intensity more reliably predicts consistency than inherently variable qualitative analyses. Preoperative knowledge of tumor firmness affords the neurosurgeon substantial benefit when planning surgical techniques. Based upon our review of the literature, we currently recommend the use of T2-weighted MRI for predicting consistency, which has been shown to correlate well with analysis of tumor histological subtype. Development of standard measures of tumor consistency, standard MRI quantification metrics, and further exploration of MRI technique may improve the predictive ability of neuroimaging for meningiomas.

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Abbreviations

MRI:

Magnetic resonance imaging

CT:

Computed tomography

MD:

Mean diffusivity

PDWI:

Proton density weight imaging

FLAIR:

fluid attenuated inversion recovery

WHO:

World Health Organization

FIESTA:

Fast imaging employing steady-state acquisition

MRE:

Magnetic resonance elastography

FA:

Fractional anisography

ADC:

Apparent diffusion coefficient

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Author notes

  1. Amy Yao

    Present address: Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, Annenberg 8, One Gustave L Levy Pl, New York, NY, 10029, USA

Authors and Affiliations

  1. Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, Annenberg 8, One Gustave L Levy Pl, New York, NY, 10029, USA

    Margaret Pain, Priti Balchandani & Raj K. Shrivastava

Authors
  1. Amy Yao
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  2. Margaret Pain
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  3. Priti Balchandani
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  4. Raj K. Shrivastava
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Corresponding author

Correspondence to Amy Yao.

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The authors declare that they have no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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For this type of study formal consent is not required.

Additional information

Highlights

• Tumor consistency and histopathological subtype can be anticipated based on pre-operative MRI

• T2 weighted images have predictive value for tumor consistency and histopathology, while T1 weighted images do not

• Images hyperintense on T2WI relative to gray matter generally correlate with softer tumors, while hypointense images correlate with firmer tumors

• Quantitative assessment of tumor signal intensity using calculations of signal intensity ratios reliably predicts tumor consistency

• Magnetic resonance elastography and fractional anisotropy are advanced MRI techniques that show potential for preoperative assessment of meningioma consistency

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Yao, A., Pain, M., Balchandani, P. et al. Can MRI predict meningioma consistency?: a correlation with tumor pathology and systematic review. Neurosurg Rev 41, 745–753 (2018). https://doi.org/10.1007/s10143-016-0801-0

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  • DOI: https://doi.org/10.1007/s10143-016-0801-0

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