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Meta-Analysis
. 2018 Jul;41(3):745-753.
doi: 10.1007/s10143-016-0801-0. Epub 2016 Nov 21.

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

Affiliations
Meta-Analysis

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

Amy Yao et al. Neurosurg Rev. 2018 Jul.

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.

Keywords: Magnetic resonance imaging; Meningioma; Pathology; Tumor consistency.

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Conflict of interest statement

Disclosure of Potential Conflicts of Interest

The authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1
Flow chart outlining the selection process of relevant studies.
Figure 2
Figure 2
Corresponding axial MR imaging of a large L anterior fronto-parietal meningioma appears iso- to hypo-intense on T1WI (A) and iso- to hyper-intense on T2WI (B) relative to adjacent gray matter. Lesion appears isointense to gray matter on apparent difficusion coefficient imaging (ADC) (C) and hyperintense on T2 FLAIR (D). Imaging performed at 1.5T. This meningioma was found to be soft intraoperatively. ROI analysis, calculated as signal intensity (SI) of lesion/SI of adjacent gray matter (GM) determined the lesion to be hyper-intense to surrounding GM (B, green circles).
Figure 3
Figure 3
Corresponding axial MR imaging of a large R anterior frontal meningioma appears isointense on T1WI (A) and iso- to hypo-intense on T2WI (B) relative to adjacent gray matter. Lesion appears isointense to gray matter on apparent difficusion coefficient imaging (ADC) (C) and iso- to hyper-intense on T2 FLAIR (D). Imaging performed at 1.5T. Subjective determination of intensity relative to gray matter on T2WI is difficult in this case and warrants quantitative analysis. This meningioma was found to be firm and fibrous intraoperatively. ROI analysis, calculated as signal intensity (SI) of lesion/SI of adjacent gray matter (GM) determined the lesion to be hypo-intense to surrounding GM (B, green circles).

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