Predicting Meningioma Consistency on Preoperative Neuroimaging Studies

Shiroishi, Mark S.; Cen, Steven; Tamrazi, Benita; d’Amore, Francesco; Lerner, Alexander; King, Kevin S.; Kim, Paul E.; Law, Meng; Hwang, Darryl; Boyko, Orest B.; Liu, Chia Shang J.

doi:10.1016/j.nec.2015.11.007

Cited by 37 publications

(33 citation statements)

References 41 publications

(92 reference statements)

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“…Increased necrosis, intratumoral heterogeneity, nonspherical shape, and larger volumes predicted higher-grade lesions. Other advanced imaging modalities, such as fractal-based analysis 9,14,15 as well as diffusion MRI, MR elastography, and MR spectroscopy, 28,30 have been employed to predict meningioma aggressiveness. Imaging analysis may complement genomic categorization to impact surgical decisionmaking.…”

Section: Discussionmentioning

confidence: 99%

Clinical potential of meningioma genomic insights: a practical review for neurosurgeons

Karsy

Azab

Abou‐Al‐Shaar

et al. 2018

Neurosurgical Focus

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Meningiomas are among the most common intracranial pathological conditions, accounting for 36% of intracranial lesions treated by neurosurgeons. Although the majority of these lesions are benign, the classical categorization of tumors by histological type or World Health Organization (WHO) grade has not fully captured the potential for meningioma progression and recurrence. Many targeted treatments have failed to generate a long-lasting effect on these tumors. Recently, several seminal studies evaluating the genomics of intracranial meningiomas have rapidly changed the understanding of the disease. The importance of NF2 (neurofibromin 2), TRAF7 (tumor necrosis factor [TNF] receptor–associated factor 7), KLF4 (Kruppel-like factor 4), AKT1, SMO (smoothened), PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha), and POLR2 (RNA polymerase II subunit A) demonstrates that there are at least 6 distinct mutational classes of meningiomas. In addition, 6 methylation classes of meningioma have been appreciated, enabling improved prediction of prognosis compared with traditional WHO grades. Genomic studies have shed light on the nature of recurrent meningioma, distinct intracranial locations and mutational patterns, and a potential embryonic cancer stem cell–like origin. However, despite these exciting findings, the clinical relevance of these findings remains elusive. The authors review the key findings from recent genomic studies in meningiomas, specifically focusing on how these findings relate to clinical insights for the practicing neurosurgeon.

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Section: Discussionmentioning

confidence: 99%

Clinical potential of meningioma genomic insights: a practical review for neurosurgeons

Karsy

Azab

Abou‐Al‐Shaar

et al. 2018

Neurosurgical Focus

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“…However, previous studies vary widely in scope and quality, and the accuracy of current neuroimaging techniques remains controversial. A recent review by Shiroishi et al provides a good summary of the existing literature but does not address study quality or correlation with tumor pathology [35]. The purpose of this study is to provide an updated review of the use of MRI to predict meningioma consistency.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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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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“…Currently, most of the available literature indicates the value of T2W imaging and show promising results with DTI and MRE techniques. 20 The authors experience suggests that the meningioma signal on T2W images provides a good prediction of tumor consistency. Lower signal implies a more fibrous, less easily suctioned tumors which may be riskier and more difficult to remove, especially when the tumor extends into the vicinity of cranial nerves.…”

Section: Tumor Consistencymentioning

confidence: 97%

“…The hyperintensity on T2W imaging of soft tumors may be related to higher water content while the lower signal on T2W imaging for hard tumors might be due to less water and more collagen and calcium content. 20 Likewise, the CT scan with bone window also provides information on calcification and hyperostosis of meningiomas which are associated to harder tumor consistency.…”

Section: Tumor Consistencymentioning

confidence: 99%

Approach Selection and Surgical Planning in Posterior Cranial Fossa Meningiomas: How I Do It

Beer‐Furlan

Vellutini²,

Gomes³

et al. 2018

J Neurol Surg B

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Posterior cranial fossa meningiomas represent approximately 9% of all the intracranial meningiomas. Despite the recent reports of radiation therapy in the management of these tumors, surgical resection continues to be the first line of treatment method aiming the permanent meningioma eradication. The evolution of imaging studies improved the preoperative evaluation of meningiomas providing greater anatomical detail of small structures not previously visualized. Nonetheless, the preoperative radiological evaluation should go beyond the differential diagnosis of a posterior fossa tumor. Anatomo-radiological assessment of meningiomas is discussed in detail. Based on our clinical experience, literature review, and case illustration, we highlight important preoperative anatomo-radiological aspects of posterior fossa meningiomas and their implications in the surgical management of these tumors.

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Predicting Meningioma Consistency on Preoperative Neuroimaging Studies

Cited by 37 publications

References 41 publications

Clinical potential of meningioma genomic insights: a practical review for neurosurgeons

Clinical potential of meningioma genomic insights: a practical review for neurosurgeons

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

Approach Selection and Surgical Planning in Posterior Cranial Fossa Meningiomas: How I Do It

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