Prediction of consistency of meningiomas with preoperative magnetic resonance imaging
- PMID: 9400639
- DOI: 10.1016/s0090-3019(96)00439-9
Prediction of consistency of meningiomas with preoperative magnetic resonance imaging
Abstract
Background: The consistency of a meningioma is one of the important factors in determining the surgical outcome. If the surgeon is aware of the consistency of a meningioma preoperatively, the surgical plans will be influenced. A few papers have described the correlation between consistency of meningiomas and their magnetic resonance imaging (MRI) findings. However, prediction of consistency with MRI is still difficult. We have tried to predict the consistency of meningiomas with MRI findings more precisely.
Methods and results: Fifty patients diagnosed as having intracranial meningiomas were studied with 1.5 Tesla MRI. We compared the MRI findings with tumor consistency. The intensities of the tumors were categorized into three grades (low, iso, and high) compared to that of the gray matter. T1-weighted images had no specifics, but T2-weighted images and proton density images were useful for the prediction of tumor consistency. Hyperintensity on protein density (PD) and T2-weighted images was a sign of a soft tumor.
Conclusion: We presume that T2 and PD are useful for predicting consistency of meningiomas, and their water content is one of the main factors in their consistency. Histology may be one of the factors helpful in defining the consistency of a tumor. In this series, we found no relationship between histology and MRI findings, nor between histology and consistency. If the meningioma is believed to be hard, preoperative endovascular embolization is beneficial, which will induce necrosis of the meningioma and make it soft enough to be removed more easily and safety.
Similar articles
-
Diffusion tensor magnetic resonance imaging for predicting the consistency of intracranial meningiomas.Acta Neurochir (Wien). 2014 Oct;156(10):1837-45. doi: 10.1007/s00701-014-2149-y. Epub 2014 Jul 8. Acta Neurochir (Wien). 2014. PMID: 25002281
-
Prediction of meningioma consistency using fractional anisotropy value measured by magnetic resonance imaging.J Neurosurg. 2007 Oct;107(4):784-7. doi: 10.3171/JNS-07/10/0784. J Neurosurg. 2007. PMID: 17937223 Clinical Trial.
-
Prediction of hard meningiomas: quantitative evaluation based on the magnetic resonance signal intensity.Acta Radiol. 2016 Mar;57(3):333-40. doi: 10.1177/0284185115578323. Epub 2015 Mar 29. Acta Radiol. 2016. PMID: 25824207
-
Intracranial meningiomas: correlations between MR imaging and histology.Eur J Radiol. 1999 Jul;31(1):69-75. doi: 10.1016/s0720-048x(98)00083-7. Eur J Radiol. 1999. PMID: 10477102 Review.
-
Magnetic resonance imaging of meningiomas.Semin Ultrasound CT MR. 1992 Jun;13(3):154-69. Semin Ultrasound CT MR. 1992. PMID: 1642904 Review.
Cited by
-
Benefits of Combined MRI Sequences in Meningioma Consistency Prediction: A Prospective Study of 287 Consecutive Patients.Asian J Neurosurg. 2022 Dec 10;17(4):614-620. doi: 10.1055/s-0042-1758849. eCollection 2022 Dec. Asian J Neurosurg. 2022. PMID: 36570751 Free PMC article.
-
Differentiation of benign angiomatous and microcystic meningiomas with extensive peritumoral edema from high grade meningiomas with aid of diffusion weighted MRI.Biomed Res Int. 2014;2014:650939. doi: 10.1155/2014/650939. Epub 2014 Nov 16. Biomed Res Int. 2014. PMID: 25478572 Free PMC article.
-
Preoperative Assessment of Meningioma Consistency Using a Combination of MR Elastography and DTI.AJNR Am J Neuroradiol. 2024 Nov 7;45(11):1755-1761. doi: 10.3174/ajnr.A8385. AJNR Am J Neuroradiol. 2024. PMID: 38906671
-
Predicting intraoperative meningioma consistency using features from standard MRI sequences: a preoperative evaluation.Acta Neurochir (Wien). 2025 Jun 21;167(1):173. doi: 10.1007/s00701-025-06582-9. Acta Neurochir (Wien). 2025. PMID: 40542946 Free PMC article.
-
Head, neck, and brain tumor embolization guidelines.J Neurointerv Surg. 2012 Jul;4(4):251-5. doi: 10.1136/neurintsurg-2012-010350. Epub 2012 Apr 26. J Neurointerv Surg. 2012. PMID: 22539531 Free PMC article. Review.
MeSH terms
LinkOut - more resources
Full Text Sources
Medical