Meningioma in Focus: Charting the Terrain of Imaging, Grading, and Pathological Vistas
Novelty in Biomedicine,
Vol. 12 No. 2 (2024),
29 April 2024
,
Page 75- 83
https://doi.org/10.22037/nbm.v12i2.44438
Abstract
Background: Meningiomas constitute a significant proportion of primary intracranial tumors, demanding a nuanced understanding of their radiological features for informed clinical decisions. This prospective study aimed to explore the intricate relationship between magnetic resonance imaging (MRI) findings and the pathological grade of meningiomas to provide insights into their diverse characteristics.
Materials and Methods: A cohort of 52 meningioma patients underwent comprehensive MRI evaluations. The study encompassed various aspects of tumor radiology, including location, peritumoral edema severity, tumor margin distinctiveness, bone infiltration, adjacent bone reaction, apparent diffusion coefficient (ADC) patterns, intratumoral calcifications, bleeding within the tumor, vascularization, and tumor enhancement.
Results: The analysis revealed that 73.1% of patients presented with grade 1 meningioma, while 26.9% exhibited grade 2 tumors, with no grade 3 cases detected. Intriguingly, while age and gender did not significantly differ between grades, several MRI findings demonstrated noteworthy distinctions. Grade 2 meningiomas were associated with moderate to severe peritumoral edema, indistinct tumor margins, increased vascularization, and heterogeneous tumor enhancement patterns. Notably, logistic regression analysis indicated that none of the investigated radiological parameters independently predicted the pathological grade of meningioma.
Conclusion: These findings emphasize the need for a comprehensive meningioma assessment approach, integrating radiological insights into clinical decision-making and prognosis for enhanced patient care.
- Meningioma
- Pathological grade
- MRI findings
How to Cite
References
Wiemels J, Wrensch M, Claus EB. Epidemiology and etiology of meningioma. Journal of neuro-oncology. 2010;99:307-14.
Liu Y, Li F, Zhu S, Liu M, Wu C. Clinical features and treatment of meningiomas in children: report of 12 cases and literature review. Pediatric neurosurgery. 2008;44(2):112-7.
Umansky F, Shoshan Y, Rosenthal G, Fraifeld S, Spektor S. Radiation-induced meningioma. Neurosurgical focus. 2008;24(5):E7.
Zamanipoor Najafabadi AH, van der Meer PB, Boele FW, et al. Determinants and predictors for the long-term disease burden of intracranial meningioma patients. Journal of Neuro-oncology. 2021;151:201-10.
Ogasawara C, Philbrick BD, Adamson DC. Meningioma: a review of epidemiology, pathology, diagnosis, treatment, and future directions. Biomedicines. 2021;9(3):319.
Hamilton BE, Salzman K, Patel N, et al. Imaging and clinical characteristics of temporal bone meningioma. American journal of neuroradiology. 2006;27(10):2204-9.
Neromyliotis E, Kalamatianos T, Paschalis A, et al. Machine learning in meningioma MRI: past to present. A narrative review. Journal of Magnetic Resonance Imaging. 2022;55(1):48-60.
Alyamany M, Alshardan M, Jamea A, ElBakry N, Soualmi L, Orz Y. Meningioma consistency: Correlation between magnetic resonance imaging characteristics, operative findings, and histopathological features. Asian journal of neurosurgery. 2018;13(02):324-8.
Lin B-J, Chou K-N, Kao H-W, et al. Correlation between magnetic resonance imaging grading and pathological grading in meningioma. Journal of neurosurgery. 2014;121(5):1201-8.
Baldi I, Engelhardt J, Bonnet C, et al. Epidemiology of meningiomas. Neurochirurgie. 2018;64(1):5-14.
Bozdag M, Er A. Relation of susceptibility-weighted imaging findings with histological grade in intracranial meningiomas. 2021.
Hale AT, Wang L, Strother MK, Chambless LB. Differentiating meningioma grade by imaging features on magnetic resonance imaging. Journal of Clinical Neuroscience. 2018;48:71-5.
Zhang S, Chiang GC-Y, Knapp JM, et al. Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping. Journal of Neuroradiology. 2020;47(4):272-7.
Amano T, Nakamizo A, Murata H, et al. Preoperative prediction of intracranial meningioma grade using conventional CT and MRI. Cureus. 2022;14(1).
Radeesri K, Lekhavat V. The Role of Pre-Operative MRI for Prediction of High-Grade Intracranial Meningioma: A Retrospective Study. Asian Pacific Journal of Cancer Prevention. 2023;24(3):819-25.
Lekhavat V, Radeesri K. The Role of Pre-operative MRI for Prediction of High-Grade Intracranial Meningioma: A Retrospective Study. 2021.
Pereira-Filho NdA, Soares FP, Chemale IdM, Coutinho LMB. Peritumoral brain edema in intracranial meningiomas. Arquivos de neuro-psiquiatria. 2010;68:346-9.
Simis A, de Aguiar PHP, Leite CC, Santana Jr PA, Rosemberg S, Teixeira MJ. Peritumoral brain edema in benign meningiomas: correlation with clinical, radiologic, and surgical factors and possible role on recurrence. Surgical neurology. 2008;70(5):471-7.
Tanaka M, Imhof HG, Schucknecht B, Kollias S, Yonekawa Y, Valavanis A. Correlation between the efferent venous drainage of the tumor and peritumoral edema in intracranial meningiomas: superselective angiographic analysis of 25 cases. Journal of neurosurgery. 2006;104(3):382-8.
Gurkanlar D, Er U, Sanlı M, Özkan M, Sekerci Z. Peritumoral brain edema in intracranial meningiomas. Journal of clinical neuroscience. 2005;12(7):750-3.
Schmid S, Aboul-Enein F, Pfisterer W, Birkner T, Stadek C, Knosp E. Vascular endothelial growth factor: the major factor for tumor neovascularization and edema formation in meningioma patients. Neurosurgery. 2010;67(6):1703-8.
Thomae W, Schmid S, Pfisterer W, Knosp E. Vascular Endothelial Growth Factor—the Major Factor for Tumor (Neo-) Vascularization and Edema Formation in Meningioma Patients. Skull Base. 2009;19(01):A302.
Hsu C-C, Pai C-Y, Kao H-W, Hsueh C-J, Hsu W-L, Lo C-P. Do aggressive imaging features correlate with advanced histopathological grade in meningiomas? Journal of Clinical Neuroscience. 2010;17(5):584-7.
Pistolesi S, Fontanini G, Camacci T, et al. Meningioma-associated brain oedema: the role of angiogenic factors and pial blood supply. Journal of neuro-oncology. 2002;60:159-64.
Nagar V, Ye J, Ng W, et al. Diffusion-weighted MR imaging: diagnosing atypical or malignant meningiomas and detecting tumor dedifferentiation. American Journal of Neuroradiology. 2008;29(6):1147-52.
Yao Y, Xu Y, Liu S, et al. Predicting the grade of meningiomas by clinical–radiological features: A comparison of precontrast and postcontrast MRI. Frontiers in Oncology. 2022;12:1053089.
Hwang WL, Marciscano AE, Niemierko A, et al. Imaging and extent of surgical resection predict risk of meningioma recurrence better than WHO histopathological grade. Neuro-oncology. 2016;18(6):863-72.
- Abstract Viewed: 155 times
- PDF Downloaded: 83 times