Ali ER, Mustafa BOZDAĞ

Relation of susceptibility-weighted imaging findings withhistological grade in intracranial meningiomas

Aim: We aimed to investigate the relation of susceptibility-weighted imaging (SWI) findings with histological grade in intracranialmeningiomas.Materials and Methods: Histopathologically confirmed 58 intracranial meningioma patients (48 typical (low-grade meningioma), 10atypical (high-grade meningioma)) who had undergone preoperative SWI between 2015 and 2020 were retrospectively evaluated.Tumor size, location, presence of peritumoral edema, WHO grade, low-grade meningioma subtypes and Ki-67 proliferation indexeswere noted. SWI findings of intracranial meningiomas were categorized as either positive or negative based on presence/absence ofintratumoral susceptibility signals (ITSSs). The origin of ITSSs in SWI-positive meningiomas was assessed with phase images andclassified as calcification (SWI-C), vascular structure (SWI-V) or hemorrhage (SWI-H). Mann-Whitney U, chi-square, Fisher’s exacttests and multiple logistic regression analyses were performed for statistical assessment.Results: There was a significant association between SWI-positivity and low-grade in meningiomas (p = 0.010). A higher incidenceof calcification was found in low-grade meningiomas (%60 in low-grade vs %10 in high-grade). Peritumoral edema was found to beassociated with high grade in meningiomas (p = 0.032). Ki-67 proliferation index was significantly higher in high-grade meningiomascompared to low-grade. (p = 0.000).Conclusion: SWI combined with peritumoral edema may help to predict high grade in intracranial meningiomas.

PDF

___

1. Chamoun R, Krisht KM, Couldwell WT. Incidental meningiomas. Neurosurg Focus 2011;31:19.
2. Louis DN, Perry A, Reifenberger G, et al. The 2016 World HealthOrganizationclassification of tumors of thecentralnervoussystem: a summary. Acta Neuropathol 2016;131:803-20.
3. Claus EB, Bondy ML, Schildkraut JM, et al. Epidemiology of intracranial meningioma. Neurosurgery 2005;57:1088-95.
4. Riemenschneider MJ, Perry A, Reifenberger G. Histological classificationandmoleculargenetics of meningiomas. Lancet Neurol 2006;5:1045-54.
5. Watts J, Box G, Galvin A, et al. Magnetic resonance imaging of meningiomas: a pictorial review. Insights Imaging 2014;5:113-22.
6. Mittal S, Wu Z, Neelavalli J, et al. Susceptibilityweighted imaging:technical aspects and clinical applications, part 2. AJNR Am J Neuroradiol 2009;30:232-52.
7. Haacke EM, Xu Y, Cheng YC, et al. Susceptibilityweighted imaging (SWI). Magn Reson Med 2004;52:612-8.
8. Haacke EM, Mittal S, Wu Z, et al. Susceptibility weighted imaging: technical aspects and clinical applications, part 1. AJNR Am J Neuroradiol 2009;30:19-30.
9. Chen W, Zhu W, Kovanlikaya I, et al. Intracranial calcifications and hemorrhages: characterization with quantitative susceptibility mapping. Radiology 2014;270:496-505.
10. Ding Y, Xing Z, Liu B, et al. Differentiation of primary central nervous system lymphoma from high-grade glioma and brain metastases using susceptibilityweighted imaging. Brain Behav 2014;4:841-9.
11. Kim HS, Jahng GH, Ryu CW, et al. Added value and diagnostic performance of intratumoral susceptibility signals in the differential diagnosis of solitary enhancing brain lesions: preliminary study. Am J Neuroradiol 2009;30:1574-9.
12. Yu Y, Zhang H, Xiao Z, et al. Diffusion-weighted MRI combined with susceptibility-weighted MRI: added diagnostic value for four common lateral ventricular tumors. Acta Radiol 2018;59:980-7.
13. Saini J, Gupta PK, Sahoo P, et al. Differentiation of grade II/III and grade IV glioma by combining “T1 contrast enhanced brain perfusion imaging” and susceptibility-weighted quantitative imaging. Neuroradiology 2018;60:43-50.
14. Chen T, Jiang B, Zheng Y, et al. Differentiating intracranial solitary fibrous tumor/hemangiopericytoma from meningioma using diffusion-weighted imaging and susceptibility-weighted imaging. Neuroradiology 2020;62:175-84.
15. Oya S, Kim SH, Sade B, et al. The natural history of intracranial meningiomas. J Neurosurg 2011;114:1250-6.
16. 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 Oncol 2016;18:863- 72.
17. Adams LC, Böker SM, Bender YY, et al. Assessment of intracranial meningioma-associated calcifications using susceptibility-weighted MRI. J Magn Reson Imaging 2017;46:1177-86.
18. Zhang S, Chiang GC, Knapp JM, et al. Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping. J Neuroradiol 2020;47:272-7.
19. Liang RF, Xiu YJ, Wang X, et al. The potential risk factors for atypical and anaplastic meningiomas: clinical series of 1,239 cases. Int J Clin Exp Med 2014;7:5696-700.
20. Hale AT, Wang L, Strother MK, et al. Differentiating meningioma grade by imaging features on magnetic resonance imaging. J Clin Neurosci 2018;48:71-5.
21. Pistolesi S, Fontanini G, Camacci T, et al. Meningioma associated brain oedema: the role of angiogenic factors and pial blood supply. J Neurooncol 2002;60:159-64.
22. Osawa T, Tosaka M, Nagaishi M, et al. Factors affecting peritumoral brain edema in meningioma: special histological subtypes with prominently extensive edema. J Neurooncol 2013;111:49-57.
23. Hsu C-C, Pai C-Y, Kao H-W, et al. Do aggressive imaging features correlate with advanced histopathological grade in meningiomas? J Clin Neurosci 201017:584- 7.
24. Li H, Zhao M, Jiao Y, et al. Prediction of high-grade pediatric meningiomas: magnetic resonance imaging features based on T1-weighted, T2-weighted, and contrast-enhanced T1-weighted images. World Neurosurg 2016;91:89-95.
25. Watanabe Y, Yamasaki F, Kajiwara Y, et al. Preoperative histological grading of meningiomas using apparent diffusion coefficient at 3T MRI. Eur J Radiol 2013;82:658-63.
26. Mukhopadhyay M, Das C, Kumari M ,et al.Spectrum of meningioma with special reference to prognostic utility of ER, PR and Ki67 expression. J Lab Physicians 2017;9:308-13.