Abstract
Purpose
Microcystic meningioma (MCM) appears similar to atypical meningioma(AM) as per conventional diagnostic imaging. However, considering their different recurrence rate and prognosis, accurate differential diagnosis is essential for determine the appropriate treatment strategy. The aim of the study was to differentiate MCM from AM by diffusion-weighted imaging (DWI), in order to provide the basis for accurate preoperative diagnosis.
Methods
The preoperative clinical data, conventional MRI and DWI data of 15 MCM and 30 AM cases were retrospectively analyzed. The average apparent diffusion coefficient (ADCmean), minimum ADC (ADCmin) and normalized ADC (nADC) between MCM and AM were compared using two sample t-tests. The value of ADCmean, ADCmin and nADC in the differential diagnosis of MCM and AM were calculated by the receiver operating curve (ROC) analysis.
Results
The ADCmean (1.06 ± 0.10 vs 0.80 ± 0.11 × 10−3 mm2/s; P < 0.001), ADCmin (0.99 ± 0.10 vs 0.74 ± 0.12 × 10−3 mm2/s; P < 0.001) and nADC (1.45 ± 0.17 vs 1.07 ± 0.17; P < .0001) were significantly higher in MCM compared to AM. ADCmean of 0.91 × 10−3 mm2/s showed an optimum area under the ROC curve of 0.967 ± 0.022, and distinguished between MCM and AM with 86.67% sensitivity, 100% specificity and 88.89% accuracy. In addition, its positive and negative predictive values were 96.29% and 77.78% respectively.
Conclusions
DWI can differentially diagnose MCM and AM, and ADCmean is a potential quantitative tool that can improve preoperative diagnosis of both tumors.
Similar content being viewed by others
References
Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, Ohgaki H, Wiestler OD, Kleihues P, Ellison DW (2016) The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131(6):803–820. https://doi.org/10.1007/s00401-016-1545-1
Danisman MC, Kelesoglu KS, Sivri M, Koplay M, Paksoy Y (2017) Microcystic meningioma: difficulties in diagnosis and magnetic resonance imaging findings. Acta Neurol Belg 117(3):745–747. https://doi.org/10.1007/s13760-017-0760-4
Wiemels J, Wrensch M, Claus EB (2010) Epidemiology and etiology of meningioma. J Neuro-Oncol 99(3):307–314. https://doi.org/10.1007/s11060-010-0386-3
Buerki RA, Horbinski CM, Kruser T, Horowitz PM, James CD, Lukas RV (2018) An overview of meningiomas. Future oncology (London, England) 14(21):2161–2177. https://doi.org/10.2217/fon-2018-0006
Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, Scheithauer BW, Kleihues P (2007) The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 114(2):97–109. https://doi.org/10.1007/s00401-007-0243-4
Fathi AR, Roelcke U (2013) Meningioma. Current neurology and neuroscience reports 13(4):337. https://doi.org/10.1007/s11910-013-0337-4
Apra C, Peyre M, Kalamarides M (2018) Current treatment options for meningioma. Expert Rev Neurother 18(3):241–249. https://doi.org/10.1080/14737175.2018.1429920
Chen L, Zou X, Wang Y, Mao Y, Zhou L (2013) Central nervous system tumors: a single center pathology review of 34,140 cases over 60 years. BMC Clin Pathol 13(1):14. https://doi.org/10.1186/1472-6890-13-14
Paek SH, Kim SH, Chang KH, Park CK, Kim JE, Kim DG, Park SH, Jung HW (2005) Microcystic meningiomas: radiological characteristics of 16 cases. Acta Neurochir 147(9):965–972; discussion 972. https://doi.org/10.1007/s00701-005-0578-3
Rishi A, Black KS, Woldenberg RW, Overby CM, Eisenberg MB, Li JY (2011) Microcystic meningioma presenting as a cystic lesion with an enhancing mural nodule in elderly women: report of three cases. Brain tumor pathology 28(4):335–339. https://doi.org/10.1007/s10014-011-0052-2
Tamiya T, Ono Y, Matsumoto K, Ohmoto T (2001) Peritumoral brain edema in intracranial meningiomas: effects of radiological and histological factors. Neurosurgery 49(5):1046–1051; discussion 1051-1042. https://doi.org/10.1097/00006123-200111000-00003
Padhani AR, Koh DM, Collins DJ (2011) Whole-body diffusion-weighted MR imaging in cancer: current status and research directions. Radiology 261(3):700–718. https://doi.org/10.1148/radiol.11110474
Sanverdi SE, Ozgen B, Oguz KK, Mut M, Dolgun A, Soylemezoglu F, Cila A (2012) Is diffusion-weighted imaging useful in grading and differentiating histopathological subtypes of meningiomas? Eur J Radiol 81(9):2389–2395. https://doi.org/10.1016/j.ejrad.2011.06.031
Hakyemez B, Yildirim N, Gokalp G, Erdogan C, Parlak M (2006) The contribution of diffusion-weighted MR imaging to distinguishing typical from atypical meningiomas. Neuroradiology 48(8):513–520. https://doi.org/10.1007/s00234-006-0094-z
Yamasaki F, Kurisu K, Satoh K, Arita K, Sugiyama K, Ohtaki M, Takaba J, Tominaga A, Hanaya R, Yoshioka H, Hama S, Ito Y, Kajiwara Y, Yahara K, Saito T, Thohar MA (2005) Apparent diffusion coefficient of human brain tumors at MR imaging. Radiology 235(3):985–991. https://doi.org/10.1148/radiol.2353031338
Shankar JJS, Hodgson L, Sinha N (2019) Diffusion weighted imaging may help differentiate intracranial hemangiopericytoma from meningioma. Journal of neuroradiology = Journal de neuroradiologie 46(4):263–267. https://doi.org/10.1016/j.neurad.2018.11.002
Whittle IR, Smith C, Navoo P, Collie D (2004) Meningiomas. Lancet (London, England) 363(9420):1535–1543. https://doi.org/10.1016/s0140-6736(04)16153-9
Kleinman GM, Liszczak T, Tarlov E, Richardson EP Jr (1980) Microcystic variant of meningioma: a light-microscopic and ultrastructural study. Am J Surg Pathol 4(4):383–389. https://doi.org/10.1097/00000478-198008000-00007
Kleihues P, Burger PC, Scheithauer BW (1993) The new WHO classification of brain tumours. Brain pathology (Zurich, Switzerland) 3(3):255–268. https://doi.org/10.1111/j.1750-3639.1993.tb00752.x
Wen PY, Huse JT (2017) 2016 World Health Organization classification of central nervous system tumors. Continuum (Minneapolis, Minn) 23 (6, Neuro-oncology):1531-1547. https://doi.org/10.1212/con.0000000000000536
Wen PY, Quant E, Drappatz J, Beroukhim R, Norden AD (2010) Medical therapies for meningiomas. J Neuro-Oncol 99(3):365–378. https://doi.org/10.1007/s11060-010-0349-8
Chen CJ, Tseng YC, Hsu HL, Jung SM (2008) Microcystic meningioma: importance of obvious hypointensity on T1-weighted magnetic resonance images. J Comput Assist Tomogr 32(1):130–134. https://doi.org/10.1097/RCT.0b013e318064f127
Hale AT, Wang L, Strother MK, Chambless LB (2018) Differentiating meningioma grade by imaging features on magnetic resonance imaging. Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia 48:71–75. https://doi.org/10.1016/j.jocn.2017.11.013
Lin BJ, Chou KN, Kao HW, Lin C, Tsai WC, Feng SW, Lee MS, Hueng DY (2014) Correlation between magnetic resonance imaging grading and pathological grading in meningioma. J Neurosurg 121(5):1201–1208. https://doi.org/10.3171/2014.7.jns132359
Hashiba T, Hashimoto N, Maruno M, Izumoto S, Suzuki T, Kagawa N, Yoshimine T (2006) Scoring radiologic characteristics to predict proliferative potential in meningiomas. Brain tumor pathology 23(1):49–54. https://doi.org/10.1007/s10014-006-0199-4
Carpeggiani P, Crisi G, Trevisan C (1993) MRI of intracranial meningiomas: correlations with histology and physical consistency. Neuroradiology 35(7):532–536. https://doi.org/10.1007/bf00588715
Kawahara Y, Nakada M, Hayashi Y, Kai Y, Hayashi Y, Uchiyama N, Nakamura H, Kuratsu J, Hamada J (2012) Prediction of high-grade meningioma by preoperative MRI assessment. J Neuro-Oncol 108(1):147–152. https://doi.org/10.1007/s11060-012-0809-4
Surov A, Ginat DT, Sanverdi E, Lim CCT, Hakyemez B, Yogi A, Cabada T, Wienke A (2016) Use of diffusion weighted imaging in differentiating between Maligant and benign Meningiomas. A Multicenter Analysis World neurosurgery 88:598–602. https://doi.org/10.1016/j.wneu.2015.10.049
Terada Y, Toda H, Okumura R, Ikeda N, Yuba Y, Katayama T, Iwasaki K (2018) Reticular appearance on gadolinium-enhanced T1- and diffusion-weighted MRI, and low apparent diffusion coefficient values in microcystic meningioma cysts. Clin Neuroradiol 28(1):109–115. https://doi.org/10.1007/s00062-016-0527-y
Bano S, Waraich MM, Khan MA, Buzdar SA, Manzur S (2013) Diagnostic value of apparent diffusion coefficient for the accurate assessment and differentiation of intracranial meningiomas. Acta radiologica short reports 2(7):2047981613512484. https://doi.org/10.1177/2047981613512484
Lin L, Bhawana R, Xue Y, Duan Q, Jiang R, Chen H, Chen X, Sun B, Lin H (2018) Comparative analysis of diffusional kurtosis imaging, diffusion tensor imaging, and diffusion-weighted imaging in grading and assessing cellular proliferation of Meningiomas. AJNR Am J Neuroradiol 39(6):1032–1038. https://doi.org/10.3174/ajnr.A5662
Nagar VA, Ye JR, Ng WH, Chan YH, Hui F, Lee CK, Lim CC (2008) Diffusion-weighted MR imaging: diagnosing atypical or malignant meningiomas and detecting tumor dedifferentiation. AJNR Am J Neuroradiol 29(6):1147–1152. https://doi.org/10.3174/ajnr.A0996
Manwaring J, Ahmadian A, Stapleton S, Gonzalez-Gomez I, Rodriguez L, Carey C, Tuite GF (2013) Pediatric microcystic meningioma: a clinical, histological, and radiographic case-based review. Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery 29(3):361–365. https://doi.org/10.1007/s00381-012-1991-6
Burdette JH, Elster AD, Ricci PE (1999) Acute cerebral infarction: quantification of spin-density and T2 shine-through phenomena on diffusion-weighted MR images. Radiology 212(2):333–339. https://doi.org/10.1148/radiology.212.2.r99au36333
Funding
This study was funded by the Health Industry Research Program Funding Project of Gansu Province (No.GSWSKY2018–52).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required.
Informed consent
For this type of retrospective study formal consent is not required.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Xiaoai, K., Qing, Z., Lei, H. et al. Differentiating microcystic meningioma from atypical meningioma using diffusion-weighted imaging. Neuroradiology 62, 601–607 (2020). https://doi.org/10.1007/s00234-020-02374-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00234-020-02374-3