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• Clinical Article •
Differential diagnosis of atypical meningiomas and anaplastic meningiomas by MRI basic signs and DWI parameters
HAN Tao  ZHANG Jing  LIU Xianwang  ZHANG Bin  DENG Liangna  LIN Xiaoqiang  JING Mengyuan  ZHOU Junlin 

Cite this article as: Han T, Zhang J, Liu XW, et al. Differential diagnosis of atypical meningiomas and anaplastic meningiomas by MRI basic signs and DWI parameters[J]. Chin J Magn Reson Imaging, 2021, 12(4): 12-16. DOI:10.12015/issn.1674-8034.2021.04.003.


[Abstract] Objective To improve the accuracy of preoperative diagnosis of atypical meningioma (AM) and anaplastic meningioma (AAM), by MRI basic signs combined with diffusion-weighted imaging (DWI) parameters. Materials andMethods The preoperative clinical, imaging and postoperative pathological data of 44 patients with AM and 16 patients with AAM confirmed by pathology were analyzed retrospectively. The MRI signs and apparent diffusion coefficient (ADC) were compared. The diagnostic efficacy of each parameter in differentiating the two groups of tumors was evaluated by the receiver working characteristic (ROC) curve.Results Between AM group and AAM group, lobulation sign (32%/62.5%, χ2=4.602), cystic degeneration (54.5%/93.75%, χ2=6.297), fuzzy tumor-brain interface (9%/62.5%, χ2=15.843), moderate-severe peritumoral edema (50%/57.5%, χ2=5.401), and uniform tumor enhancement (47.7%/0%) were statistically significant (P＜0.05). The ADCmean (ADCmin and rADC) of AAM and AM were (0.742±0.083)×10-3 mm2/s and (0.890±0.076)×10-3 mm2/s [(0.700±0.099)×10-3 mm2/s and (0.842±0.079)×10-3 mm2/s, (1.07±0.10) and (1.17±0.10)], P＜0.001, respectively. When the ADCmean threshold is 0.822×10-3 mm2/s, the sensitivity and specificity of distinguishing them are 84.1% and 87.5%; when the ADCmin threshold is 0.800×10-3 mm2/s, the sensitivity and specificity of distinguishing them are 75% and 87.5%, when the rADC threshold is 1.005, the sensitivity and specificity of distinguishing them are 95.5% and 43.7% respectively.Conclusions The five MRI signs of blurred brain interface, peritumoral edema, lobulation sign, cystic degeneration and homogeneity of enhancement are helpful to differentiate AM from AAM. Combined with DWI quantitative parameters (ADCmean, ADCmin and rADC) can effectively improve the preoperative diagnosis of AAM and AM, which has a certain clinical application value.
[Keywords] meningioma；typing；magnetic resonance imaging；diffusion-weighted imaging；apparent diffusion coefficient

HAN Tao   ZHANG Jing   LIU Xianwang   ZHANG Bin   DENG Liangna   LIN Xiaoqiang   JING Mengyuan   ZHOU Junlin*  

Department of Radiology, Lanzhou University Second Hospital; Second Clinical School, Lanzhou University; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China

Zhou JL, E-mail: lzuzjl601@163.com

Conflicts of interest   None.

This work was part of Lanzhou University Second Hospital "Cuiying Technology Innovation Plan" Applied Basic Research Project (No. CY2017-MS03).
Received  2020-08-24
Accepted  2021-01-12
DOI: 10.12015/issn.1674-8034.2021.04.003
Cite this article as: Han T, Zhang J, Liu XW, et al. Differential diagnosis of atypical meningiomas and anaplastic meningiomas by MRI basic signs and DWI parameters[J]. Chin J Magn Reson Imaging, 2021, 12(4): 12-16. DOI:10.12015/issn.1674-8034.2021.04.003.

1
Buerki RA, Horbinski CM, Kruser T, et al. An overview of meningiomas[J]. Future Oncol, 2018, 14(21): 2161-2177. DOI: 10.2217/fon-2018-0006.
2
Bai J, Cheng JL, Gao AK, et al. Classification and interpretation of WHO central nervous system tumors in 2016[J]. Chin J Radiol, 2016, 50(12): 1000-1005. DOI: 10.3760/cma.j.issn.1005-1201.2016.12.025.
3
Louis DN, Perry A, Reifenberger G, et al. The 2016 World Health Organization classification of tumors of the central nervous system: a summary[J]. Acta Neuropathol, 2016, 131(6): 803-820. DOI: 10.1007/s00401-016-1545-1.
4
Chen R, Aghi MK. Atypical meningiomas[J]. Handb Clin Neurol, 2020, 170: 233-244. DOI: 10.1016/B978-0-12-822198-3.00043-4.
5
Fountain DM, Young Adam MH, Santarius T. Malignant meningiomas[J]. Handb Clin Neurol, 2020, 170: 245-250. DOI: 10.1016/B978-0-12-822198-3.00044-6.
6
Xiao GQ, Wang ST, Xu FL. Value of DWI combined with MRS in glioma grade diagnosis[J]. Chin J Magn Reson Imaging, 2020, 11(7): 573-576. DOI: 10.12015/issn.1674-8034.2020.07.019.
7
Yue SH, Wei JY, Zhou JL, et al. Imaging of microcystic meningioma and anaplastic meningioma: A comparative study[J]. Chin J Med Imaging, 2014, 22(12): 891-894. DOI: 103969/j.issn.1005-5185.2014.12.003.
8
Li WY, Zhou JL, Dong C, et al. Comparative analysis of MRI features of anaplastic meningioma and atypical meningioma[J]. Chin Interventional Imaging Therapeutics, 2014, 11(7): 427-430. DOI: 10.13929/j.1672-8475.2014.07.006
9
Liu H, Zhou J, Li W, et al. Comparative analysis of the magnetic resonance imaging features between anaplastic meningioma and atypical meningioma[J]. J Craniofac Surg, 2016, 27(3): e229-e233. DOI: 10.1097/SCS.0000000000002361.
10
Ma YG, Chen LJ, Chen SX, et al. MR findings and pathological comparison of atypical and anaplastic meningiomas[J]. J Med Imaging, 2018, 28(4): 538-541.
11
Meyer HJ, Wienke A, Surov A. ADC values of benign and high grade meningiomas and associations with tumor cellularity and proliferation-A systematic review and meta-analysis[J]. J Neurol Sci, 2020, 415: 116975. DOI: 10.1016/j.jns.2020.116975.
12
Yu J, Liu XJ, Lin F, et al. Comparison of MRI imaging features of the latest WHO pathological classification of meningioma[J]. Shenzhen J Integra Tradit Chin West Med, 2019, 29(10): 60-64, 199. DOI: 10.16458/j.cnki.1007-0893.2019.10.026.
13
JIZI LL, Hu RJ, Yang GP, et al. Analysis of correlation between MRI features and pathological grade of meningioma[J]. Chin J Clin Neurosurgery, 2018, 23(8): 526-528. DOI: 10.13798/j.issn.1009-153X.2018.08.005.
14
Sun Q, Ke XA, Zhou Q, et al. Magnetic resonance imaging and diffusion weighted imaging in the differential diagnosis of microcystic meningioma and atypical meningioma[J]. Chin J Med Imaging, 2020, 28(7): 493-498. DOI: 10.3969/j.issn.1005-5185.2020.07.003.
15
Hwang KL, Hwang WL, Bussière MR, et al. The role of radiotherapy in the management of high-grade meningiomas[J]. Chin Clin Oncol, 2017, 6(Suppl 1): S5. DOI: 10.21037/cco.2017.06.09.
16
Jiang HT, Wang YS, Zhang J, et al. Pathological and imaging observation of WHO meningioma classification[J]. Inter J Neurology Neurosurgery, 2012, 39(6): 511-514.
17
Chen T, Jiang B, Zheng Y, et al. Differentiating intracranial solitary fibrous tumor/hemangiopericytoma from meningioma using diffusion-weighted imaging and susceptibility-weighted imaging[J]. Neuroradiology, 2020, 62(2): 175-184. DOI: 10.1007/s00234-019-02307-9.
18
Azeemuddin M, Nizamani WM, Tariq MU, et al. Role of ADC values and ratios of MRI scan in differentiating typical from atypical/anaplastic meningiomas[J]. J Pak Med Assoc, 2018, 68(9): 1403-1406.
19
Ke XA, Zhou Q, Han L, et al. Differentiating microcystic meningioma from atypical meningioma using diffusion-weighted imaging[J]. Neuroradiology, 2020, 62(5): 601-607. DOI: 10.1007/s00234-020-02374-3.
20
Lu ZW, You ZQ, Xie DH, et al. Apparent diffusion coefficient values in differential diagnosis and prognostic prediction of solitary of fibrous tumor/hemangiopericytoma (WHOII) and atypical meningioma[J]. Technol Health Care, 2019, 27(2): 137-147. DOI: 10.3233/THC-181447.
21
Shankar JJS, Hodgson L, Sinha N. Diffusion weighted imaging may help differentiate intracranial hemangiopericytoma from meningioma[J]. J Neuroradiology, 2019, 46(4): 263-267. DOI: 10.1016/j.neurad.2018.11.002.
22
Shen JH, Dong G, Fang LJ, et al. Correlation analysis of ADC value, radc value and Ki-67 proliferation index in meningioma[J]. J Clin Radiol, 2017, 36(1): 11-14.
23
Duran R, Ronot M, Kerbaol A, et al. Hepatic hemangiomas: factors associated with T2 shine-through effect on diffusion-weighted MR sequences[J]. Eur J Radiol, 2014, 83(3): 468-478. DOI: 10.1016/j.ejrad.2013.11.023.

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