Main Article Content
Meningiomas are the most common primary extra-axial non-glial intracranial tumors. The severe grade of meningioma, according to WHO, has the highest recurrence rate accompanied by high morbidity and mortality rates. Therefore, it is imperative to perform pre-operative assessments so the clinician can give prompt treatment to gain a better prognosis. It is a novel alternative way of predicting meningioma’s malignancy by calculating the tumor’s apparent diffusion coefficient (ADC) value. The objective of the study was to determine the value of ADC for differentiating benign and malignant meningiomas.
This cross-sectional study involved 32 subjects with clinically diagnosed or histologically verified meningioma (21 benign and 11 malignant). They underwent a head-magnetic resonance imaging (MRI) examination and biopsy. We calculated the ADC value by creating regions of interest (ROIs) on the solid part of the tumor, guided by contrast and fluid-attenuated inversion recovery (FLAIR) sequence. We analyzed the ADC value with independent t-test and Bland-Altman graphs, calculated the average difference, CI 95%, limit of agreement between observers, and ROC.
Mean ADC of malignant meningiomas (0.877 ± 0.167 x 10-3 mm2/s) was significantly lower than that of benign meningiomas (0.990 ± 0.105 x 10-3 mm2/s) (p<0.05). The ADC threshold is 0.886 x 10-3 mm2/s with sensitivity 63.6%, specificity 85.7%, positive predictive value 70% and negative predictive value 81.8%.
The ADC value measurement provides a discriminative feature to differentiate between benign and malignant meningiomas. However, the clinical applicability still needs to be elucidated, as histopathological confirmation remains the mainstay of definitive diagnosis.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.The journal allow the authors to hold the copyright without restrictions and allow the authors to retain publishing rights without restrictions.
Sohu DM, Sohail S, Shaikh R. Diagnostic accuracy of diffusion weighted MRI in differentiating benign and malignant meningiomas. Pak J Med Sci 2019;35:726-30. DOI: 10.12669/pjms.35.3.1011.
Lu Y, Liu L, Luan S, Xiong J, Geng D, Yin B. The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest. Eur Radiol 2019;29:1318–28. DOI: 10.1007/s00330-018-5632-7.
Surov A, Ginat DT, Sanverdi E, et al. Use of diffusion weighted imaging in differentiating between malignant and benign meningiomas: a multicenter analysis. World Neurosurg 2016;88:598–602. DOI: 10.1016/j.wneu.2015.10.049.
Saligheh Rad H, Safari M, Kazerooni AF, Moharamzad Y, Taheri MS. Apparent diffusion coefficient (ADC) and first-order histogram statistics in differentiating malignant versus benign meningioma in adults. Iran J Radiol 2019;16:e74324. DOI: 10.5812/iranjradiol.7432416.
Baskan O, Silav G, Bolukbasi FH, Canoz O, Geyik S, Elmaci I. Relation of apparent diffusion coefficient with Ki-67 proliferation index in meningiomas. Br J Radiol 2016;89:4–9. DOI: 10.1259/bjr.20140842.
Madhok R, Sachdeva P. Measurement of mean ADC values in tubercular vertebrae and associated collection. J Clin Diagn Res 2016;10:TC19-TC23. DOI: 10.7860/JCDR/2016/20520.8344.
Moraru L, Dimitrievici L. Apparent diffusion coefficient of the normal human brain for various experimental conditions AIP Conference Proceedings 1796, 2017;040005-1-040005-6. DOI: 10.1063/1.4972383.
Surov A, Gottschling S, Mawrin C, et al. Diffusion-weighted imaging in meningioma: Prediction of tumor grade and association with histopathological parameters. Transl Oncol 2015;517–23. DOI: 10.1016/j.tranon.2015.11.012.
Azeemuddin M, Nizamani WM, Tariq MU, Wasay M. Role of ADC values and ratios of MRI scan in differentiating typical from atypical/anaplastic meningiomas. J Pak Med Assoc 2018;68:1403–6.
Yiping L, Kawai S, Jianbo W, Li L, Daoying G, Bo Y. Evaluation parameters between intra-voxel incoherent motion and diffusion-weighted imaging in grading and differentiating histological subtypes of meningioma: a prospective pilot study. J Neurol Sci 2017; 372:60–9. DOI: 10.1016/j.jns.2016.11.037.
Memon MA, Ting H, Cheah JH, Thurasamy R, Chuah F, Cham TH. Sample size for survey research: review and recommendations, Appl Struct Equation Modeling 2020; 2920; 4: i-xx11.
Vaubel RA, Chen SG, Raleigh DR, et al. Meningiomas with rhabdoid features lacking other histologic features of malignancy: a study of 44 cases and review of the literature. J Neuropathol Exp Neurol 2016;75:44–52. DOI: 10.1093/jnen/nlv006.
Giavarina D. Understanding Bland Altman analysis. Biochem Med (Zagreb) 2015;25:141–51. DOI: 10.11613/BM.2015.015.
Server A, Kulle B, Maehlen J, et al. Quantitative apparent diffusion coefficients in the characterization of brain tumors and associated peritumoral edema. Acta Radiol 2009;50:682-9. DOI: 10.1080/02841850902933123.
Yin B, Liu L, Zhang BY, Li YX, Li Y, Geng DY. Correlating apparent diffusion coefficients with histopathologic findings on meningiomas. Eur J Radiol 2012;81:4050-6. DOI: 10.1016/j.ejrad.2012.06.002.
Chen L, Liu M, Bao J, et al. The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis. PLoS One 2013;8.e79008. DOI: 10.1371/journal.pone.0079008.
Abdel-Kerim A, Shehata M, El Sabaa B, Fadel S, Heikal A, Mazloum Y. Differentiation between benign and atypical cranial meningiomas. Can ADC measurement help? MRI findings with hystopathological correlation. Egyptian J Radiol Nuclear Med 2018;49:172-5. DOI: 10.1016/j.ejrnm.2017.10.004
Neethu PM, Saanida MP, Subramaniam G, et al. Use of MRI apparent diffusion coefficient to noninvasively differentiate between the histologic grades of meningioma. J. Evolution Med Dent Sci 2020;9:1679-83. DOI:10.14260/jemds/2020/369.
Hirunpat S, Sanghan N, Watcharakul C, Kayasut K, Ina N, Pornrujee H. Is apparent diffusion coefficient value measured on picture archiving and communication system workstation helpful in prediction of high-grade meningioma? Hong Kong J Radiol 2016;19:84-90. DOI: 10.12809/hkjr1615346.
Just N. Improving tumour heterogeneity MRI assessment with histograms. Br J Cancer 2014;111:2205-13. DOI: 10.1038/bjc.2014.512.