Characteristics of typical and atypical meningiomas on ADC maps with respect to schwannomas

Pavliša, Goran; Radoš, Marko; Pažanin, Leo; Padovan, Ranka Štern; Ozretić, David; Pavliša, Gordana

doi:10.1016/j.clinimag.2007.07.007

Cited by 58 publications

(42 citation statements)

References 31 publications

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“…Pavlisa et al . found similar values, with a mean value of 1.33 (± 0.21) × 10 −3 mm 2 /s, in 15 schwannomas 17 . In our case, the mean ADC value was 1.25 × 10 −3 mm 2 /s, and in another case of CPA subependymoma, reported by Koral et al ., it was 1.34 × 10 −3 mm 2 /s 7 .…”

Section: Discussionsupporting

confidence: 89%

Cerebellopontine angle subependymoma without fourth ventricle extension: An uncommon tumor in a rare location

et al. 2011

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Subependymomas are benign tumors that occur predominantly in the ventricular system. We describe a case of a 57-year-old man with a large cerebellopontine angle (CPA) tumor which expanded into the jugular foramen. Complete surgical excision of the tumor was achieved through a retrosigmoid approach and the histopathological diagnosis was subependymoma. Subependymomas located exclusively in the CPA without extension into the fourth ventricle are extremely rare. The mainly pathological features and the difficulty in correctly diagnosing these cases preoperatively, even with MRI, are discussed.

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Section: Discussionsupporting

confidence: 89%

Cerebellopontine angle subependymoma without fourth ventricle extension: An uncommon tumor in a rare location

et al. 2011

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“…Several studies reported that MD or MD ratio may be useful for determining meningioma grade and progression (8)(9)(10)(11). Other studies, however, reported the trend of lower MD in atypical meningiomas, with no signifi cant difference (12)(13)(14). We observed signifi cantly lower MD values in atypical meningiomas in comparison to typical meningiomas.…”

Section: Neuroradiology: Determination Of Grade and Subtype Of Meningcontrasting

confidence: 50%

“…Of all the DT imaging parameters, mean diffusivity (MD) has been most commonly used for the characterization of meningiomas (8)(9)(10)(11)(12)(13)(14). However, although some studies reported that MD or MD ratio can help differentiate atypical from typical meningiomas (8)(9)(10)(11), others suggested that MD was not indicative of malignancy grade or tumor subtype (12)(13)(14). DT imaging also provides anisotropic information about the tissue.…”

Section: Patientsmentioning

confidence: 99%

Determination of Grade and Subtype of Meningiomas by Using Histogram Analysis of Diffusion-Tensor Imaging Metrics

Wang¹,

Kim²,

Zhang³

et al. 2012

Radiology

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Purpose:To determine whether histogram analysis of diffusiontensor (DT) magnetic resonance (MR) imaging metrics, including tensor shape measurements, can help determine the grades and subtypes of meningiomas. Materials and Methods:The institutional review board approved this HIPAAcompliant study. Nine atypical, three anaplastic, and 39 typical meningiomas were retrospectively studied. The 39 typical meningiomas included one secretory meningioma and 11 fi broblastic, 11 transitional, 14 meningothelial, and two angiomatous meningiomas. DT imaging metrics, including fractional anisotropy, mean diffusivity, linear anisotropy coeffi cient, planar anisotropy coeffi cient (CP), spherical anisotropy coeffi cient (CS), and eigenvalue skewness (SK), as well as normalized signal intensity from contrastenhanced T1-and T2-weighted images, were measured from the enhancing region of the tumor. Mean, variance, skewness, and kurtosis were extracted from the histograms. A two-level decision tree was designed, and a multivariate logistic regression analysis was used at each level to determine the best model for classifi cation. Results:Histogram skewness of SK and kurtosis of SK were significantly higher in atypical and anaplastic meningiomas than in typical meningiomas ( P , .01). Among typical meningiomas, signifi cant differences in histogram measures of CP and CS between fi broblastic meningiomas and other subtypes were observed ( P , .01). The best model for differentiating atypical and anaplastic meningiomas from typical meningiomas consisted of mean and skewness of SK and kurtosis of T1 signal intensity , with an area under the receiver operating characteristic curve (AUC) of 0.946. The best model for differentiating fi broblastic meningiomas from other subtypes consisted of skewness of T2 signal intensity and kurtosis of CP (AUC, 0.970). Conclusion:Histogram analysis of DT imaging metrics can help determine the grades and subtypes of meningiomas, which can better assist in surgical planning.q RSNA, 2011Supplemental material: http://radiology.rsna.org/lookup /suppl

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“…In our study, Atypical and malignant meningiomas (n = 5), classified as WHO Grade-II and Grade-III, respectively, all had markedly increased signal on DWIs, and extremely low ADC values, indicative of marked restriction to water diffusion, which is in consistence with Pavlisa et al, 25 who stated that high-grade tumours with increased cellularity have lower ADC values than low-grade tumours or normal brain.…”

Section: Resultssupporting

confidence: 68%

Differentiation of typical from atypical and malignant meningiomas using diffusion weighted magnetic resonance imaging

Naseruddin

Devi

Prasad

et al. 2017

jcsr

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Background: Atypical and malignant meningiomas are associated with less favourable clinical outcome as they are more prone to recurrence and aggressive growth. Conventional magnetic resonance imaging (MRI) can reliably differentiate meningiomas from other extra-axial neoplasms, but grading of meningiomas as typical or atypical/malignant is not possible. Diffusion weighted MRI (DWMRI) has been used reliably for grading of gliomas. There are only few studies to investigate utility of DWMRI in grading of meningiomas. So we have planned in this study to investigate the utility of DWMRI parameters such as apparent diffusion coefficients (ADC) and normalized ADC (NADC) ratios in the preoperative characterization of meningiomas.Methods: Thirty patients with pathologically proven meningiomas [typical (n=25) atypical/malignant (n=5)] underwent MRI at 1.5 T. The signal intensity of lesions on DWI was evaluated. ADC values of lesion and NADC ratios from lesion and contralateral normal white matter were calculated. Results: The mean apparent diffusion constant (ADC) values (×10-3 mm 2 / s) were 0.92±0.2 and 0.66±0.08 in typical and atypical/malignant meningiomas respectively. The mean NADC ratios were 1.24±0.28 and 0.86±0.08 for typical and atypical/malignant meningiomas respectively. Conclusions:Atypical and malignant meningiomas have significantly lower ADC and NADC ratios compared to typical meningiomas. Key words: Meningioma, Differentiation, Diffusion magnetic resonance imaging, Apparent diffusion coefficients, Normalized apparent diffusion coefficientsKhaja Naseruddin VS, Vijaya lakshmi Devi B, Prasad BCM, Rukmangada N, Lakshmi AY. Differentiation of typical from atypical and malignant meningiomas using diffusion weighted magnetic resonance imaging. J Clin Sci Res 2017;6:80-8.

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Characteristics of typical and atypical meningiomas on ADC maps with respect to schwannomas

Cited by 58 publications

References 31 publications

Cerebellopontine angle subependymoma without fourth ventricle extension: An uncommon tumor in a rare location

Cerebellopontine angle subependymoma without fourth ventricle extension: An uncommon tumor in a rare location

Determination of Grade and Subtype of Meningiomas by Using Histogram Analysis of Diffusion-Tensor Imaging Metrics

Differentiation of typical from atypical and malignant meningiomas using diffusion weighted magnetic resonance imaging

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