Perfusion MR imaging for differentiation of benign and malignant meningiomas

Abstract

Introduction Our purpose was to determine whether perfusion MR imaging can be used to differentiate benign and malignant meningiomas on the basis of the differences in perfusion of tumor parenchyma and/or peritumoral edema. Methods A total of 33 patients with preoperative meningiomas (25 benign and 8 malignant) underwent conventional and dynamic susceptibility contrast perfusion MR imaging. Maximal relative cerebral blood volume (rCBV) and the corresponding relative mean time to enhance (rMTE) (relative to the contralateral normal white matter) in both tumor parenchyma and peritumoral edema were measured. The independent samples t-test was used to determine whether there was a statistically significant difference in the mean rCBV and rMTE ratios between benign and malignant meningiomas. Results The mean maximal rCBV values of benign and malignant meningiomas were 7.16±4.08 (mean±SD) and 5.89±3.86, respectively, in the parenchyma, and 1.05±0.96 and 3.82±1.39, respectively, in the peritumoral edema. The mean rMTE values were 1.16±0.24 and 1.30±0.32, respectively, in the parenchyma, and 0.91±0.25 and 1.24±0.35, respectively, in the peritumoral edema. The differences in rCBV and rMTE values between benign and malignant meningiomas were not statistically significant (P>0.05) in the parenchyma, but both were statistically significant (P<0.05) in the peritumoral edema. Conclusion Perfusion MR imaging can provide useful information on meningioma vascularity which is not available from conventional MRI. Measurement of maximal rCBV and corresponding rMTE values in the peritumoral edema is useful in the preoperative differentiation between benign and malignant meningiomas.

Assessment of Angiographic Vascularity of Meningiomas with Dynamic Susceptibility Contrast-Enhanced Perfusion-Weighted Imaging and Diffusion Tensor Imaging

“…In the present study, all meningiomas demonstrated increased CBV, a finding similar to what has been reported in the literature. 10 However, not all meningiomas with increased CBV demonstrated tumor stain visible on conventional angiography. Rather, angiographic vascularity was absent in (grade 0) 12.5% of meningiomas and only slightly increased (grade 1) in 18.8% of cases.…”

“…5 DSC-PWI, on the other hand, measures T2*-weighted signal intensity loss that occurs dynamically over bolus injection of contrast medium, from which relative CBV, a quantitative marker of tumor angiogenesis, can be computed. 6 Both DTI 7,8 and DSC-PWI [9][10][11] had been reported to be useful in subtyping meningiomas. The microvessel area of meningiomas determined by histopathology was found to correlate with relative CBV derived from DSC-PWI.…”

Ekstraaksiyel Beyin Tumorleri

“…Özellikle yüksek dereceli tümörlerde artmış vaskülarite mevcuttur. Yapılan çalışmalarda tipik ve atipik menenjiomlar karşılaştırıldığında serebral kan hacimleri (rCBV) arasında anlamlı farklılık saptanmamıştır [46][47][48]. Ancak malign menenjiomların peritümöral ödemindeki rCBV değerleri benign menenjiomlardakine göre daha yüksek bulunmuştur [48].…”

“…Yapılan çalışmalarda tipik ve atipik menenjiomlar karşılaştırıldığında serebral kan hacimleri (rCBV) arasında anlamlı farklılık saptanmamıştır [46][47][48]. Ancak malign menenjiomların peritümöral ödemindeki rCBV değerleri benign menenjiomlardakine göre daha yüksek bulunmuştur [48]. Bu bulgu da komşu beyin parankimine tümör invazyonuna ve anjiogeneze bağlanmaktadır [49].…”

Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques

“…In addition to 1 H-MRS, the other advanced MRI techniques, DWI [11] , DTI [12] and PWI have already found increasing use in the evaluation of cerebral tumors and still remain a subject of intense research [1,13,14] . DWI probes local tissue microstructure reflected by the freedom of microscopic motion of water molecules and provides a sensitive means to detect alterations in the integrity of white matter structures, while PWI facilitates the prediction of brain lesion progression in conjunction with histopathology [15] .…”