Differentiation between supratentorial pilocytic astrocytoma and extraventricular ependymoma using multiparametric MRI

2021 ◽  
pp. 028418512110541
Author(s):  
Xiaofang Zhou ◽  
Yan Su ◽  
Wanrong Huang ◽  
Xiaojun Lin ◽  
Zhen Xing ◽  
...  
Keyword(s):  
Cerebral Blood Volume ◽  
Volume Ratio ◽  
High Sensitivity ◽  
Cystic Mass ◽  
Multiparametric Mri ◽  
Dynamic Susceptibility ◽  
Dynamic Susceptibility Contrast ◽  
Conventional Mri ◽  
Mri Features ◽  
Susceptibility Contrast

Background The differentiation of supratentorial pilocytic astrocytomas (STPAs) and supratentorial extraventricular ependymomas (STEEs) is clinically pivotal because of distinct therapeutic management and prognosis, which is sometimes challenging to both neuroradiologists and pathologists. Purpose To explore and compare the conventional and advanced magnetic resonance imaging (MRI) features between STPA and STEE. Material and Methods A total of 23 patients with STPAs and 23 patients with STEEs were reviewed in this study. All patients performed conventional MRI, susceptibility-weighted imaging (SWI), and diffusion-weighted imaging (DWI), and 34 patients (17 with STPAs and 17 with STEEs) examined dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) in addition. Clinical data, conventional MRI features, minimum relative apparent diffusion coefficient ratio (rADCmin), and maximum relative cerebral blood volume ratio (rCBVmax) were compared between the two groups and subgroups. The optimal cutoff values of rADCmin and rCBVmax with sensitivity and specificity were calculated. Results STPA manifested similar to STEE as a solid-cystic mass but more frequently presented with a marked enhancing deep nodule ( P = 0.02), no peritumoral edema ( P = 0.036), higher rADCmin value (2.0 ± 0.5 vs. 0.9 ± 0.2; P < 0.001), and lower rCBVmax value (2.1 ± 0.4 vs. 14.4 ± 5.5; P < 0.001). The cutoff value of >1.39 for rADCmin and ≤ 2.81 for rCBVmax produced a high sensitivity of 95.65% and 100.0%, respectively, and all produced a specificity of 100.0% in differentiating STPAs from STEEs. Conclusion Multiparametric MRI techniques including conventional MRI, DWI, and DSC-PWI contribute to the differential diagnosis of STPA and STEE.

Predicting 1p/19q codeletion status using diffusion-, susceptibility-, perfusion-weighted, and conventional MRI in IDH-mutant lower-grade gliomas

2020 ◽  
pp. 028418512097362
Author(s):  
Xiefeng Yang ◽  
Yu Lin ◽  
Zhen Xing ◽  
Dejun She ◽  
Yan Su ◽  
...  
Keyword(s):  
Predictive Value ◽  
Operating Characteristic ◽  
Cerebral Blood Volume ◽  
Characteristic Curve ◽  
Lower Grade ◽  
Dynamic Susceptibility ◽  
Dynamic Susceptibility Contrast ◽  
Conventional Mri ◽  
Susceptibility Contrast ◽  
Sensitivity Specificity

Background Isocitrate dehydrogenase (IDH)-mutant lower-grade gliomas (LGGs) are further classified into two classes: with and without 1p/19q codeletion. IDH-mutant and 1p/19q codeleted LGGs have better prognosis compared with IDH-mutant and 1p/19q non-codeleted LGGs. Purpose To evaluate conventional magnetic resonance imaging (cMRI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) for predicting 1p/19q codeletion status of IDH-mutant LGGs. Material and Methods We retrospectively reviewed cMRI, DWI, SWI, and DSC-PWI in 142 cases of IDH mutant LGGs with known 1p/19q codeletion status. Features of cMRI, relative ADC (rADC), intratumoral susceptibility signals (ITSSs), and the value of relative cerebral blood volume (rCBV) were compared between IDH-mutant LGGs with and without 1p/19q codeletion. Receiver operating characteristic curve and logistic regression were used to determine diagnostic performances. Results IDH-mutant and 1p/19q non-codeleted LGGs tended to present with the T2/FLAIR mismatch sign and distinct borders ( P < 0.001 and P = 0.038, respectively). Parameters of rADC, ITSSs, and rCBVmax were significantly different between the 1p/19q codeleted and 1p/19q non-codeleted groups ( P < 0.001, P = 0.017, and P < 0.001, respectively). A combination of cMRI, SWI, DWI, and DSC-PWI for predicting 1p/19q codeletion status in IDH-mutant LGGs resulted in a sensitivity, specificity, positive predictive value, negative predictive value, and an AUC of 80.36%, 78.57%, 83.30%, 75.00%, and 0.88, respectively. Conclusion 1p/19q codeletion status of IDH-mutant LGGs can be stratified using cMRI and advanced MRI techniques, including DWI, SWI, and DSC-PWI. A combination of cMRI, rADC, ITSSs, and rCBVmax may improve the diagnostic performance for predicting 1p/19q codeletion status.

Attempts to improve absolute quantification of cerebral blood flow in dynamic susceptibility contrast magnetic resonance imaging: a simplified T1-weighted steady-state cerebral blood volume approach

2007 ◽  
Vol 48 (5) ◽  
pp. 550-556 ◽  
Author(s):  
R. Wirestam ◽  
L. Knutsson ◽  
J. Risberg ◽  
S. Börjesson ◽  
E.-M. Larsson ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Steady State ◽  
Water Exchange ◽  
Cerebral Blood Volume ◽  
Dynamic Susceptibility ◽  
Resonance Imaging ◽  
Dynamic Susceptibility Contrast ◽  
Dsc Mri ◽  
Contrast Magnetic Resonance ◽  
Susceptibility Contrast

Background: Attempts to retrieve absolute values of cerebral blood flow (CBF) by dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) have typically resulted in overestimations. Purpose: To improve DSC-MRI CBF estimates by calibrating the DSC-MRI-based cerebral blood volume (CBV) with a corresponding T1-weighted (T1W) steady-state (ss) CBV estimate. Material and Methods: 17 volunteers were investigated by DSC-MRI and 133Xe SPECT. Steady-state CBV calculation, assuming no water exchange, was accomplished using signal values from blood and tissue, before and after contrast agent, obtained by T1W spin-echo imaging. Using steady-state and DSC-MRI CBV estimates, a calibration factor K = CBV(ss)/CBV(DSC) was obtained for each individual. Average whole-brain CBF(DSC) was calculated, and the corrected MRI-based CBF estimate was given by CBF(ss) = K×CBF(DSC). Results: Average whole-brain SPECT CBF was 40.1±6.9 ml/min·100 g, while the corresponding uncorrected DSC-MRI-based value was 69.2±13.8 ml/min·100 g. After correction with the calibration factor, a CBF(ss) of 42.7±14.0 ml/min·100 g was obtained. The linear fit to CBF(ss)-versus-CBF(SPECT) data was close to proportionality ( R = 0.52). Conclusion: Calibration by steady-state CBV reduced the population average CBF to a reasonable level, and a modest linear correlation with the reference 133Xe SPECT technique was observed. Possible explanations for the limited accuracy are, for example, large-vessel partial-volume effects, low post-contrast signal enhancement in T1W images, and water-exchange effects.

scholarly journals Integrative Analysis of mRNA, microRNA, and Protein Correlates of Relative Cerebral Blood Volume Values in GBM Reveals the Role for Modulators of Angiogenesis and Tumor Proliferation

2016 ◽  
Vol 15 ◽  
pp. CIN.S33014 ◽  
Author(s):  
Arvind Rao ◽  
Ganiraju Manyam ◽  
Ganesh Rao ◽  
Rajan Jain
Keyword(s):  
Blood Volume ◽  
Messenger Rna ◽  
Cerebral Blood Volume ◽  
The Cancer Genome Atlas ◽  
Dynamic Susceptibility ◽  
Tumor Proliferation ◽  
Dynamic Susceptibility Contrast ◽  
Relative Cerebral Blood Volume ◽  
Hemodynamic Assessment ◽  
Susceptibility Contrast

Dynamic susceptibility contrast-enhanced magnetic resonance imaging is routinely used to provide hemodynamic assessment of brain tumors as a diagnostic as well as a prognostic tool. Recently, it was shown that the relative cerebral blood volume (rCBV), obtained from the contrast-enhancing as well as -nonenhancing portion of glioblastoma (GBM), is strongly associated with overall survival. In this study, we aim to characterize the genomic correlates (microRNA, messenger RNA, and protein) of this vascular parameter. This study aims to provide a comprehensive radiogenomic and radioproteomic characterization of the hemodynamic phenotype of GBM using publicly available imaging and genomic data from the Cancer Genome Atlas GBM cohort. Based on this analysis, we identified pathways associated with angiogenesis and tumor proliferation underlying this hemodynamic parameter in GBM.

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