Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI

Hu, Yue; Chen, Yue; Wang, Jie; Kang, Jin Juan; Shen, Dan Dan; Zhong, Jia

doi:10.3389/fonc.2020.593102

Cited by 13 publications

(10 citation statements)

References 32 publications

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“…Therefore, the observed relationship between Ktrans (Quantile 90) and Ktrans (Quantile 50) and VEGF expression is reasonable. The findings reported in this study are consistent with those of previous reports in that VEGF and Ktrans have significantly positive associations in gliomas [ 24 , 25 ]. Furthermore, this study indicated that VEGF expression in diffuse-type AGC was significantly higher than that in intestinal-type AGC.…”

Section: Discussionsupporting

confidence: 93%

Association Between DCE-MRI Perfusion Histogram Parameters and EGFR and VEGF Expressions in Different Lauren Classifications of Advanced Gastric Cancer

Zhao

Wang

et al. 2022

Pathol. Oncol. Res.

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Objective: To investigate the correlations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion histogram parameters and vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR) expressions in advanced gastric cancer (AGC).Methods: This retrospective study included 80 pathologically confirmed patients with AGC who underwent DCE-MRI before surgery from February 2017 to May 2021. The DCE-MRI perfusion histogram parameters were calculated by Omni Kinetics software in four quantitative parameter maps. Immunohistochemical methods were used to detect VEGF and EGFR expressions and calculate the immunohistochemical score.Results: VEGF expression was relatively lower in patients with intestinal-type AGC than those with diffuse-type AGC (p < 0.05). For VEGF, Receiver operating characteristics (ROC) curve analysis revealed that Quantile 90 of Ktrans, Meanvalue of Kep and Quantile 50 of Ve provided the perfect combination of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for distinguishing high and low VEGF expression, For EGFR, Skewness of Ktrans, Energy of Kep and Entropy of Vp provided the perfect combination of sensitivity, specificity, PPV and NPV for distinguishing high and low EGFR expression. Ktrans (Quantile 90, Entropy) showed the strongest correlation with VEGF and EGFR in patients with intestinal-type AGC (r = 0.854 and r = 0.627, respectively); Ktrans (Mean value, Entropy) had the strongest correlation with VEGF and EGFR in patients with diffuse-type AGC (r = 0.635 and 0.656, respectively).Conclusion: DCE-MRI perfusion histogram parameters can serve as imaging biomarkers to reflect VEGF and EGFR expressions and estimate their difference in different Lauren classifications of AGC.

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Section: Discussionsupporting

confidence: 93%

Association Between DCE-MRI Perfusion Histogram Parameters and EGFR and VEGF Expressions in Different Lauren Classifications of Advanced Gastric Cancer

Zhao

Wang

et al. 2022

Pathol. Oncol. Res.

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“…Moreover, studies revealed that DCE‐driven parameters were able to predict some of the molecular characteristics used recently for the classification of glioma tumors, including IDH and MGMT methylation. Hu et al reported statistically significant differences in histogram parameters of K trans and V e between IDH‐mutated and IDH‐wild‐type glioma 53 . Furthermore, Zhang et al found that glioblastoma with MGMT methylation showed significantly higher K trans , indicating that MGMT methylation may be involved in glioma‐associated angiogenesis characterized by high endothelial permeability vasculatures 48 .…”

Section: Resultsmentioning

confidence: 99%

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1

Hirschler

Sollmann

Schmitz-Abecassis

et al. 2023

Magnetic Resonance Imaging

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Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast‐enhanced MRI, arterial spin labeling, diffusion‐weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility‐weighted imaging, MRI‐PET, MR elastography, and MR‐based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2

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“…Transforming growth factor-β and hypoxic signals are increased in IDH wild-type low-grade gliomas, and neovascularization in IDH-mutated and wild-type tumors has different molecular features [ 14 ]. Expression of VEGF, which is involved in neovascularization, is significantly lower in IDH-mutated gliomas [ 15 ]. These reports suggest that IDH wild-type gliomas have more aggressive neovascularization, which can lead to poorer outcomes.…”

Section: Discussionmentioning

confidence: 99%

Factors Involved in Preoperative Edema in High-Grade Gliomas

Saito¹,

Mizumoto²,

Liang³

et al. 2022

Cureus

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BackgroundExpansion of preoperative edema (PE) is an independent poor prognostic factor in high-grade gliomas.Evaluation of PE provides important information that can be readily obtained from magnetic resonance imaging (MRI), but there are few reports on factors associated with PE. The goal of this study was to identify factors contributing to PE in Grade 3 (G3) and Grade 4 (G4) gliomas. MethodologyPE was measured in 141 pathologically proven G3 and G4 gliomas, and factors with a potential relationship with PE were examined in univariate and multivariate analyses. The following eight explanatory variables were used: age, sex, Karnofsky performance status (KPS), location of the glioma, tumor diameter, pathological grade, isocitrate dehydrogenase (IDH)-1-R132H status, and Ki-67 index. Overall survival (OS) and progression-free survival (PFS) were calculated in groups divided by PE (<1 vs. ≥1 cm) and by factors with a significant correlation with PE in multivariate analysis. ResultsIn univariate analysis, age (p = 0.013), KPS (p = 0.012), pathology grade (p = 0.004), and IDH1-R132H status (p = 0.0003) were significantly correlated with PE. In multivariate analysis, only IDH1-R132H status showed a significant correlation (p = 0.036), with a regression coefficient of -0.42. The median follow-up period in survivors was 38.9 months (range: 1.2-131.7 months). The one-, two-, and three-year OS rates for PE <1 vs. ≥1 cm were 77% vs. 68%, 67% vs. 44%, and 63% vs. 24% (p = 0.0001), respectively, and those for IDH1-R132H mutated vs. wild-type cases were 85% vs. 67%, 85% vs. 40%, and 81% vs. 21% (p < 0.0001), respectively. The one-, two-, and three-year PFS rates for PE <1 vs. ≥1 cm were 77% vs. 49%, 64% vs. 24%, and 50% vs. 18% (p = 0.0002), respectively, and those for IDH1-R132H mutated vs. wild-type cases were 85% vs. 48%, 77% vs. 23%, and 73% vs. 14% (p < 0.0001), respectively. ConclusionsIDH1-R132H status was found to be a significant contributor to PE. Cases with PE <1 cm and those with the IDH1-R132H mutation clearly had a better prognosis.

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Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI

Cited by 13 publications

References 32 publications

Association Between DCE-MRI Perfusion Histogram Parameters and EGFR and VEGF Expressions in Different Lauren Classifications of Advanced Gastric Cancer

Association Between DCE-MRI Perfusion Histogram Parameters and EGFR and VEGF Expressions in Different Lauren Classifications of Advanced Gastric Cancer

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1

Factors Involved in Preoperative Edema in High-Grade Gliomas

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