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Published on: January 9, 2019
Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic
1Department of Medical Imaging, Affiliated Hospital of Nantong University, Nantong, China.
Objectives:
To investigate whether glioma isocitrate dehydrogenase (IDH) 1 mutation and vascular endothelial growth factor (VEGF) expression can be estimated by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).
Methods:
Chinese Glioma Genome Atlas (CGGA) database was wined for differential expression of VEGF in gliomas with different IDH genotypes. The VEGF expression and IDH1 genotypes of 56 glioma samples in our hospital were assessed by immunohistochemistry. Preoperative DCE-MRI data of glioma samples were reviewed. Regions of interest (ROIs) covering tumor parenchyma were delineated. Histogram parameters of volume transfer constant (K ) and volume of extravascular extracellular space per unit volume of tissue (V ) derived from DCE-MRI were obtained. Histogram parameters of K , V and VEGF expression of IDH1 mutant type (IDH1 ) gliomas were compared with the IDH1 wildtype (IDH1 ) gliomas. Receiver operating characteristic (ROC) curve analysis was performed to differentiate IDH1 from IDH1 gliomas. The correlation coefficients were determined between histogram parameters of K , V and VEGF expression in gliomas.
Results:
In CGGA database, VEGF expression in IDH gliomas was lower as compared to wildtype counterpart. The immunohistochemistry of glioma samples in our hospital also confirmed the results. Comparisons demonstrated statistically significant differences in histogram parameters of K and V [mean, standard deviation (SD), 50th, 75th, 90th. and 95th percentile] between IDH1 and IDH1 gliomas (P < 0.05, respectively). ROC curve analysis revealed that 50th percentile of K (0.019 min-1) and V (0.039) provided the perfect combination of sensitivity and specificity in differentiating gliomas with IDH1 from IDH1 . Irrespective of IDH1 mutation, histogram parameters of K and V were correlated with VEGF expression in gliomas (P < 0.05, respectively).
Conclusions:
VEGF expression is significantly lower in IDH1 gliomas as compared to the wildtype counterpart, and it is non-invasively predictable with histogram analysis of DCE-MRI.

