Dataset Information

Radiogenomic analysis of vascular endothelial growth factor in patients with diffuse gliomas.

ABSTRACT: OBJECTIVE:To predict vascular endothelial growth factor (VEGF) expression in patients with diffuse gliomas using radiomic analysis. MATERIALS AND METHODS:Preoperative magnetic resonance images were retrospectively obtained from 239 patients with diffuse gliomas (World Health Organization grades II-IV). The patients were randomly assigned to a training group (n?=?160) or a validation group (n?=?79) at a 2:1 ratio. For each patient, a total of 431 radiomic features were extracted. The minimum redundancy maximum relevance (mRMR) algorithm was used for feature selection. A machine-learning model for predicting VEGF status was then developed using the selected features and a support vector machine classifier. The predictive performance of the model was evaluated in both groups using receiver operating characteristic curve analysis, and correlations between selected features were assessed. RESULTS:Nine radiomic features were selected to generate a VEGF-associated radiomic signature of diffuse gliomas based on the mRMR algorithm. This radiomic signature consisted of two first-order statistics or related wavelet features (Entropy and Minimum) and seven textural features or related wavelet features (including Cluster Tendency and Long Run Low Gray Level Emphasis). The predictive efficiencies measured by the area under the curve were 74.1% in the training group and 70.2% in the validation group. The overall correlations between the 9 radiomic features were low in both groups. CONCLUSIONS:Radiomic analysis facilitated efficient prediction of VEGF status in diffuse gliomas, suggesting that using tumor-derived radiomic features for predicting genomic information is feasible.

SUBMITTER: Sun Z

PROVIDER: S-EPMC6805458 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Radiogenomic analysis of vascular endothelial growth factor in patients with diffuse gliomas.

Sun Zhiyan Z Li Yiming Y Wang Yinyan Y Fan Xing X Xu Kaibin K Wang Kai K Li Shaowu S Zhang Zhong Z Jiang Tao T Liu Xing X

Cancer imaging : the official publication of the International Cancer Imaging Society 20191021 1

<h4>Objective</h4>To predict vascular endothelial growth factor (VEGF) expression in patients with diffuse gliomas using radiomic analysis.<h4>Materials and methods</h4>Preoperative magnetic resonance images were retrospectively obtained from 239 patients with diffuse gliomas (World Health Organization grades II-IV). The patients were randomly assigned to a training group (n = 160) or a validation group (n = 79) at a 2:1 ratio. For each patient, a total of 431 radiomic features were extracted. T ...[more]

PMID: 31639060

Similar Datasets

Project description:PURPOSE:To assess systemic vascular endothelial growth factor (VEGF)-A levels after treatment with intravitreous aflibercept, bevacizumab, or ranibizumab. DESIGN:Comparative-effectiveness trial with participants randomly assigned to 2 mg aflibercept, 1.25 mg bevacizumab, or 0.3 mg ranibizumab after a re-treatment algorithm. PARTICIPANTS:Participants with available plasma samples (N = 436). METHODS:Plasma samples were collected before injections at baseline and 4-week, 52-week, and 104-week visits. In a preplanned secondary analysis, systemic-free VEGF levels from an enzyme-linked immunosorbent assay were compared across anti-VEGF agents and correlated with systemic side effects. MAIN OUTCOME MEASURES:Changes in the natural log (ln) of plasma VEGF levels. RESULTS:Baseline free VEGF levels were similar across all 3 groups. At 4 weeks, mean ln(VEGF) changes were -0.30±0.61 pg/ml, -0.31±0.54 pg/ml, and -0.02±0.44 pg/ml for the aflibercept, bevacizumab, and ranibizumab groups, respectively. The adjusted differences between treatment groups (adjusted confidence interval [CI]; P value) were -0.01 (-0.12 to +0.10; P = 0.89), -0.31 (-0.44 to -0.18; P < 0.001), and -0.30 (-0.43 to -0.18; P < 0.001) for aflibercept-bevacizumab, aflibercept-ranibizumab, and bevacizumab-ranibizumab, respectively. At 52 weeks, a difference in mean VEGF changes between bevacizumab and ranibizumab persisted (-0.23 [-0.38 to -0.09]; P < 0.001); the difference between aflibercept and ranibizumab was -0.12 (P = 0.07) and between aflibercept and bevacizumab was +0.11 (P = 0.07). Treatment group differences at 2 years were similar to 1 year. No apparent treatment differences were detected at 52 or 104 weeks in the cohort of participants not receiving injections within 1 or 2 months before plasma collection. Participants with (N = 9) and without (N = 251) a heart attack or stroke had VEGF levels that appeared similar. CONCLUSIONS:These data suggest that decreases in plasma free-VEGF levels are greater after treatment with aflibercept or bevacizumab compared with ranibizumab at 4 weeks. At 52 and 104 weeks, a greater decrease was observed in bevacizumab versus ranibizumab. Results from 2 subgroups of participants who did not receive injections within at least 1 month and 2 months before collection suggest similar changes in VEGF levels after stopping injections. It is unknown whether VEGF levels return to normal as the drug is cleared from the system or whether the presence of the drug affects the assay's ability to accurately measure free VEGF. No significant associations between VEGF concentration and systemic factors were noted.

Dataset Information

Radiogenomic analysis of vascular endothelial growth factor in patients with diffuse gliomas.

Publications

Radiogenomic analysis of vascular endothelial growth factor in patients with diffuse gliomas.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets