The preliminary radiogenomics association between MR perfusion imaging parameters and genomic biomarkers, and their predictive performance of overall survival in patients with glioblastoma

Abstract

The radiogenomics association of neovascularization is important for overall survival (OS) in glioblastoma patients and remains unclear. The purpose of this study is to assess the association between MR perfusion imaging derived parameters and genomic biomarkers of glioblastoma, and to evaluate their prognostic value. This retrospective study enrolled 41 patients with newly diagnosed glioblastoma. The mean and maximal relative cerebral blood volume (rCBV) ratio (rCBV and rCBV), derived from MR perfusion weighted imaging, of the enhancing tumor, as well as maximal rCBV ratio of peri-enhancing tumor area (rCBV) were measured. The ki-67 labeling index, mammalian target of rapamycin (mTOR) activation, epidermal growth factor receptor (EGFR) amplification, isocitrate dehydrogenase (IDH) mutation and TP53 were assessed. There was a significant correlation between rCBV and mTOR based on Pearson's correlations with Benjamini-Hochberg adjustment for controlling false discovery rate, p = 0.047. The rCBV showed significant correlation with mTOR (p = 0.0183) after adjustment of gender and EGFR status. The mean rCBV value of the patients with OS shorter than 14 months was significantly higher than patients with OS longer than 14 months, p = 0.002. The rCBV and age were the two strongest predictors of OS (hazard ratio = 1.29 and 1.063 respectively) by Cox regression analysis. This study showed that hemodynamic abnormalities of glioblastoma were associated with genomics activation status of mTOR-EGFR pathway, however, the radiogenomics associations are different in enhancing and peri-enhancing area of glioblastoma. The rCBV has better prognostic value than genomic biomarkers alone.

IDH genotypes differentiation in glioblastomas using DWI and DSC-PWI in the enhancing and peri-enhancing region

“…Conventional and advanced magnetic resonance imaging have been widely used for gliomas grading and genotyping (8)(9)(10)(11). As previously reported, conventional magnetic resonance imaging (cMRI) features including tumor location might predict molecular profiles in GBMs in some instances (12,13).…”

Correlation Between Quantitative Perfusion Histogram Parameters of DCE-MRI and PTEN, P-Akt and m-TOR in Different Pathological Types of Lung Cancer

“…Phosphatidylinositol 3 kinase (PI3K) / protein kinase B (AKT) / mammalian target of rapamycin (mTOR) signaling pathway plays an important role in the genesis and development of many kinds of tumors. The signaling pathways through PI3K and AKT gene mutation and ampli cation, oncogene receptor activation, gene expression reduction of phpsphase and tensin homologue deleted on chromosome 10 (PTEN), and regulation of vascular endothelial growth factor (VEGF) expression and other mechanisms to promote tumor cell growth and angiogenesis [3][4][5]. Studies have shown that PTEN is a tumor suppressor gene with dual speci c phosphatase activity, and its gene mutation and loss of expression can cause the P13K / AKT / mTOR signaling pathway to be activated, leading to abnormal cell proliferation, in ltration and metastasis [6].…”

Machine‐learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time

“…In recent years, the emergence of radiogenomics, combing radiomics image features and genomics, allows the study of GBM more comprehensively. For example, MRI parameters revealed that haemodynamic abnormalities were associated with the expression level of the mTOR-EGFR pathway in [10]. Based on previous findings, we aimed to investigate the machine learning based methods in combination with radiogenomics to study the associations among MRI features, genomics and the survival rates in GBM patients.…”