期刊
SCIENTIFIC REPORTS
卷 8, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41598-017-18310-0
关键词
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资金
- National Cancer Institute of the National Institutes of Health [1U24CA199374-01, R01CA202752-01A1 R01CA208236-01A1 R21CA179327-01]
- National Institute of Diabetes and Digestive and Kidney Diseases [R21CA195152-01, R01DK098503-02]
- National Center for Research Resources [1 C06 RR12463-01]
- DOD Prostate Cancer Synergistic Idea Development Award [PC120857]
- DOD Lung Cancer Idea Development New Investigator Award [LC130463]
- DOD Prostate Cancer Idea Development Award
- DOD Peer Reviewed Cancer Research Program [W81XWH-16-1-0329]
- Ohio Third Frontier Technology Validation Fund
- Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering
- Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University
Hypoxia, a characteristic trait of Glioblastoma (GBM), is known to cause resistance to chemo-radiation treatment and is linked with poor survival. There is hence an urgent need to non-invasively characterize tumor hypoxia to improve GBM management. We hypothesized that (a) radiomic texture descriptors can capture tumor heterogeneity manifested as a result of molecular variations in tumor hypoxia, on routine treatment naive MRI, and (b) these imaging based texture surrogate markers of hypoxia can discriminate GBM patients as short-term (STS), mid-term (MTS), and long-term survivors (LTS). 115 studies (33 STS, 41 MTS, 41 LTS) with gadolinium-enhanced T1-weighted MRI (Gd-T1w) and T2-weighted (T2w) and FLAIR MRI protocols and the corresponding RNA sequences were obtained. After expert segmentation of necrotic, enhancing, and edematous/nonenhancing tumor regions for every study, 30 radiomic texture descriptors were extracted from every region across every MRI protocol. Using the expression profile of 21 hypoxia-associated genes, a hypoxia enrichment score (HES) was obtained for the training cohort of 85 cases. Mutual information score was used to identify a subset of radiomic features that were most informative of HES within 3-fold cross-validation to categorize studies as STS, MTS, and LTS. When validated on an additional cohort of 30 studies (11 STS, 9 MTS, 10 LTS), our results revealed that the most discriminative features of HES were also able to distinguish STS from LTS (p = 0.003).
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