Associations between Tumor Vascularity, Vascular Endothelial Growth Factor Expression and PET/MRI Radiomic Signatures in Primary Clear-Cell-Renal-Cell-Carcinoma: Proof-of-Concept Study
- Authors
- Yin, Qingbo; Hung, Sheng-Che; Wang, Li; Lin, Weili; Fielding, Julia R.; Rathmell, W. Kimryn; Khandani, Amir H.; Woods, Michael E.; Milowsky, Matthew I.; Brooks, Samira A.; Wallen, Eric. M.; Shen, Dinggang
- Issue Date
- 3-3월-2017
- Publisher
- NATURE PUBLISHING GROUP
- Citation
- SCIENTIFIC REPORTS, v.7
- Indexed
- SCIE
SCOPUS
- Journal Title
- SCIENTIFIC REPORTS
- Volume
- 7
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/84175
- DOI
- 10.1038/srep43356
- ISSN
- 2045-2322
- Abstract
- Studies have shown that tumor angiogenesis is an essential process for tumor growth, proliferation and metastasis. Also, tumor angiogenesis is an important prognostic factor of clear cell renal cell carcinoma (ccRCC), as well as a factor in guiding treatment with antiangiogenic agents. Here, we attempted to find the associations between tumor angiogenesis and radiomic imaging features from PET/MRI. Specifically, sparse canonical correlation analysis was conducted on 3 feature datasets (i.e., radiomic imaging features, tumor microvascular density (MVD), and vascular endothelial growth factor (VEGF) expression) from 9 patients with primary ccRCC. In order to overcome the potential bias of intratumoral heterogeneity of angiogenesis, this study investigated the relationship between regional expressions of angiogenesis and VEGF, and localized radiomic features from different parts within the tumors. Our study highlighted the significant strong correlations between radiomic features and MVD, and also demonstrated that the spatiotemporal features extracted from DCE-MRI provided stronger radiomic correlation to MVD than the textural features extracted from Dixon sequences and FDG PET. Furthermore, PET/MRI, which takes advantage of the combined functional and structural information, had higher radiomics correlation to MVD than solely utilizing PET or MRI alone.
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Collections - Graduate School > Department of Artificial Intelligence > 1. Journal Articles
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