ArticleScientific reports2017
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.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.
- Diagnostic performance of MRI, SPECT, and PET in detecting renal cell carcinoma: a systematic review and meta-analysis.BMC cancer · 2022Pooled it
- Staging and imaging-based prognostication in renal cell carcinoma: current guidelines and practical considerations.Abdominal radiology (New York) · 2026Review
- Imaging the hallmarks of cancer.Nature reviews. Cancer · 2026Review
- Bridging tumor biology and radiomics through an ultra-large physics-driven vascular model.npj biomedical innovations · 2026Article
- Analysis of correlation between dynamic contrast-enhanced ultrasound and angiogenesis activity of renal cell carcinoma.Ultrasound international open · 2025Article
- Deep learning techniques for imaging diagnosis of renal cell carcinoma: current and emerging trends.Frontiers in oncology · 2023Review
- Review
- Article
- Immunology and Immunotherapeutic Approaches for Advanced Renal Cell Carcinoma: A Comprehensive Review.International journal of molecular sciences · 2021Review
- Dynamic contrast-enhanced breast MRI features correlate with invasive breast cancer angiogenesis.NPJ breast cancer · 2021Article
- The Biological Meaning of Radiomic Features.Radiology · 2021Review
- Multiparametric MRI for assessment of early response to neoadjuvant sunitinib in renal cell carcinoma.PloS one · 2021Article
- Computed Tomography Radiomics Kinetics as Early Imaging Correlates of Osteoradionecrosis in Oropharyngeal Cancer Patients.Frontiers in artificial intelligence · 2021Article
- Quantification of contrast-uptake as imaging biomarker for disease progression of renal cell carcinoma after tumor ablation.Acta radiologica (Stockholm, Sweden : 1987) · 2020Article
- Association of tumor grade, enhancement on multiphasic CT and microvessel density in patients with clear cell renal cell carcinoma.Abdominal radiology (New York) · 2020Article
- Radiomics Applications in Renal Tumor Assessment: A Comprehensive Review of the Literature.Cancers · 2020Review
- Identification of Predominant Histopathological Growth Patterns of Colorectal Liver Metastasis by Multi-Habitat and Multi-Sequence Based Radiomics Analysis.Frontiers in oncology · 2020Article
- Radiomics for radiation oncologists: are we ready to go?BJR open · 2020Review
- Role of Artificial Intelligence in Kidney Disease.International journal of medical sciences · 2020Review
- What can artificial intelligence teach us about the molecular mechanisms underlying disease?European journal of nuclear medicine and molecular imaging · 2019Review
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 4 countries.
Funding
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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