ArticleTechnology in cancer research & treatment2019
Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression.
Article in Technology in cancer research & treatment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
- Circulating Tumor Function: A Systems Biology Framework for Liquid Biopsy in Genitourinary Cancers.Genes · 2026Review
- From Radiomics to Radiogenomics: Decoding Renal Cell Carcinoma Biology for Precision Medicine-a narrative review.Insights into imaging · 2025Review
- Machine learning-assisted radiogenomic analysis for miR-15a expression prediction in renal cell carcinoma.BMC cancer · 2025Article
- From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Phenomic Imaging.Phenomics (Cham, Switzerland) · 2023Review
- Genetic and Epigenetic Characteristics in Isolated Pancreatic Metastases of Clear-Cell Renal Cell Carcinoma.International journal of molecular sciences · 2023Review
- Role of AI and Radiomic Markers in Early Diagnosis of Renal Cancer and Clinical Outcome Prediction: A Brief Review.Cancers · 2023Review
- Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects.International journal of molecular sciences · 2023Review
- Prognostic evaluation based on radiological morphological characteristic for tumors larger than 7 cm in renal cell carcinoma.Journal of cancer research and clinical oncology · 2023Review
- Novel Imaging Methods for Renal Mass Characterization: A Collaborative Review.European urology · 2022Review
- Radiogenomics in Clear Cell Renal Cell Carcinoma: A Review of the Current Status and Future Directions.Cancers · 2022Review
- Review
- Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients.Diagnostics (Basel, Switzerland) · 2021Article
- Radiomics and Radiogenomics in Evaluation of Colorectal Cancer Liver Metastasis.Frontiers in oncology · 2021Review
- Development and Validation of a Radiomic Nomogram for Predicting the Prognosis of Kidney Renal Clear Cell Carcinoma.Frontiers in oncology · 2021Article
- Background, applications and challenges of radiogenomics in genitourinary tumor.American journal of cancer research · 2021Review
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13 authors.
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Abstract
purposeA relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs.
methodsIn a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort.
resultsIn this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management.
conclusionIn this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found.
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