ArticleQuantitative imaging in medicine and surgery2023
Development of a novel tumor microenvironment-related radiogenomics model for prognosis prediction in hepatocellular carcinoma.
Article in Quantitative imaging in medicine and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Noninvasive Multi-Omics Radiomic Model Integrating scRNA-seq and Bulk RNA-seq for Hepatocellular Carcinoma Prognosis.Journal of imaging informatics in medicine · 2026Article
- Integrating MRI radiomics and transcriptomics to predict IDH mutation status and prognosis in glioma.Cancer cell international · 2026Article
- Radiogenomics and machine learning in hepatocellular carcinoma: from foundations to clinical translation.World journal of surgical oncology · 2026Review
- Review
- Pulsed Low-Dose-Rate Chemoradiation Induces Stromal Reprogramming in Pancreatic CAF-Generated ECM: Quantification by the HOST-Factor.Gastro hep advances · 2026Article
- Current applications of radiomics in the assessment of tumor microenvironment of hepatocellular carcinoma.Abdominal radiology (New York) · 2025Review
- MiR-10a-5p suppresses hepatocellular carcinoma progression and microvascular invasion by targeting TFR1-STAT3-CD24 signaling axis.Frontiers in oncology · 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
- Preoperative prediction of Ki-67 expression in hepatocellular carcinoma by spectral imaging on dual-energy computed tomography (DECT).Quantitative imaging in medicine and surgery · 2024Article
- [Research progress and prospects of the application of radiographic imaging in the precise diagnosis and treatment of hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2024Review
- Prediction of glypican-3 expression in hepatocellular carcinoma using multisequence magnetic resonance imaging-based histology nomograms.Quantitative imaging in medicine and surgery · 2024Article
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6 authors.
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Abstract
Background: The tumour microenvironment (TME) has occupied a potent position in the tumorigenesis and tumor progression of hepatocellular carcinoma (HCC). Radiogenomics is an emerging field that integrates imaging and genetic information, thus offering a novel class of non-invasive biomarkers with diagnostic, prognostic, and treatment response. However, optimal evaluation methodologies for radiogenomics in patients with HCC have not been well established. Therefore, this study aims to develop a radiogenomics models, associating contrast-enhanced computed tomography (CECT) based radiomics features and transcriptomics data with TME, to increase predictive precision for overall survival (OS) in patients with HCC. Methods: Transcriptome profiles of 365 patients with HCC from The Cancer Genome Atlas (TCGA)-HCC cohort were used to obtain TME-related genes by differential expression analysis. TME-related radiomics features of 53 patients with HCC from The Cancer Imaging Archive (TCIA)-HCC cohort matched with the TCGA-HCC cohort were screened via correlation analysis. Furthermore, a radiogenomics score-based prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis in the TCIA-HCC cohort. Finally, the ability to predict prognosis and the value of the model in identifying the abundance of immune cell infiltration were investigated. Results: A radiogenomics prognostic model was developed, which incorporated 1 radiomics feature [original_gray-level co-occurrence matrix (glcm)_inverse difference normalized (Idn)] and 3 genes [spen paralogue and orthologue C‑terminal domain containing 1 ( Conclusions: The novel CECT-based radiogenomics model may provide valuable insights for prognostic stratification and TME assessment of patients with HCC.
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