ArticlePloS one2015
Cholangiocarcinoma: Correlation between Molecular Profiling and Imaging Phenotypes.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Automated Radiomics Model for Preoperative Pancreatic Neuroendocrine Tumor Grade Prediction.Annals of surgical oncology · 2026Article
- Molecular and Histological Profiles and Relevant Imaging Signatures of Intrahepatic Cholangiocarcinoma.Journal of clinical and translational hepatology · 2025Review
- Diagnosis of Cholangiocarcinoma: The New Biological and Technological Horizons.Diagnostics (Basel, Switzerland) · 2025Review
- Preoperative assessment of longitudinal extent in hilar cholangiocarcinoma using noninvasive enhanced MR radiomics: a multicenter study.Frontiers in oncology · 2025Article
- Review
- Molecular Profile of Intrahepatic Cholangiocarcinoma.International journal of molecular sciences · 2023Review
- Review of the Application of Dual Drug Delivery Nanotheranostic Agents in the Diagnosis and Treatment of Liver Cancer.Molecules (Basel, Switzerland) · 2023Review
- Radiomic signatures from T2W and DWI MRI are predictive of tumour hypoxia in colorectal liver metastases.Insights into imaging · 2023Article
- Systematic review with radiomics quality score of cholangiocarcinoma: an EuSoMII Radiomics Auditing Group Initiative.Insights into imaging · 2023Article
- Texture analysis on routine MRI sequences to differentiate between focal nodular hyperplasia and hepatocellular adenoma.Polish journal of radiology · 2023Article
- Prediction of angiogenesis in extrahepatic cholangiocarcinoma using MRI-based machine learning.Frontiers in oncology · 2023Article
- Personalized intrahepatic cholangiocarcinoma prognosis prediction using radiomics: Application and development trend.Frontiers in oncology · 2023Review
- Article
- Radiomics of Biliary Tumors: A Systematic Review of Current Evidence.Diagnostics (Basel, Switzerland) · 2022Review
- Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma.BMC cancer · 2021Article
- Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics.Abdominal radiology (New York) · 2021Article
- Quantitative Computed Tomography Image Analysis to Predict Pancreatic Neuroendocrine Tumor Grade.JCO clinical cancer informatics · 2021Article
- Radiomics in immuno-oncology.Immuno-oncology technology · 2021Review
- Radiomics of cholangiocarcinoma on pretreatment CT can identify patients who would best respond to radioembolisation.European radiology · 2020Article
- Outcomes assessment in intrahepatic cholangiocarcinoma using qualitative and quantitative imaging features.Cancer imaging : the official publication of the International Cancer Imaging Society · 2020Article
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Authors and funding
10 authors.
Funding
Abstract
purposeTo investigate associations between imaging features of cholangiocarcinoma by visual assessment and texture analysis, which quantifies heterogeneity in tumor enhancement patterns, with molecular profiles based on hypoxia markers.
methodsThe institutional review board approved this HIPAA-compliant retrospective study of CT images of intrahepatic cholangiocarcinoma, obtained before surgery. Immunostaining for hypoxia markers (EGFR, VEGF, CD24, P53, MDM2, MRP-1, HIF-1α, CA-IX, and GLUT1) was performed on pre-treatment liver biopsies. Quantitative imaging phenotypes were determined by texture analysis with gray level co-occurrence matrixes. The correlations between quantitative imaging phenotypes, qualitative imaging features (measured by radiographic inspection alone), and expression levels of the hypoxia markers from the 25 tumors were assessed.
resultsTwenty-five patients were included with a median age of 62 years (range: 54-84). The median tumor size was 10.2 cm (range: 4-14), 10 (40%) were single tumors, and 90% were moderately differentiated. Positive immunostaining was recorded for VEGF in 67% of the cases, EGFR in 75%, and CD24 in 55%. On multiple linear regression analysis, quantitative imaging phenotypes correlated significantly with EGFR and VEGF expression levels (R2 = 0.4, p<0.05 and R2 = 0.2, p<0.05, respectively), while a trend was demonstrated with CD24 expression (R2 = 0.33, p = 0.1). Three qualitative imaging features correlated with VEGF and CD24 expression (P<0.05), however, none of the qualitative features correlated with the quantitative imaging phenotypes.
conclusionQuantitative imaging phenotypes, as defined by texture analysis, correlated with expression of specific markers of hypoxia, regardless of conventional imaging features.
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