ReviewDiagnostics (Basel, Switzerland)2018
Radiogenomics and Radiomics in Liver Cancers.
Review in Diagnostics (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed.
- Comprehensive radiomics nomogram for predicting survival of patients with combined hepatocellular carcinoma and cholangiocarcinoma.World journal of gastroenterology · 2021Trial
- Advances in the Molecular Mechanisms of Cholangiocarcinoma: A Comprehensive Review of Biomarkers, Regulatory Pathways and Tumor Microenvironment Reprogramming.International journal of molecular sciences · 2026Review
- Pulmonary Artery Diameters in Children, Teenagers and Young Adults Derived from Quiescent Interval Slice Selective (QISS) Magnetic Resonance Angiography.Pediatric cardiology · 2026Article
- Radiogenomics and machine learning in hepatocellular carcinoma: from foundations to clinical translation.World journal of surgical oncology · 2026Review
- Radiomics for Detection and Differentiation of Intrahepatic Cholangiocarcinoma: A Systematic Review and Meta-Analysis.Cancers · 2026Review
- Multi-algorithm radiomics machine learning models integrating ultrasound imaging and inflammation-immune features for hepatic metastases identification.BMC medical imaging · 2025Article
- Clinical Nomogram Model for Pre-Operative Prediction of Microvascular Invasion of Hepatocellular Carcinoma before Hepatectomy.Medicina (Kaunas, Lithuania) · 2024Article
- Prediction of glypican-3 expression in hepatocellular carcinoma using multisequence magnetic resonance imaging-based histology nomograms.Quantitative imaging in medicine and surgery · 2024Article
- Predictability of the radiological response to Yttrium-90 transarterial radioembolization by dynamic magnetic resonance imaging-based radiomics analysis in patients with intrahepatic cholangiocarcinomaDiagnostic and interventional radiology (Ankara, Turkey) · 2024Article
- An Informative Review of Radiomics Studies on Cancer Imaging: The Main Findings, Challenges and Limitations of the Methodologies.Current oncology (Toronto, Ont.) · 2024Review
- Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment.La Radiologia medica · 2023Article
- Artificial intelligence and radiation effects on brain tissue in glioblastoma patient: preliminary data using a quantitative tool.La Radiologia medica · 2023Article
- Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics.Infectious agents and cancer · 2023Review
- Exploring Radiologists' Burnout in the COVID-19 Era: A Narrative Review.International journal of environmental research and public health · 2023Review
- Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence.Biology · 2023Review
- Development and External Validation of a Radiomics Model Derived from Preoperative Gadoxetic Acid-Enhanced MRI for Predicting Histopathologic Grade of Hepatocellular Carcinoma.Diagnostics (Basel, Switzerland) · 2023Article
- Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence.Cancers · 2023Review
- Predicting the risk of distant metastasis in patients with locally advanced rectal cancer using model based on pre-treatment T2WI-based radiomic features plus postoperative pathological stage.Frontiers in oncology · 2023Article
- Ultrasound-based radiomics for predicting different pathological subtypes of epithelial ovarian cancer before surgery.BMC medical imaging · 2022Article
- Radiomics textural features by MR imaging to assess clinical outcomes following liver resection in colorectal liver metastases.La Radiologia medica · 2022Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiogenomics is a computational discipline that identifies correlations between cross-sectional imaging features and tissue-based molecular data. These imaging phenotypic correlations can then potentially be used to longitudinally and non-invasively predict a tumor's molecular profile. A different, but related field termed radiomics examines the extraction of quantitative data from imaging data and the subsequent combination of these data with clinical information in an attempt to provide prognostic information and guide clinical decision making. Together, these fields represent the evolution of biomedical imaging from a descriptive, qualitative specialty to a predictive, quantitative discipline. It is anticipated that radiomics and radiogenomics will not only identify pathologic processes, but also unveil their underlying pathophysiological mechanisms through clinical imaging alone. Here, we review recent studies on radiogenomics and radiomics in liver cancers, including hepatocellular carcinoma, intrahepatic cholangiocarcinoma, and metastases to the liver.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.