ReviewCancers2021
Radiogenomics: Hunting Down Liver Metastasis in Colorectal Cancer Patients.
Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI-driven estimation of O6 methylguanine-DNA-methyltransferase (MGMT) promoter methylation in glioblastoma patients: a systematic review with bias analysis.Journal of cancer research and clinical oncology · 2024Pooled it
- Gut microbiota-driven pre-metastatic niche formation in colorectal cancer liver metastasis: mechanisms and translational significance.Gut pathogens · 2026Review
- Radiogenomics and machine learning in hepatocellular carcinoma: from foundations to clinical translation.World journal of surgical oncology · 2026Review
- Prognostic Factors in Colorectal Liver Metastases: An Exhaustive Review of the Literature and Future Prospectives.Cancers · 2025Review
- Explainable multi-modal radiomics for early prediction of liver metastasis in rectal cancer: a multicentric study.Insights into imaging · 2025Article
- Predictive modeling for metastasis in oncology: current methods and future directions.Annals of medicine and surgery (2012) · 2025Review
- Understanding pre-metastatic niche formation: implications for colorectal cancer liver metastasis.Journal of translational medicine · 2025Review
- Image Analysis as tool for Predicting Colorectal Cancer Molecular Alterations: A Scoping Review.Molecular imaging and radionuclide therapy · 2025Article
- A study predicting long-term survival capacity in postoperative advanced gastric cancer patients based on MAOA and subcutaneous muscle fat characteristics.World journal of surgical oncology · 2024Article
- Rapid detection of liver metastasis risk in colorectal cancer patients through blood test indicators.Frontiers in oncology · 2024Article
- Radiomics and Radiogenomics in Pelvic Oncology: Current Applications and Future Directions.Current oncology (Toronto, Ont.) · 2023Review
- Dynamic radiomics for predicting the efficacy of antiangiogenic therapy in colorectal liver metastases.Frontiers in oncology · 2023Article
- Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine.Cancers · 2022Review
- Radiomics textural features by MR imaging to assess clinical outcomes following liver resection in colorectal liver metastases.La Radiologia medica · 2022Article
- Combined Hepatocellular-Cholangiocarcinoma: What the Multidisciplinary Team Should Know.Diagnostics (Basel, Switzerland) · 2022Review
- CT-Based Radiomics Analysis to Predict Histopathological Outcomes Following Liver Resection in Colorectal Liver Metastases.Cancers · 2022Article
- The Value ofDiagnostics (Basel, Switzerland) · 2022Review
- An update on radiomics techniques in primary liver cancers.Infectious agents and cancer · 2022Article
- EOB-MR Based Radiomics Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases.Cancers · 2022Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Radiomics is a developing new discipline that analyzes conventional medical images to extract quantifiable data that can be mined for new biomarkers that show the biology of pathological processes at microscopic levels. These data can be converted into image-based signatures to improve diagnostic, prognostic and predictive accuracy in cancer patients. The combination of radiomics and molecular data, called radiogenomics, has clear implications for cancer patients' management. Though some studies have focused on radiogenomics signatures in hepatocellular carcinoma patients, only a few have examined colorectal cancer metastatic lesions in the liver. Moreover, the need to differentiate between liver lesions is fundamental for accurate diagnosis and treatment. In this review, we summarize the knowledge gained from radiomics and radiogenomics studies in hepatic metastatic colorectal cancer patients and their use in early diagnosis, response assessment and treatment decisions. We also investigate their value as possible prognostic biomarkers. In addition, the great potential of image mining to provide a comprehensive view of liver niche formation is examined thoroughly. Finally, new challenges and current limitations for the early detection of the liver premetastatic niche, based on radiomics and radiogenomics, are also discussed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.