ReviewCancers2020
Radiomics of Liver Metastases: A Systematic Review.
Review in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
69 citing papers in PubMed.
- Early hemodynamic assessment and longitudinal imaging for predicting graft outcomes post-transplant.Annals of medicine · 2026Article
- Longitudinal radiomics of liver metastases during magnetic resonance-guided radiotherapy.Physics and imaging in radiation oncology · 2026Article
- Radiomics-based outcome prediction for irinotecan-TACE in colorectal liver metastases: advanced analysis from the prospective CIREL trial.European radiology · 2026Article
- CT-based radiomics improves survival prediction in colorectal liver metastases: beyond clinical scores.Updates in surgery · 2026Article
- Liver metastases beyond classical imaging findings.Abdominal radiology (New York) · 2026Review
- CT radiomics for survival risk stratification in resectable colorectal liver metastases: a multi-centre study.Scientific reports · 2026Article
- Article
- Robust multicentre detection and classification of colorectal liver metastases on CT: application of foundation models.NPJ precision oncology · 2026Article
- Radiomics of portal-phase ring enhancement: a novel imaging biomarker for bevacizumab response associated with overall survival rates. It might help with surgical decision-making in colorectal liver metastases?Updates in surgery · 2026Article
- Review
- Pretreatment CT radiomics for prediction of pathological complete response after neoadjuvant chemoimmunotherapy in NSCLC: a multicenter study incorporating habitat analysis.Frontiers in immunology · 2026Article
- CT-Based Radiomics Models with External Validation for Prediction of Recurrence and Disease-Specific Mortality After Radical Surgery of Colorectal Liver Metastases.Annals of surgical oncology · 2025Article
- Evidence for imaging-based diagnosis of liver metastases from colorectal cancer.Journal of gastroenterology · 2025Review
- Machine learning model-based approach using cellular proliferation marker expression for preoperative clinical decision-making in patients with hepatocellular carcinoma.World journal of gastrointestinal oncology · 2025Article
- Review
- Radiomics-driven spectral profiling of six kidney stone types with monoenergetic CT reconstructions in photon-counting CT.European radiology · 2025Article
- Unveiling the biological side of PET-derived biomarkers: a simulation-based approach applied to PDAC assessment.European journal of nuclear medicine and molecular imaging · 2025Article
- Finding Reproducible and Prognostic Radiomic Features in Variable Slice Thickness Contrast Enhanced CT of Colorectal Liver Metastases.The journal of machine learning for biomedical imaging · 2025Article
- Development and independent validation of explainable radiomics-based machine learning models for prognosis in colorectal liver metastases.Frontiers in digital health · 2025Article
- Current status and quality of prognosis prediction models of non-small cell lung cancer constructed using computed tomography (CT)-based radiomics: a systematic review and radiomics quality score 2.0 assessment.Quantitative imaging in medicine and surgery · 2024Review
9 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Multidisciplinary management of patients with liver metastases (LM) requires a precision medicine approach, based on adequate profiling of tumor biology and robust biomarkers. Radiomics, defined as the high-throughput identification, analysis, and translational applications of radiological textural features, could fulfill this need. The present review aims to elucidate the contribution of radiomic analyses to the management of patients with LM. We performed a systematic review of the literature through the most relevant databases and web sources. English language original articles published before June 2020 and concerning radiomics of LM extracted from CT, MRI, or PET-CT were considered. Thirty-two papers were identified. Baseline higher entropy and lower homogeneity of LM were associated with better survival and higher chemotherapy response rates. A decrease in entropy and an increase in homogeneity after chemotherapy correlated with radiological tumor response. Entropy and homogeneity were also highly predictive of tumor regression grade. In comparison with RECIST criteria, radiomic features provided an earlier prediction of response to chemotherapy. Lastly, texture analyses could differentiate LM from other liver tumors. The commonest limitations of studies were small sample size, retrospective design, lack of validation datasets, and unavailability of univocal cut-off values of radiomic features. In conclusion, radiomics can potentially contribute to the precision medicine approach to patients with LM, but interdisciplinarity, standardization, and adequate software tools are needed to translate the anticipated potentialities into clinical practice.
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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.