ArticleCancer imaging : the official publication of the International Cancer Imaging Society2022
Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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10 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Artificial intelligence for the prediction of synchronous and metachronous liver metastasis in colorectal cancer patients: a systematic review and meta-analysis.Abdominal radiology (New York) · 2026Pooled it
- Radiomics' Role in Predicting Distant Metastases, Recurrence and Survival Outcome in Rectal Cancer: A Systematic Review.Cancers · 2026Review
- Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters.Insights into imaging · 2026Article
- Interpretable habitat radiomics model based on multi-sequence MRI for risk prediction of metachronous liver metastasis in rectal cancer: a multicenter study.Japanese journal of radiology · 2026Article
- Machine learning-based radiomics models for the prediction of metachronous liver metastases in patients with colorectal cancer: A multimodal study.Oncology letters · 2025Article
- Explainable multi-modal radiomics for early prediction of liver metastasis in rectal cancer: a multicentric study.Insights into imaging · 2025Article
- The impact of ultrasound contrast-enhanced fusion virtual navigation technology-guided microwave ablation (MWA) and standard MWA on the local tumor progression of hepatocellular carcinoma with unclear ultrasound images.European journal of medical research · 2025Article
- Cancer-induced systemic pre-conditioning of distant organs: building a niche for metastatic cells.Nature reviews. Cancer · 2024Review
- Radiomics in rectal cancer: current status of use and advances in research.Frontiers in oncology · 2024Review
- Immune determinants of the pre-metastatic niche.Cancer cell · 2023Review
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Authors and funding
7 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundTo develop a radiomics model based on pretreatment whole-liver portal venous phase (PVP) contrast-enhanced CT (CE-CT) images for predicting metachronous liver metastases (MLM) within 24 months after rectal cancer (RC) surgery.
methodsThis study retrospectively analyzed 112 RC patients without preoperative liver metastases who underwent rectal surgery between January 2015 and December 2017 at our institution. Volume of interest (VOI) segmentation of the whole-liver was performed on the PVP CE-CT images. All 1316 radiomics features were extracted automatically. The maximum-relevance and minimum-redundancy and least absolute shrinkage and selection operator methods were used for features selection and radiomics signature constructing. Three models based on radiomics features (radiomics model), clinical features (clinical model), and radiomics combined with clinical features (combined model) were built by multivariable logistic regression analysis. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of models, and calibration curve and the decision curve analysis were performed to evaluate the clinical application value.
resultsIn total, 52 patients in the MLM group and 60 patients in the non-MLM group were enrolled in this study. The radscore was built using 16 selected features and the corresponding coefficients. Both the radiomics model and the combined model showed higher diagnostic performance than clinical model (AUCs of training set: radiomics model 0.84 (95% CI, 0.76-0.93), clinical model 0.65 (95% CI, 0.55-0.75), combined model 0.85 (95% CI, 0.77-0.94); AUCs of validation set: radiomics model 0.84 (95% CI, 0.70-0.98), clinical model 0.58 (95% CI, 0.40-0.76), combined model 0.85 (95% CI, 0.71-0.99)). The calibration curves showed great consistency between the predicted value and actual event probability. The DCA showed that both the radiomics and combined models could add a net benefit on a large scale.
conclusionsThe radiomics model based on preoperative whole-liver PVP CE-CT could predict MLM within 24 months after RC surgery. Clinical features could not significantly improve the prediction efficiency of the radiomics model.
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