ArticleEuropean radiology2021
Radiomics complements clinical, radiological, and technical features to assess local control of colorectal cancer lung metastases treated with radiofrequency ablation.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- Artificial Intelligence in Thermal Ablation: Current Applications and Future Directions in Microwave Technologies.Biomimetics (Basel, Switzerland) · 2025Review
- Development of a predictive model for pneumothorax after microwave ablation based on radiomics and clinical baseline data.BMC pulmonary medicine · 2025Article
- Applications of artificial intelligence in interventional oncology: An up-to-date review of the literature.Japanese journal of radiology · 2025Review
- Stereotactic ablative brachytherapy versus percutaneous microwave ablation as salvage treatments for lung oligometastasis from colorectal cancer.BMC cancer · 2024Article
- Habitat-based radiomics analysis for evaluating immediate response in colorectal cancer lung metastases treated by radiofrequency ablation.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Retrospective cohort study on the correlation analysis among peri-procedural factors, complications, and local tumor progression of lung tumors treated with CT-guided microwave ablation.Journal of thoracic disease · 2023Article
- Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment.La Radiologia medica · 2023Article
- CT-based radiomics models may predict the early efficacy of microwave ablation in malignant lung tumors.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023Article
- Radiofrequency ablation of lung metastases of colorectal cancer: could early radiomics analysis of the ablation zone help detect local tumor progression?The British journal of radiology · 2023Article
- Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics.Infectious agents and cancer · 2023Review
- Ablation of pulmonary neoplasms: review of literature and future perspectives.Polish journal of radiology · 2023Review
- A CT-based radiomics approach to predict immediate response of radiofrequency ablation in colorectal cancer lung metastases.Frontiers in oncology · 2023Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesRadiofrequency ablation (RFA) of lung metastases of colorectal origin can improve patient survival and quality of life. Our aim was to identify pre- and per-RFA features predicting local control of lung metastases following RFA.
methodsThis case-control single-center retrospective study included 119 lung metastases treated with RFA in 48 patients (median age: 60 years). Clinical, technical, and radiological data before and on early CT scan (at 48 h) were retrieved. After CT scan preprocessing, 64 radiomics features were extracted from pre-RFA and early control CT scans. Log-rank tests were used to detect categorical variables correlating with post-RFA local tumor progression-free survival (LTPFS). Radiomics prognostic scores (RPS) were developed on reproducible radiomics features using Monte-Carlo cross-validated LASSO Cox regressions.
resultsTwenty-six of 119 (21.8%) nodules demonstrated local progression (median delay: 11.2 months). In univariate analysis, four non-radiomics variables correlated with post-RFA-LTPFS: nodule size (> 15 mm, p < 0.001), chosen electrode (with difference between covered array and nodule diameter < 20 mm or non-expandable electrode, p = 0.03), per-RFA intra-alveolar hemorrhage (IAH, p = 0.002), and nodule location into the ablation zone (not seen or in contact with borders, p = 0.005). The highest prognostic performance was reached with the multivariate model including a RPS built on 4 radiomics features from pre-RFA and early revaluation CT scans (cross-validated concordance index= 0.74) in which this RPS remained an independent predictor (cross-validated HR = 3.49, 95% confidence interval = [1.76 - 6.96]).
conclusionsTechnical, radiological, and radiomics features of the lung metastases before RFA and of the ablation zone at 48 h can help discriminate nodules at risk of local progression that could benefit from complementary local procedure. KEY POINTS: • The highest prognostic performance to predict post-RFA LTPFS was reached with a parsimonious model including a radiomics score built with 4 radiomics features. • Nodule size, difference between electrode diameter, use of non-expandable electrode, per-RFA hemorrhage, and a tumor not seen or in contact with the ablation zone borders at 48-h CT were correlated with post-RFA LTPFS.
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