ArticleEuropean radiology2020
Radiomics analysis of lung CT image for the early detection of metastases in patients with breast cancer: preliminary findings from a retrospective cohort study.
Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 15 citations in OpenAlex.
- Review
- Cancer-induced systemic pre-conditioning of distant organs: building a niche for metastatic cells.Nature reviews. Cancer · 2024Review
- Immune determinants of the pre-metastatic niche.Cancer cell · 2023Review
- Radiomics signature of brain metastasis: prediction of EGFR mutation status.European radiology · 2021Article
- Computed tomography reveals microenvironment changes in premetastatic lung.European radiology · 2021Article
- Early recognition of necrotizing pneumonia in children based on non-contrast-enhanced computed tomography radiomics signatures.Translational pediatrics · 2021Article
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10 authors at 2 institutions in 1 country.
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Abstract
objectivesTo investigate whether subtle changes in radiomics features are present in lung CT images prior to the development of CT-detectable lung metastases in patients with breast cancer.
methodsThirty-three radiomics features were measured in the metastasis region (MR) and in matched contralateral tissues (non-metastasis region, NMR) of 29 breast cancer patients at the last CT scan, as well as in the corresponding regions of the patients' pre-metastasis scan (pre-MR and pre-NMR). We also compared them with normal lung tissues (control group, CG) from 29 healthy volunteers. Then, 8 patients from the 29 patients with lung metastases and 8 patients who did not develop lung metastases were chosen for further study of the correlation between radiomics parameters and tumor growth.
resultsIn the MR vs. NMR and MR vs. CG groups, almost all radiomics features were significantly different. Twenty-six parameters showed significant differences between the pre-MRs and pre-NMRs. Linear fitting demonstrated a significant correlation between 5 features and tumor growth in the metastasis group, but not in the non-metastasis group. Among them, run percentage was the most representative feature. The calculated area under curves (AUCs), based on run percentage for the classification of metastasis and pre-metastasis, were 0.954 and 0.852, respectively.
conclusionsRadiomics features may allow early detection of lung metastases before they become visually detectable, and the feature run percentage may be a promising image surrogate marker for the microinvasion of tumor cells into the lung tissue. KEY POINTS: • The significant differences in radiomics features between pre-MR and pre-NMR are critical for the early detection of lung metastases. • Five radiomics features show a correlation with tumor growth. • The radiomics feature run percentage may be a potential imaging biomarker for the early detection of lung metastases.
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