ArticleBMC medical imaging2022
Prediction of the therapeutic efficacy of epirubicin combined with ifosfamide in patients with lung metastases from soft tissue sarcoma based on contrast-enhanced CT radiomics features.
Article in BMC medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Differentiating breast cancer lung metastasis from primary lung cancer using clinical and computed tomography radiomics features.Translational cancer research · 2026Article
- Radiomics of soft tissue sarcoma metastases to assess prognostic factors related to intrapatient intertumor heterogeneity.Translational cancer research · 2026Article
- Applying Radiomics to Predict Outcomes in Patients with High-Grade Retroperitoneal Sarcoma Treated with Preoperative Radiotherapy.Journal of imaging · 2025Article
- The impact of radiomics in the management of soft tissue sarcoma.Discover oncology · 2024Review
- Radiomics in Lung Metastases: A Systematic Review.Journal of personalized medicine · 2023Review
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate the value of contrast-enhanced computed tomography (CECT) radiomics features in predicting the efficacy of epirubicin combined with ifosfamide in patients with pulmonary metastases from soft tissue sarcoma.
methodsA retrospective analysis of 51 patients with pulmonary metastases from soft tissue sarcoma who received the chemotherapy regimen of epirubicin combined with ifosfamide was performed, and efficacy was evaluated by Recist1.1. ROIs (1 or 2) were selected for each patient. Lung metastases were used as target lesions (86 target lesions total), and the patients were divided into a progression group (n = 29) and a non-progressive group (n = 57); the latter included a stable group (n = 34) and a partial response group (n = 23). Information on lung metastases was extracted from CECT images before chemotherapy, and all lesions were delineated by ITK-SNAP software manually or semiautomatically. The decision tree classifier had a better performance in all radiomics models. A receiver operating characteristic curve was plotted to evaluate the predictive performance of the radiomics model.
resultsIn total, 851 CECT radiomics features were extracted for each target lesion and finally reduced to 2 radiomics features, which were then used to construct a radiomics model. Areas under the curves of the model for predicting lesion progression were 0.917 and 0.856 in training and testing groups, respectively.
conclusionThe model established based on the radiomics features of CECT before treatment has certain predictive value for assessing the efficacy of chemotherapy for patients with soft tissue sarcoma lung metastases.
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