ArticleBioMed research international2021
Pretreatment Prediction of Relapse Risk in Patients with Osteosarcoma Using Radiomics Nomogram Based on CT: A Retrospective Multicenter Study.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Minimal residual disease and relapse surveillance in osteosarcoma: an action-linked framework integrating liquid biopsy and imaging biomarkers.Journal of bone oncology · 2026Review
- Time-dependent evolution of osteosarcoma recurrence risk across clinical risk stratification and its prognostic value.American journal of cancer research · 2026Article
- Research Progress on the Evaluation and Clinical Value of Negative Surgical Margins in Osteosarcoma.Orthopedic research and reviews · 2026Review
- Preoperative prediction of high-grade osteosarcoma response to neoadjuvant therapy based on a plain CT radiomics model: A dual-center study.Journal of bone oncology · 2024Article
- CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies.Insights into imaging · 2024Article
- Radiomics analysis based on CT for the prediction of pulmonary metastases in ewing sarcoma.BMC medical imaging · 2023Article
- Imaging evaluation of blood supply changes after chemotherapy of osteosarcoma and its correlation with tumor necrosis rate.Journal of bone oncology · 2023Article
- Cancer-Specific Survival after Limb Salvage versus Amputation in Children and Adolescents with Osteosarcoma: A Population-Based Analysis with Propensity Score Matching.Journal of oncology · 2023Article
- An updated systematic review of radiomics in osteosarcoma: utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics.Insights into imaging · 2022Article
- Postoperative Relapse Prediction in Patients With Ewing Sarcoma Using Computed Tomography-Based Radiomics Models Covering Tumor Per Se and Peritumoral Signatures.Journal of computer assisted tomographyArticle
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Authors and funding
11 authors.
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Abstract
objectiveTo develop and externally validate a CT-based radiomics nomogram for pretreatment prediction of relapse in osteosarcoma patients within one year. MATERIALS AND
methodsIn this multicenter retrospective study, a total of 80 patients (training cohort: 63 patients from three hospitals; validation cohort: 17 patients from three other hospitals) with osteosarcoma, undergoing pretreatment CT between August 2010 and December 2018, were identified from multicenter databases. Radiomics features were extracted and selected from tumor regions on CT image, and then, the radiomics signature was constructed. The radiomics nomogram that incorporated the radiomics signature and clinical-based risk factors was developed to predict relapse risk with a multivariate Cox regression model using the training cohort and validated using the external validation cohort. The performance of the nomogram was assessed concerning discrimination, calibration, reclassification, and clinical usefulness.
resultsKaplan-Meier curves based on the radiomics signature showed a significant difference between the high-risk and the low-risk groups in both training and validation cohorts (
conclusionsThis multicenter study demonstrates that a radiomics nomogram incorporated the radiomics signature and clinical-based risk factors can increase the predictive value of the osteosarcoma relapse risk, which supports the clinical application in different institutions.
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