ArticleFrontiers in medicine2024
Radiomics analysis based on multiparametric magnetic resonance imaging for differentiating early stage of cervical cancer.
Article in Frontiers in medicine, 2024. 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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Who cites it
6 citing papers in PubMed.
- Clinical translation of a DWI-radiomics nomogram integrating serum biomarkers for pretreatment staging of cervical cancer.BMC medical imaging · 2026Article
- Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer.Scientific reports · 2025Article
- Construction of the preoperative staging prediction model for cervical cancer based on deep learning and MRI: a retrospective study.Frontiers in oncology · 2025Article
- An interpretable clinical ultrasound-radiomics combined model for diagnosis of stage I cervical cancer.Frontiers in oncology · 2024Article
- Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics.Technology in cancer research & treatmentArticle
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Authors and funding
8 authors.
Funding
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Abstract
Objective: To investigate the performance of multiparametric magnetic resonance imaging (MRI)-based radiomics models in differentiating early stage of cervical cancer (Stage I-IIa vs. IIb-IV). Methods: One hundred patients with cervical cancer who underwent preoperative MRI between June 2020 and March 2022 were retrospectively enrolled. Training ( Results: The characteristics of age, histological subtypes, tumor grades, and node status were not significantly different between the low [I-IIa] and high [IIb-IV] FIGO stages ( Conclusion: The radiomics models combined T2W and ADC maps had good predictive performance in differentiating the early stage from locally advanced cervical cancer.
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