ArticleFrontiers in oncology2024
MRI radiomics captures early treatment response in patient-derived organoid endometrial cancer mouse models.
Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Organoids in Precision Radiotherapy: Methodological Foundations, Tumor-Specific Evidence, and Translational Roadmaps.Cancer medicine · 2026Review
- Review
- Evaluation of early chemotherapy response by combining static- and dynamic [EJNMMI research · 2025Article
- MRI Radiomics Predicts Early Biological Progression in a Preclinical Colon Cancer Model Following Mesenchymal Stem Cell Intervention.Cancer management and research · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
Background: Radiomics can capture microscale information in medical images beyond what is visible to the naked human eye. Using a clinically relevant mouse model for endometrial cancer, the objective of this study was to develop and validate a radiomic signature ( Methods: Mice orthotopically implanted with a patient-derived grade 3 endometrioid endometrial cancer organoid model (O-PDX) were allocated to chemotherapy (combined paclitaxel/carboplatin, n=11) or saline/control (n=13). During tumor progression, the mice underwent weekly T2-weighted (T2w) magnetic resonance imaging (MRI). Segmentation of primary tumor volume (vMRI) allowed extraction of radiomic features from whole-volume tumor masks. A radiomic model for predicting treatment response was derived employing least absolute shrinkage and selection operator (LASSO) statistics at endpoint images in the orthotopic O-PDX ( Results: The Conclusions: We have developed and validated a radiomic signature that was able to capture chemotherapeutic treatment response both in an O-PDX and in a subcutaneous endometrial cancer mouse model. This study supports the promising role of preclinical imaging including radiomic tumor profiling to assess early treatment response in endometrial cancer models.
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