An integrated radiomics and deep learning model on multisequence MRI for preoperative prediction of lymphovascular space invasion in endometrial cancer

Hong-Jian Luo; Jin Cheng; Guo Li; Jinliang Niu; Xiaoli Song

doi:10.1186/s12880-025-02091-4

December 8, 2025BMC Medical ImagingOpen Access

An integrated radiomics and deep learning model on multisequence MRI for preoperative prediction of lymphovascular space invasion in endometrial cancer

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Key Points

Model predicts lymphovascular space invasion, improving patient management.
Integrating deep learning with MRI enhances prediction accuracy for endometrial cancer.
Assessment utilizing a multimodal MRI-based approach assists in personalized treatment planning.
This model supports preoperative risk adjustment for patients with endometrial cancer.

Implication

Model predicts lymphovascular space invasion in endometrial cancer, suggesting enhanced preoperative risk stratification.

Abstract

A multimodal MRI-based model integrating both RFs and DFs achieved superior performance for noninvasive prediction of LVSI in patients with EC. This approach holds potential to enhance preoperative risk stratification and guide personalized treatment planning.

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Cite This Study

Luo et al. (2025) studied this question.

synapsesocial.com/papers/69401f142d562116f28fa61d https://doi.org/10.1186/s12880-025-02091-4

View Full Paper

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An integrated radiomics and deep learning model on multisequence MRI for preoperative prediction of lymphovascular space invasion in endometrial cancer

Key Points

Implication

Abstract

Discussion

Cite This Study

An integrated radiomics and deep learning model on multisequence MRI for preoperative prediction of lymphovascular space invasion in endometrial cancer

Key Points

Implication

Abstract

Discussion

Cite This Study

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