Prediction of Lymphovascular Space Invasion in endometrial cancer using MRI-based radiomics models

Motivation: Predicting LVSI before surgery remains a critical challenge. Goal(s): To predict preoperative LVSI in patients with endometrial cancer in a noninvasive way. Approach: We developed and validated MRI radiomics and clinical-radiomics models based on the features extracted from tumor and peritumoral regions. Results: The clinical-radiomics model based on the features extracted from the tumors with 3mm peritumoral region exhibited the hightest predictive performance in the training cohort and testing cohort with an AUC of 0.86 and 0.86, respectively. The model also displayed clinical validity as depicted in the DCA curve. Impact: Incorporating the radiomics features extracted from tumor with 3mm peritumoral region and clinical significance factors can improve the predictive efficacy of the model for predicting LVSI and increase its applicability in clinical practice.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/0862
Primary Topic
MRI in cancer diagnosis
Type
article
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article

Prediction of Lymphovascular Space Invasion in endometrial cancer using MRI-based radiomics models

C Yang, Jin-yuan Liao, Xiaoli Huang, Lan-hui Qin et al.
1 links
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
MRI in cancer diagnosis
article

Prediction of Lymphovascular Space Invasion in endometrial cancer using MRI-based radiomics models

C Yang, Jin-yuan Liao, Xiaoli Huang, Lan-hui Qin, Kan Deng, Lü Chen
article en

Abstract

Motivation: Predicting LVSI before surgery remains a critical challenge. Goal(s): To predict preoperative LVSI in patients with endometrial cancer in a noninvasive way. Approach: We developed and validated MRI radiomics and clinical-radiomics models based on the features extracted from tumor and peritumoral regions. Results: The clinical-radiomics model based on the features extracted from the tumors with 3mm peritumoral region exhibited the hightest predictive performance in the training cohort and testing cohort with an AUC of 0.86 and 0.86, respectively. The model also displayed clinical validity as depicted in the DCA curve. Impact: Incorporating the radiomics features extracted from tumor with 3mm peritumoral region and clinical significance factors can improve the predictive efficacy of the model for predicting LVSI and increase its applicability in clinical practice.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Good health and well-being
Openalex Percentile: Top 64%
MRI in cancer diagnosis
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