Radiomics-Based Multiparametric MRI for Differentiating Luminal A and Luminal B Breast Cancer: A Multi-Center Study
Motivation: This study aims to improve the non-invasive classification of Luminal A and Luminal B breast cancer subtypes using a multiparametric radiomics model integrating T2WI, DWI, and DCE-MRI. Goal(s): The goal is to improve non-invasive breast cancer classification using a multiparametric radiomics model. Approach: This study analyzed T2WI, DWI, and DCE-MRI data from 130 patients, developing a model evaluated with AUC, DCA, and DeLong test. Results: The multiparametric model achieved AUCs of 0.9625, 0.8276, and 0.8750 in the training and test sets, outperforming single-sequence models in accuracy and clinical benefit. DeLong test confirmed significant differences, supporting the superior performance of the combined approach. Impact: This study enhances breast cancer diagnosis by providing a noninvasive method to differentiate Luminal A and Luminal B subtypes. This could potentially improve clinical decision-making and enable personalized treatment plans for patients.
Authors
- Wei Lin (ORCID: https://orcid.org/0000-0003-1718-3539)
- Xiaohui Liu (ORCID: https://orcid.org/0000-0002-7701-1205)
- Dawei Yang (ORCID: https://orcid.org/0000-0003-3313-6935)
- Hui Zhou (ORCID: https://orcid.org/0000-0002-4900-4294)
- Xiaodie Zeng (ORCID: https://orcid.org/0009-0000-8350-6303)
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
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/1985
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00