Keywords: Breast, Radiomics, Breast Cancer, Molecular Receptors Status, Feature Fusion Radiomics Model
Motivation: Investigating the performance of a feature fusion radiomics (RFF) strategy that mimicked the routine diagnostic practices of radiologists in distinguishing different statuses of molecular receptors in breast cancer (BC) preoperatively.
Goal(s): Develop an RFF model that incorporates optimal mpMRIs for BC’s molecular receptor status identification.
Approach: Constructed and analyzed 150 models to determine the top four optimum sequences for identifying distinct BC’s molecular receptor statuses. Then the optimal single sequence models (Rss) and combined sequences models (RFF) were developed and compared.
Results: The RFF model integrating mpMRI radiomics features exhibited promising ability to imitate radiologists’ diagnosis for preoperative identification of BC’s molecular receptors.
Impact: A multiparametric MR-based RFF model, mimicking the radiologists’ daily diagnostic approach, which fused radiomics features with dominant MR sequences, was able to distinguish different molecular receptor statuses of breast cancer.
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