Keywords: Breast, Breast, Synthetic MRI; Apparent diffusion coefficient; Breast cancer; Radiomics; Neoadjuvant chemotherapy
Motivation: Contrast-free sequences are receiving increasing attention. As a novel technology, radiomics analysis of synthetic MRI (SyMRI) in breast treatment has not been widely explored.
Goal(s): To investigate the radiomics features extracted from the contrast-free SyMRI and apparent diffusion coefficient (ADC) in predicting pathological complete response in breast cancer.
Approach: The support vector machine-based recursive feature elimination (SVM-RFE) was used to build models. The model performance was assessed by receiver operating characteristic curve and compared by Delong test.
Results: Radiomics model based on delta-SyT2 and 1st-ADC achieved the optimal performance after one cycle treatment. After adding receptor status, the clinical-radiomics achieved the highest performance.
Impact: Multiparametric SyMRI and ADC, as noncontrast sequences, have the potential to early predict NAC response in radiomics analysis, thus reducing the need for repeated contrast agent injections during treatment.
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