Keywords: Breast, Breast, cancer, HER-2, multi-modality, intratumoral
Motivation: Understanding the prognostic factors in breast cancer is crucial for improving clinical diagnosis and treatment.
Goal(s): This study aims to evaluate the predictive value of multimodal MRI parameters for determining human epidermal growth factor receptor 2 (HER-2) status in breast cancer.
Approach: A retrospective analysis was conducted using multimodal MRI techniques, including DCE-MRI, MUSE-IVIM, IDEAL-IQ, and MAGiC, on patients diagnosed with breast cancer. Quantitative parameters were extracted and analyzed.
Results: Significant differences in MRI parameters between HER-2 positive and negative groups were found, with combined models showing high diagnostic performance (AUC=0.822) for predicting HER-2 expression.
Impact: This study’s findings could enhance non-invasive HER-2 status assessment in breast cancer, aiding clinicians in personalized treatment planning. It opens avenues for further research on multimodal MRI’s role in predicting other molecular characteristics, improving diagnostic precision.
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