Keywords: Breast, Tumor, multiparametric MRI, neoadjuvant chemotherapy (NAC), HER2-positive breast cancer
Motivation: Imaging pre- and post- neoadjuvant chemotherapy (NAC) fails to adequately capture and quantify temporal heterogeneity and biological changes of tumors.
Goal(s): To assess if longitudinal changes in multiparametric MRI can predict early response to neoadjuvant chemotherapy (NAC) in HER2-positive breast cancer and to establish quantitative models based on these features.
Approach: Two predictive models were developed, one based on clinicopathologic features and another that combined clinicopathologic and MRI features.
Results: The combined model performs optimally in all datasets. Changes observed in multiparametric MRI can predict early treatment responses in HER2-positive BC and assist in tailoring personalized treatment plans.
Impact: The prediction model was simple and feasible, which was helpful for individualized treatment planning.
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