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Abstract #0407

Early Prediction of Treatment Response in HER2-Positive Breast Cancer Using multiparametric MRI

Siyi Chen1, Wenjie Tang1, Yuan Guo1, Zhidan Zhong1, Yongzhou Xu2, Lu Han3, and Xinhua Wei1
1Department of Radiology, Guangzhou First People's Hospital, Guangzhou, China, 2Philips Healthcare, Guangzhou, China, 3Philips Healthcare, Shanghai, China

Synopsis

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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