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Abstract #1047

Novel MRI-based Hyper-Fused Radiomics for Predicting Pathologic Complete Response to Neoadjuvant Therapy in Breast Cancer

Quanxiang Cui1, LiangQin Zhou1, XinYi Wang1, Haonan Guan2, and Zixiang Kuai1
1Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China, 2MR Research China, GE Healthcare, Beijing, China

Synopsis

Keywords: Radiomics, Analysis/Processing, Hyper-Fused Radiomics, Neoadjuvant Therapy, Breast Cancer

Motivation: Predicting pathologic complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer (BC) is essential for personalized treatment planning.

Goal(s): This study aimed to enhance predictive accuracy of MRI-based radiomics by developing a hyper-fused radiomic model.

Approach: Hyper-fused radiomic features were extracted by combining voxel-wise data from multiple MRI parametric volumes, transformed into spherical coordinates for more comprehensive analysis.

Results: The hyper-fused model demonstrated higher predictive performance compared to conventional methods, with greater AUCs and robust associations with pCR, validated in an external test set.

Impact: This research highlights hyper-fused radiomics as a promising tool in precision oncology, potentially replacing contrast-based imaging for patients with contraindications and advancing predictive accuracy in therapy response.

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