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Abstract #1550

Research on Predicting the Efficacy of NAC in Breast Cancer Based on a Multisequence MRI Intratumoral Combined Peritumoral Radiomics Model

Xinyi Liu1, Yuntai Cao1, Airu Yang1, and Mingtai Cao1
1Qinghai University Affiliated Hospital, Xining, China

Synopsis

Keywords: AI Diffusion Models, Breast, cancer

Motivation: Currently, studies on the efficacy of neoadjuvant chemotherapy (NAC) in breast cancer primarily focus on the internal regions of the lesion. There are fewer studies on the surrounding regions of the tumor, and most of them use single sequences for analysis.

Goal(s): This study aims to assess the efficacy of NAC for breast cancer before treatment, providing personalized treatment plans for patients.

Approach: Extract radiomics features from the intratumoral and peritumoral regions of breast cancer patients from three centers, construct radiomics models, and select the optimal model.

Results: This study can effectively predict the efficacy of NAC in breast cancer.

Impact: This study contributes to improving the level of breast cancer diagnosis and treatment.

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Keywords