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Abstract #1557

The Role of Multiparametric MRI Radiomics in Predicting Axillary Lymph Node Metastasis in Invasive Breast Cancer Patients: A Comparative Study

Yongxin Chen1, Yuan Guo1, Wenjie Tang1, Siyi Chen1, Qingcong Kong2, Yongzhou Xu3, and Xinqing Jiang1
1Guangzhou First People's Hospital, Guangzhou, China, 2The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China, 3Philips Healthcare, Guangzhou, China

Synopsis

Keywords: Diagnosis/Prediction, Radiomics

Motivation: The predictive value of different MRI sequences for axillary lymph node metastasis (ALNM) in invasive breast cancer patients remains uncertain.

Goal(s): To compare and assess the performance of individual and combined MRI sequences in preoperatively predicting ALNM status in invasive breast cancer patients.

Approach: Three single-sequence models and four multi-sequence models based on multiparametric MRI radiomics were constructed, and their performances were compared using the DeLong test. The optimal radiomics model was then used to create a nomogram incorporating the significant clinicopathologic features.

Results: The multi-sequence models outperform the single-sequence models, with dynamic contrast-enhanced imaging showing greater stability among the single-sequence models.

Impact: The comparative analysis identified the optimal combination of MRI sequences that can enhance the accuracy of preoperative ALNM status prediction in invasive breast cancer patients, potentially enabling the personalization of axillary treatment strategies.

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