Abstract

Abstract Background: Axillary lymph node metastasis is a vital factor of prognosis in patients with invasive breast cancer. However, sensitivity and noninvasive for prediction of lymph node metastasis and survival after neoadjuvant chemotherapy is limited. This study aims to develop radiomics combining multi-parametric MRI before and after neoadjuvant chemotherapy to predict axillary lymph node metastasis and prognosis, as well as investigate the relationship between the radiomics and tumor microenvironment in invasive breast- cancer. Methods: RBC-02 is a multicenter, ambispective cohort study proposes to build a clinical predictive model to predict axillary lymph node metastasis and prognosis in invasive-breast- cancer patients who received neoadjuvant chemotherapy. Patients are recruited from Sun Yat-sen Memorial Hospital of Sun Yat-sen University (training cohort), Sun Yat-sen University Cancer Center (validation cohort), and Tungwah hospital of Sun Yat-sen University (validation cohort) in China. Invasive breast cancer patients undergo multi-parametric MRI at baseline, then undergo multi-parametric MRI after received neoadjuvant chemotherapy for at least 4 cycles as planned. After the surgery, responses to neoadjuvant chemotherapy are determined according to the histopathologically examination of the surgically resected specimens. The model is built based on breast MRI signatures extracted and analyzed via deep machine- learning algorithm methods. The correlation between radiomics features and tumor microenvironment is also planned to investigate. Decision curve analysis was performed with the combined training and validation set to estimate the clinical usefulness of the radiomics nomogram, which is built with a multivariate logistic regression model. The primary endpoint is disease-free survival. Secondary endpoints include pathological complete response, pathological axillary lymph node status, and overall survival. The trial is registered with ClinicalTrials.gov, number NCT04004559, and Chinese Clinical Trail Registry, number ChiCTR1900024113. Citation Format: Herui Yao, ChenChen Li, Yunfang Yu, Chuanmiao Xie, Jie Ouyang, Yujie Tan, Nian Lu, Ying Wang, Jianli Zhao, Kai Chen, Jiafan Ma. Radiomics multi-parametric MRI of before and after neoadjuvant chemotherapy associated with axillary lymph node metastasis and prognostic in patients with breast cancer: A multicenter RBC-002 study [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr OT3-02-03.

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