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This study is aimed to illustrate whether Radiomics combining multiparametric MRI before and after neoadjuvant chemotherapy (NACT) with clinical data is a good way to predict axillary lymph node metastasis and prognosis in invasive-breast-cancer.
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This 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 before surgery. The model is built based on breast MRI signatures extracted and analyzed via deep machine-learning algorithm methods. Invasive breast cancer patients undergo multiparametric MRI at baseline, then undergo multiparametric 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. After completion of treatment procedure, patients are followed up for 5 years.
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600 participants in 3 patient groups
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Yunfang Yu, MD; Herui Yao, Ph. D
Data sourced from clinicaltrials.gov
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