Research progress of radiomics and deep learning in predicting axillary lymph node metastasis in breast cancer
Breast cancer is one of the most prevalent malignant tumors in women,and the status of axillary lymph nodes plays a decisive role in clinical staging,treatment decision-making,and prognosis of the tumor.Sentinel lymph node biopsy and axillary lymph node dissection are currently the gold standards for evaluating the status of axillary lymph nodes,but both are invasive procedures with various postoperative complications.Therefore,preoperative non-invasive assessment of axillary lymph nodes status is crucial for clinical treatment decision-making.Radiomics and deep learning techniques predict the biological behavior of tumors by extracting high-throughput radiomics features,characterized by reproducibility,non-invasiveness,and objectivity.They have been widely used in the diagnosis of breast cancer,evaluation of lymph node metastasis,and prognosis assessment.This article summarizes the research progress of radiomics and deep learning techniques based on digital mammography and MRI in predicting axillary lymph node metastasis in breast cancer,aiming to provide new ideas for clinical individualized precision medicine.
breast canceraxillary lymph nodemagnetic resonance imagingdigital mammographyradiomicsdeep learning
万方数据
维普
