Sub-regional Tumor Segmentation Based on CEUS Perfusion Characteristics: Enhancing Breast Tumor Diagnosis

The goal of this study is to investigate breast cancer's internal heterogeneity and enhance diagnostic accuracy. The investigators aim to achieve this by utilizing Contrast-Enhanced Ultrasound (CEUS) technology, which provides detailed information about tumor perfusion dynamics. Traditional biopsy methods have limitations due to the invasive nature and complexity of breast cancer heterogeneity. Participants in this study will undergo preoperative breast cancer diagnosis using CEUS technology, which is safe, cost-effective, and convenient. Dynamic CEUS videos will be used to cluster perfusion characteristics at the pixel level within breast tumors, allowing the investigators to divide the tumors into distinct subregions based on these clusters. The investigators will then explore the correlation between these perfusion subregions and the diagnosis of benign or malignant breast tumors. The ultimate aim is to develop diagnostic models that utilize non-invasive imaging data to enhance breast cancer diagnosis. This approach reduces subjective judgments in the diagnostic process, potentially improving diagnostic accuracy. It also provides valuable information for personalized treatment decisions, thus advancing the field of breast cancer treatment.