Preoperative prediction of sentinel lymph node metastasis in breast cancer based on radiomics of T2-weighted fat-suppression and diffusion-weighted MRI.
Yuhao DongQianjin FengWei YangZixiao LuChunyan DengLu ZhangZhouyang LianJing LiuXiaoning LuoShufang PeiXiaokai MoWenhui HuangChanghong LiangBin ZhangShuixing ZhangPublished in: European radiology (2017)
• SLN biopsy to access breast cancer metastasis has multiple complications. • Radiomics uses features extracted from medical images to characterise intratumour heterogeneity. • We combined T 2 -FS and DWI textural features to predict SLN metastasis non-invasively.
Keyphrases
- contrast enhanced
- diffusion weighted
- sentinel lymph node
- magnetic resonance imaging
- diffusion weighted imaging
- magnetic resonance
- computed tomography
- early stage
- lymph node
- neoadjuvant chemotherapy
- deep learning
- adipose tissue
- patients undergoing
- squamous cell carcinoma
- ultrasound guided
- convolutional neural network
- lymph node metastasis
- optical coherence tomography
- machine learning
- fine needle aspiration
- fatty acid