Radiomics is an emerging translational field of medicine based on the extraction of high-
dimensional data from radiological images, with the purpose to reach reliable models to be …

The significance of metastatic lymph nodes in tumor diagnosis and prognosis is self-evident.
With the deepening of research on the lymphatic system and the advancement of imaging …

Purpose To develop a nomogram based on radiomics signature and deep-learning
signature for predicting the axillary lymph node (ALN) metastasis in breast cancer. Methods …

Background Multiparametric magnetic resonance imaging (MRI) is widely used in breast
cancer screening. Accurate prediction of the axillary lymph nodes metastasis (ALNM) is …

Background Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer
patients is essential for prognosis and treatment planning. Current radiological staging of …

The objective of this study is to develop a radiomic signature constructed from deep learning
features and a nomogram for prediction of axillary lymph node metastasis (ALNM) in breast …

Purpose To develop and validate a radiomics nomogram based on T2-weighted imaging
(T2WI) and apparent diffusion coefficient (ADC) features for the preoperative prediction of …

Purpose The purpose of this study was to assess the clinical value of conventional magnetic
resonance imaging (MRI) and intravoxel incoherent motion (IVIM) features for predicting the …

Rationale and Objectives This multicenter study aimed to explore the feasibility of radiomics
based on intra-and peritumoral regions on preoperative breast cancer contrast-enhanced …

Lymph node involvement increases the risk of breast cancer recurrence. An accurate non-
invasive assessment of nodal involvement is valuable in cancer staging, surgical risk, and …