MRI-based radiomic and machine learning for prediction of lymphovascular invasion status in breast cancer.

Objective: Lymphovascular invasion (LVI) is critical for the effective treatment and prognosis of breast cancer (BC). This study aimed to investigate the value of eight machine learning models based on MRI radiomic features for the preoperative prediction of LVI status in BC.

Methods: A total of 454 patients with BC with known LVI status who underwent breast MRI were enrolled and randomly assigned to the training and validation sets at a ratio of 7:3.

Structure and activity alteration in adult highland residents' cerebrum: Voxel-based morphometry and amplitude of low-frequency fluctuation study.

Introduction: People living in highland areas may have factors that allow them to adapt to chronic hypoxia, but these physiological mechanisms remain unclear. This study aimed to investigate the brain mechanism in a cohort of adult residents of Tibet, a well-known plateau section in China, by observing differences in brain structure and function in non-plateau populations.

Methods: The study included 27 Tibetan and 27 non-plateau region residents who were matched in age, sex, and education.