Purpose: This study aims to develop a non-invasive method to distinguish between luminal and non-luminal breast cancer subtypes using super-resolution ultrasound (SRUS). Currently, subtype classification requires a tissue biopsy, which is invasive and may not fully capture the tumor's biological heterogeneity.
Methods: The study retrospectively included 94 patients with histologically confirmed breast cancer who underwent SRUS imaging. Sixteen quantitative features of the tumor microvasculature-such as vessel density, blood flow intensity, and perfusion-were extracted. Three key predictors (fractional weighted vessel density, mean intensity, and perfusion index) were identified and combined into a predictive nomogram.
Goal: The goal is to provide clinicians with a non-invasive imaging tool that can help personalize treatment decisions for breast cancer patients before therapy initiation, potentially reducing the need for repeat biopsies.