Predicting estrogen receptor factor expression based on tumor habitats in patients with malignant breast cancer: a feasibility study

Motivation: Immunohistochemistry remains the gold standard for diagnosing the estrogen receptor (ER) factor in breast cancer. However, the non-invasive IVIM radiomics method offers a meaningful alternative for predicting ER expression. Goal(s): The objective of this study is to assess the feasibility and performance of a prediction model based on tumors habitats in predicting ER expression in malignant breast cancer patients. Approach: We developed and evaluated a predictive model that utilizes tumors habitats to diagnose ER expression. Results: The IVIM indicators can be employed for tumor subregions’ segmentation to hypoxia. The model demonstrates effective prediction capabilities for determining the probability of ER-positive in breast cancer. Impact: Our research highlights the excellent performance of the predictive model based on tumors habitats in predicting ER expression in breast cancer. The model can aid clinicians in making more informed treatment decisions and subsequently improve patient outcomes.