Spatial habitats features derived from IVIM for the HER2 status prediction of breast cancer: a preliminary study

Motivation: Besides immunohistochemistry, a non-invasive method based on tumor habitats is worth exploring. It predicted the expression of HER2 factor in malignant breast cancer. Goal(s): We determined whether a prediction model, which was based on tumors habitats, could be used to predict the expression of HER2 factor. Approach: A predictive model based on tumors habitats was developed and used to diagnose HER2 status. The IVIM-based imaging technique could extract features. Results: The model of tumor habitats predicted the expression of HER2 factor in breast cancer by using the following parameters: AUC of 0.902, sensitivity of 0.709, and specificity of 0.909. Impact: In this experiment, a predictive model based on features of habitats could determine the expression of HER2 factor in patients with malignant breast cancer. Thus, this non-invasive approach is a better treatment option in clinical practice.