Intravoxel incoherent motion-based habitat imaging for the prediction of immunohistochemistry in patients with breast cancer.

Background: To explore the value of intravoxel incoherent motion (IVIM)-based habitat imaging in predicting immunohistochemistry in patients with breast cancer.

Methods: 299 patients with suspected breast cancer were randomly assigned to a training set of 210 individuals and a test set of 89 individuals. A series of models was constructed for human epidermal growth factor receptor 2 (HER2)/Ki-67/hormone receptors (HR)/lymph node metastasis (LNM) prediction, including the whole-tumor model, habitat model, conventional MRI features (CF) model and hybrid model (incorporating habitats features and CF). The performance of various models was evaluated with the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). P (two-tailed) < 0.05 was considered statistically significant.

Results: On the test cohort, for HER2/HR/LNM, the habitats model achieved the highest AUC values of 0.692/0.651/0.722, higher than those of the whole-tumor model (AUC = 0.591/0.599/0.609) and the CF model (AUC = 0.598/0.603/0.608). For Ki-67, the CF model achieved a highest AUC of 0.746. The hybrid model achieved AUC values of 0.706/0.762/0.668/0.728 for HER2/Ki67/HR/LNM. DeLong test showed a significant difference between habitats model and the whole-tumor model for LNM ( = 0.006).

Conclusion: While habitat features can provide richer biological information, the models combining habitats and CF obtained more accurate results than other models, making them promising candidates for clinical application in breast cancer diagnosis.