Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study

ConclusionsThe proposed DLRP strategy holds promise for effectively predicting NAC response at its early stage for BC patients.Key Points• We proposed two novel deep learning radiomics (DLR) models to predict response to neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients based on US images at different NAC time points.• Combining two DLR models, a deep learning radiomics pipeline (DLRP) was proposed for stepwise prediction of response to NAC.• The DLRP may provide BC patients and physicians with an effective and feasible tool to predict response to NAC at an early stage and to determine further personalized treatment options.
Source: European Radiology - Category: Radiology Source Type: research