Multimodal radiomics for early prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer: integration of amide proton transfer weighted imaging in radiomics | Synapse
April 10, 2026Open Access
Multimodal radiomics for early prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer: integration of amide proton transfer weighted imaging in radiomics
Key Points
This research aims to enhance the prediction of treatment outcomes in breast cancer using a multimodal radiomics approach.
Developed a multimodal radiomics model integrating various imaging techniques.
Compared the effectiveness of this model against traditional single-modal imaging.
Analyzed biomarkers related to treatment response after neoadjuvant chemotherapy.
The multimodal model significantly improved prediction accuracy compared to single-modal approaches.
Early identification of patients likely to achieve a complete response was achieved.
Findings support personalized therapy choices to reduce unnecessary treatments.
Abstract
Compared to single-modal imaging, our multimodal radiomics model provides more comprehensive biomarkers, thereby enabling personalized therapeutic decisions and optimizing NAC regimens to reduce overtreatment.