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September 17, 2025

New biomarkers’ exploration with multiparametric MRI for predicting pathological response to neoadjuvant chemotherapy in breast cancer

Key Points

A predictive model combining MRI parameters and clinical data shows strong potential for identifying pCR.
The analysis involved 692 patients and utilized logistic regression to establish predictive accuracy.
Key imaging biomarkers identified include rimed enhancement pre-NAC, tumor size, and ADC post-NAC.
This reliable model may improve treatment strategies and outcomes for patients undergoing neoadjuvant chemotherapy.

Abstract

Motivation: Accurate prediction of pathological completed response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer. Goal(s): Evaluate the value of potential MRI biomarkers for predicting pCR and establish a new nomogram to improve predictive performance. Approach: We conducted an analysis of 692 patients, utilizing univariable and multivariable logistic regression analyses, and training/validation cohorts for model development and validation. Results: Our newly developed model, combining the selected MRI parameters, hormone receptor (HR) and Ki67 index, exhibited strong predictive power, and also identified the rimed enhancement pre-NAC, and tumor size, wash-in slope, and ADC after NAC as significant imaging biomarkers of pCR. Impact: The impact of this study is significant, as it enhances breast cancer treatment by providing a reliable predictive model for neoadjuvant chemotherapy response, potentially improving patient outcomes and treatment strategies.

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Cite This Study

Li et al. (Tue,) studied this question.

synapsesocial.com/papers/68d45b0b31b076d99fa5d0af https://doi.org/https://doi.org/10.58530/2025/2004

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