What type of study is this?

This is a Cohort Study study (also classified as: Quantitative Study).

September 17, 2025

Preoperative Prediction of Pathological Complete Response in Breast Cancer Treated with Neoadjuvant Chemotherapy: A Longitudinal MRI Study

Key Points

Significant associations were found between clinical characteristics and pathological complete response, enhancing predictive accuracy.
The study involved 303 patients receiving neoadjuvant chemotherapy, highlighting the scale of the analysis and its implications for treatment.
Machine learning techniques, particularly XGBoost, were utilized to devise a predictive model using MRI data, indicating technological advancement in treatment prediction.
The proposed model offers a novel approach to personalize treatment plans for breast cancer patients based on MRI findings, improving clinical outcomes.

Abstract

Motivation: Currently, there are no standardized methods or imaging biomarkers available in clinical practice to accurately predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with non-mass enhancement breast cancer. Goal(s): Utilize longitudinal dynamic contrast-enhanced (DCE) MRI radiological features alongside clinical and pathological data to predict pCR in breast cancer patients. Approach: We retrospectively collected longitudinal MRI and clinical data from 303 patients undergoing NAC and utilized machine learning approaches for pCR prediction. Results: Our results showed significant associations between multiple radiological and clinical characteristics and pCR. The XGBoost machine learning models effectively predicted pCR in breast cancer. Impact: We proposed a novel model based on longitudinal MRI data to predict pCR to NAC in breast cancer, including both mass and non-mass enhancement lesions, to inform personalized clinical treatment plans.

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Cite This Study

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

synapsesocial.com/papers/68d4597031b076d99fa5c606 https://doi.org/https://doi.org/10.58530/2025/1977

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