# Early peritumoral edema change improve prediction of pathological complete response in breast cancer: a multiparametric magnetic resonance imaging-based model

## TL;DR

This study shows that early changes in peritumoral edema in breast cancer patients can improve predictions of treatment response to chemotherapy.

## Contribution

The study introduces a new MRI-based model that incorporates early peritumoral edema changes to enhance prediction of pathological complete response.

## Key findings

- Early peritumoral edema changes are an independent predictor of pathological complete response.
- Combining edema changes with MRI features improved predictive accuracy (AUC 0.899).
- The model outperformed conventional methods in both training and validation cohorts.

## Abstract

To evaluate the independent and additive predictive value of peritumoral edema for pathological complete response (pCR) following neoadjuvant chemotherapy (NAC) in patients with breast cancer.

Breast cancer patients who underwent NAC between February 2018 and December 2024 were retrospectively enrolled. Based on treatment response, patients were categorized into pCR and non-pCR groups. Clinicopathological characteristics, peritumoral edema, and changes in MRI features (pre-NAC and after two cycles of NAC) were compared between groups. Variables showing statistical significance were included in multivariate logistic regression to identify independent predictors. The additional contribution of edema to predictive performance was assessed using the DeLong test.

A total of 230 patients were included, of whom 96 achieved pCR. Multivariate analysis identified early changes in peritumoral edema, percentage change in apparent diffusion coefficient, percentage change in lesion diameter, and molecular subtype as independent predictors of pCR (P < 0.05). The integration of edema changes with conventional MRI features enhanced predictive accuracy (AUC improved from 0.816–0.844 to 0.851–0.880). A comprehensive prediction model incorporating molecular subtype and MRI features achieved the highest AUC values: 0.899 in the training cohort and 0.882 in the validation cohort.

A predictive model incorporating early peritumoral edema changes, apparent diffusion coefficient, lesion diameter, and molecular subtype achieved an AUC of 0.899, indicating robust predictive performance in predicting pCR among breast cancer patients undergoing NAC. This model may facilitate personalized treatment planning and clinical decision-making.