What question did this study set out to answer?

The study aims to determine if breast edema scores from MRI can predict lymphovascular invasion in breast cancer patients before surgery.

February 17, 2026Open Access

Preoperative Prediction of Fat-Suppressed T2-Weighted Imaging-based Breast Edema Scores for Lymphovascular Invasion in Patients with Breast Cancer

Key Points

The study aims to determine if breast edema scores from MRI can predict lymphovascular invasion in breast cancer patients before surgery.
Retrospective cohort of 574 breast cancer patients undergoing MRI and surgery from 2021 to 2023.
Patients classified as LVI-positive or LVI-negative based on postoperative pathology findings.
Breast edema was scored using fat-suppressed T2-weighted imaging, ranging from no edema to subcutaneous edema.
Binary logistic regression analyses identified independent risk factors for LVI.
Breast edema scores were significant predictors of LVI, with higher scores indicating increased risk.
Scores of BES 2, BES 3, and BES 4 showed increased LVI risks of 1.825, 2.047, and 4.341 times, respectively.
The combined model of BES and clinicopathological features had a better predictive performance than clinicopathological factors alone.

Abstract

Introduction: Lymphovascular invasion (LVI) is a critical prognostic factor in breast cancer, typically diagnosed via postoperative pathology. This study aimed to evaluate whether fat-suppressed T2-weighted imaging (FS T2WI)-based breast edema score (BES) combined with clinicopathological features could preoperatively predict LVI status. Materials and Methods: This retrospective study enrolled 574 breast cancer patients who underwent MRI and surgery from January 2021 to December 2023. Patients were classified as LVI-positive (n=174) or LVI-negative (n=400) based on postoperative pathology. Breast edema on FS T2WI was scored from 1 to 4 (BES 1, no edema; BES 2, peritumoral edema; BES 3, prepectoral edema; and BES 4, subcutaneous edema). Univariate and multivariate binary logistic regression analyses were performed to identify risk factors associated with LVI. A clinicopathological model and a combined BES–clinicopathological model were constructed, and diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC) and the DeLong test. Results: Multivariate analysis revealed that BES and clinicopathological factors, including age, axillary lymph node metastasis, and tumor size, were independent predictors of LVI. Compared with BES 1, tumors with BES 2, BES 3, and BES 4 were associated with a 1.825-, 2.047-, and 4.341- fold increased LVI risk, respectively. The combined BES–clinicopathological model outperformed the clinicopathological model alone (AUC, 0.765 vs. 0.778; P< 0.05). Discussion: Higher BES was independently associated with increased LVI risk. The predictive model integrating BES with clinicopathological variables outperformed single-parameter models, suggesting that BES may provide complementary imaging biomarkers for assessing tumor aggressiveness. Validation in larger, multicenter cohorts is warranted. Conclusion: FS T2WI-based BES combined with clinicopathological features may improve preoperative prediction of LVI in breast cancer and support individualized treatment planning.

Preoperative Prediction of Fat-Suppressed T2-Weighted Imaging-based Breast Edema Scores for Lymphovascular Invasion in Patients with Breast Cancer

Key Points

Abstract

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