Accuracy of shear-wave elastography in diagnosing severity of breast cancer–related lymphedema

Abstract

Introduction:

Up to 30% of breast cancer patients develop breast cancer–related lymphedema. Accurate staging is crucial for treatment selection. We aimed to evaluate the diagnostic accuracy of shear-wave elastography in differentiating International Society of Lymphology stage 1 from stage 2 breast cancer–related lymphedema through tissue stiffness quantification.

Methods:

From September 2024 to February 2025, this cross-sectional study included 120 unilateral breast cancer–related lymphedema patients (60 stage 1 and 60 stage 2) who underwent shear-wave elastography using an Acuson S3000 system. Shear-wave velocity (m/s) was measured in cutaneous/subcutaneous tissues of the forearm and upper arm. Staging followed International Society of Lymphology 2020 criteria, integrating clinical assessment, arm circumference difference (⩾2 cm indicative of stage 2), and bioimpedance spectroscopy (absolute value of the L-Dex score ⩾10 indicative of stage 2). Diagnostic performance was analysed via receiver operating characteristic curves, with the optimal shear-wave velocity cutoff determined by the Youden index.

Results:

Forearm cutaneous shear-wave velocity was significantly higher in stage 2 versus stage 1 (2.03 ± 0.25 m/s vs. 1.74 ± 0.17 m/s; p < 0.001). No significant differences were observed in forearm subcutaneous, arm cutaneous, or arm subcutaneous tissues (p = 0.063, p = 0.194, and p = 0.412, respectively). Receiver operating characteristic analysis for forearm cutaneous shear-wave velocity yielded an area under the curve of 0.80. At the optimal cut-off of 1.90 m/s, sensitivity was 76.7% and specificity was 71.7%.

Conclusion:

Shear-wave elastography–derived forearm cutaneous shear-wave velocity provides an objective biomarker for distinguishing International Society of Lymphology stage 1 and 2 breast cancer–related lymphedema, with good diagnostic accuracy. However, stiffness differences were not observed across all measured regions/layers. This non-invasive technique may guide personalised antifibrotic therapy by identifying advanced fibrosis.