Added Value of Shear Wave Elastography for Noninvasive Detection of Axillary Lymph Node Metastasis and IHC-Defined Surrogate Subtype Characterization in Breast Cancer

Background: Accurate preoperative characterization of axillary lymph nodes (ALNs) is important in breast cancer, but conventional ultrasound has variable diagnostic performance. We evaluated quantitative shear wave elastography (SWE) for distinguishing reactive from metastatic ALNs, and we explored associations between nodal SWE parameters, breast cancer subtypes, and histological grades. Methods: We prospectively enrolled women with suspicious breast lesions and ALNs identified by clinical ultrasound who were scheduled for biopsy. After exclusions, 141 patients (57 reactive and 84 metastatic ALNs) were included. ElasticNet-regularized logistic regression with nested cross-validation compared clinical ultrasound alone with ultrasound plus SWE. Among 70 patients with metastatic ALNs and immunohistochemical characterization, SWE parameters were compared across surrogate subtypes and histological grades using Kruskal–Wallis tests with Holm adjustments. Results: The combined ultrasound–SWE model achieved an area under the receiver operating characteristic curve of 0.911 (95% CI, 0.859–0.961) compared to 0.798 (95% CI, 0.723–0.873) for ultrasound alone. At the Youden-derived threshold, the combined model achieved 88.1% sensitivity, 82.5% specificity, and 85.8% accuracy. Among metastatic ALNs, SWE parameters, namely Vmean, Vsd, and Vmax, differed significantly across surrogate subtypes, with the most pronounced differences observed between Luminal A and Luminal B tumors, (p = 0.0250, p = 0.0069, and p = 0.0065). No statistically significant differences were detected with histological grades in the five SWE parameters. Conclusions: Quantitative SWE complemented conventional ultrasound for assessing axillary nodal metastasis, with higher cross-validated discrimination for the combined model. Exploratory analyses identified differences in several SWE stiffness metrics between Luminal A and Luminal B tumors; these subtype-associated biomechanical differences require validation in larger cohorts.

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Journal
Cancers
Published
2026-11-04
DOI
https://doi.org/10.3390/cancers18213549
Primary Topic
Ultrasound Imaging and Elastography
Type
article
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article

Added Value of Shear Wave Elastography for Noninvasive Detection of Axillary Lymph Node Metastasis and IHC-Defined Surrogate Subtype Characterization in Breast Cancer

Nicholas Bradley Larson, Robert T. Fazzio, Azra Alizad, David Rosen et al.
Cancers
Ultrasound Imaging and Elastography
article

Added Value of Shear Wave Elastography for Noninvasive Detection of Axillary Lymph Node Metastasis and IHC-Defined Surrogate Subtype Characterization in Breast Cancer

Nicholas Bradley Larson, Robert T. Fazzio, Azra Alizad, David Rosen, Mostafa Fatemi, Tanin Adl Parvar, Jie Chen
article en

Abstract

Background: Accurate preoperative characterization of axillary lymph nodes (ALNs) is important in breast cancer, but conventional ultrasound has variable diagnostic performance. We evaluated quantitative shear wave elastography (SWE) for distinguishing reactive from metastatic ALNs, and we explored associations between nodal SWE parameters, breast cancer subtypes, and histological grades. Methods: We prospectively enrolled women with suspicious breast lesions and ALNs identified by clinical ultrasound who were scheduled for biopsy. After exclusions, 141 patients (57 reactive and 84 metastatic ALNs) were included. ElasticNet-regularized logistic regression with nested cross-validation compared clinical ultrasound alone with ultrasound plus SWE. Among 70 patients with metastatic ALNs and immunohistochemical characterization, SWE parameters were compared across surrogate subtypes and histological grades using Kruskal–Wallis tests with Holm adjustments. Results: The combined ultrasound–SWE model achieved an area under the receiver operating characteristic curve of 0.911 (95% CI, 0.859–0.961) compared to 0.798 (95% CI, 0.723–0.873) for ultrasound alone. At the Youden-derived threshold, the combined model achieved 88.1% sensitivity, 82.5% specificity, and 85.8% accuracy. Among metastatic ALNs, SWE parameters, namely Vmean, Vsd, and Vmax, differed significantly across surrogate subtypes, with the most pronounced differences observed between Luminal A and Luminal B tumors, (p = 0.0250, p = 0.0069, and p = 0.0065). No statistically significant differences were detected with histological grades in the five SWE parameters. Conclusions: Quantitative SWE complemented conventional ultrasound for assessing axillary nodal metastasis, with higher cross-validated discrimination for the combined model. Exploratory analyses identified differences in several SWE stiffness metrics between Luminal A and Luminal B tumors; these subtype-associated biomechanical differences require validation in larger cohorts.

CancersVol. 18(21)
Mayo Clinic (US)
Openalex Percentile: Top 14%
Ultrasound Imaging and Elastography
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