Imaging of COVID-19 Vaccine-Related Axillary Lymphadenopathy: Initial Outcomes Based on US Features of Axillary Lymph Nodes

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Abstract

Objective: The purpose of this study is to describe the imaging characteristics and outcomes of COVID-19 vaccine-related axillary adenopathy and subsequent follow-up. Methods: This was an IRB-approved, retrospective study of patients with imaging evidence of axillary lymphadenopathy who had received at least one dose of a COVID-19 vaccine and presented between January 1, 2021, and February 28, 2021. Sonographic cortical thickness and morphology was evaluated. A mixed effects model was used to model lymph node cortical thickness decrease over time. Results: A total of 57 women were identified with lymphadenopathy and a COVID vaccination during the study period with 51 (89.5%) women completing imaging surveillance or undergoing tissue sampling of a lymph node. Three women (5.9%) were diagnosed with metastatic breast cancer to an axillary node. There was a statistically significant correlation with cortical thickness at initial US evaluation and malignancy (7.7 mm [SD ± 0.6 mm] for metastatic nodes and 5 mm [SD ± 2 mm] for benign nodes, P = 0.02). Suspicious morphological features (effacement of fatty hilum, P = 0.02) also correlated with malignancy. Time to resolution of lymphadenopathy can be prolonged with estimated half-life of the rate of decrease in cortical thickness modeled at 77 days (95% CI, 59-112 days). Diffuse, smooth cortical thickening over 3 mm was the most common lymph node morphology. Conclusion: Malignant lymph node morphology and cortical thickness best predicted malignancy. Benign hyperplastic lymph nodes were the most common morphology observed after COVID-19 vaccination. Lymphadenopathy after vaccination is slow to resolve.

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APA

Ahn, R. W., Porembka, J. H., Mootz, A. R., Goudreau, S. H., Dogan, B. E., Xi, Y., & Seiler, S. J. (2023). Imaging of COVID-19 Vaccine-Related Axillary Lymphadenopathy: Initial Outcomes Based on US Features of Axillary Lymph Nodes. Journal of Breast Imaging, 5(2), 135–147. https://doi.org/10.1093/jbi/wbac091

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