With more axillary adenopathies likely to present on breast imaging, Society of Breast Imaging experts offer guidance for best management during the pandemic.
In response to evidence published last week in Clinical Imaging that the two approved COVID-19 vaccines can potentially lead to axillary adenopathies that can mimic breast malignancies, the Society of Breast Imaging (SBI) has published management guidelines for affected patients.
Although these adenopathies are rare on normal screening mammograms, appearing on 0.02 percent-to-0.04 percent of studies, SBI experts said, breast imagers need to be aware they will likely be more common in the coming months.
“As national vaccination efforts are underway, women with a recent COVID-19 vaccine may present for diagnostic workup for newly palpable axillary adenopathy or have new axillary adenopathy identified on routine screening mammography or ultrasound,” they said in a published statement, advising breast radiologists they will encounter more axillary adenopathies as vaccine rates increase.
Related Content: COVID-19 Vaccine-Linked Adenopathies Could Mimic Breast Malignancies
According the data from vaccine manufacturers Moderna and Pfizer-BioNTech, these adenopathies can occur in 11.6 percent of patients who receive the first-round vaccine dose and in 16 percent of those who receive the second dose. They appear within two-to-four days and can last for up to 10 days. Post-vaccine adenopathies that have appeared on mammography have, thus far, been unilateral.
To ensure that women undergoing breast imaging are properly managed during this time of the pandemic, the SBI offered five guidelines.
SBI experts cautioned that guidance for assessing and managing these axillary adenopathies could be subject to changes as more information about the COVID-19 vaccines become available. Recommendations for other vaccines will also be incorporated as they are approved for use.
For more coverage based on industry expert insights and research, subscribe to the Diagnostic Imaging e-Newsletter here.
Study: AI Boosts Ultrasound AUC for Predicting Thyroid Malignancy Risk by 34 Percent Over TI-RADS
February 17th 2025In a study involving assessment of over 1,000 thyroid nodules, researchers found the machine learning model led to substantial increases in sensitivity and specificity for estimating the risk of thyroid malignancy over traditional TI-RADS and guidelines from the American Thyroid Association.
Study: AI Boosts Ultrasound AUC for Predicting Thyroid Malignancy Risk by 34 Percent Over TI-RADS
February 17th 2025In a study involving assessment of over 1,000 thyroid nodules, researchers found the machine learning model led to substantial increases in sensitivity and specificity for estimating the risk of thyroid malignancy over traditional TI-RADS and guidelines from the American Thyroid Association.
2 Commerce Drive
Cranbury, NJ 08512