Objective : To identify nodal features used to distinguish COVID-19 vaccine-Induced benign reactive adenopathy from malignant adenopathy. Materials and Methods : This IRB-approved, single-institution, retrospective study compared features of 77… Click to show full abstract
Objective : To identify nodal features used to distinguish COVID-19 vaccine-Induced benign reactive adenopathy from malignant adenopathy. Materials and Methods : This IRB-approved, single-institution, retrospective study compared features of 77 consecutive patients with benign adenopathy secondary to a mRNA COVID-19 vaccine with 76 patients with biopsy-proven malignant adenopathy from breast cancer. Patient demographics and nodal features were compared between the two groups using univariate and multivariate logistic regression models. A receiver operating characteristic analysis with the maximum value of Youden's index was performed for the cutoff value of cortical thickness for predicting nodal status. Results : The mean cortical thickness was 5.1 mm +/- 2.8 mm among benign nodes and 8.9 mm +/- 4.5 mm among malignant nodes (p < 0.001). A cortical thickness ≥ 3.0 mm had a sensitivity of 100% and a specificity of 21% (AUC = 0.60, 95% CI: 0.52-0.68). When the cutoff for cortical thickness was increased to ≥ 5.4 mm, the sensitivity decreased to 74%, while the specificity increased to 69% (AUC = 0.77, 95% CI: 0.70-0.84). Conclusion : Cortical thickness and morphology are predictive of malignancy. Cortical thickness cutoff of ≥ 5.4 mm demonstrates higher specificity and improved accuracy for detecting malignant adenopathy than a cutoff of ≥ 3.0 mm.
               
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