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Acad Radiol ; 29(7): 1004-1012, 2022 07.
Article in English | MEDLINE | ID: covidwho-1705736

ABSTRACT

RATIONALE AND OBJECTIVE: To identify nodal features used to distinguish coronavirus disease 2019 (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 messenger RNA 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% (area under the curve [AUC] = 0.60, 95% confidence interval [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).Cortical thickness correlated with nodal morphology type (r2 = 0.57). An axillary node with generalized lobulated cortical thickening had a 7.5 odds ratio and a node with focal cortical lobulation had a 123.0 odds ratio compared to one with diffuse, uniform cortical thickening only (p < 0.001). 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.


Subject(s)
Breast Neoplasms , COVID-19 , Lymphadenopathy , Axilla/pathology , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/pathology , COVID-19 Vaccines/adverse effects , Female , Humans , Lymph Nodes/diagnostic imaging , Lymph Nodes/pathology , Lymphadenopathy/diagnostic imaging , Lymphadenopathy/etiology , Retrospective Studies , Sensitivity and Specificity
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