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Ultrasound Features to Differentiate COVID-19 Vaccine-Induced Benign Adenopathy from Breast Cancer Related Malignant Adenopathy
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 pati...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Association Of University Radiologists
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8858693/ https://www.ncbi.nlm.nih.gov/pubmed/35296413 http://dx.doi.org/10.1016/j.acra.2022.02.015 |
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author | HL, Chung GJ, Whitman JWT, Leung J, Sun LP, Middleton HT, Le-Petross |
author_facet | HL, Chung GJ, Whitman JWT, Leung J, Sun LP, Middleton HT, Le-Petross |
author_sort | HL, Chung |
collection | PubMed |
description | 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 (r(2) = 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. |
format | Online Article Text |
id | pubmed-8858693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Association Of University Radiologists |
record_format | MEDLINE/PubMed |
spelling | pubmed-88586932022-02-22 Ultrasound Features to Differentiate COVID-19 Vaccine-Induced Benign Adenopathy from Breast Cancer Related Malignant Adenopathy HL, Chung GJ, Whitman JWT, Leung J, Sun LP, Middleton HT, Le-Petross Acad Radiol Original Investigation 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 (r(2) = 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. Association Of University Radiologists 2022-07 2022-02-21 /pmc/articles/PMC8858693/ /pubmed/35296413 http://dx.doi.org/10.1016/j.acra.2022.02.015 Text en Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Investigation HL, Chung GJ, Whitman JWT, Leung J, Sun LP, Middleton HT, Le-Petross Ultrasound Features to Differentiate COVID-19 Vaccine-Induced Benign Adenopathy from Breast Cancer Related Malignant Adenopathy |
title | Ultrasound Features to Differentiate COVID-19 Vaccine-Induced Benign Adenopathy from Breast Cancer Related Malignant Adenopathy |
title_full | Ultrasound Features to Differentiate COVID-19 Vaccine-Induced Benign Adenopathy from Breast Cancer Related Malignant Adenopathy |
title_fullStr | Ultrasound Features to Differentiate COVID-19 Vaccine-Induced Benign Adenopathy from Breast Cancer Related Malignant Adenopathy |
title_full_unstemmed | Ultrasound Features to Differentiate COVID-19 Vaccine-Induced Benign Adenopathy from Breast Cancer Related Malignant Adenopathy |
title_short | Ultrasound Features to Differentiate COVID-19 Vaccine-Induced Benign Adenopathy from Breast Cancer Related Malignant Adenopathy |
title_sort | ultrasound features to differentiate covid-19 vaccine-induced benign adenopathy from breast cancer related malignant adenopathy |
topic | Original Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8858693/ https://www.ncbi.nlm.nih.gov/pubmed/35296413 http://dx.doi.org/10.1016/j.acra.2022.02.015 |
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