FDG PET/CT radiomics as a tool to differentiate between reactive axillary lymphadenopathy following COVID-19 vaccination and metastatic breast cancer axillary lymphadenopathy: a pilot study

OBJECTIVES: To evaluate if radiomics with machine learning can differentiate between F-18-fluorodeoxyglucose (FDG)-avid breast cancer metastatic lymphadenopathy and FDG-avid COVID-19 mRNA vaccine–related axillary lymphadenopathy. MATERIALS AND METHODS: We retrospectively analyzed FDG-positive, patho...

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Detalles Bibliográficos
Autores principales: Eifer, Michal, Pinian, Hodaya, Klang, Eyal, Alhoubani, Yousef, Kanana, Nayroz, Tau, Noam, Davidson, Tima, Konen, Eli, Catalano, Onofrio A., Eshet, Yael, Domachevsky, Liran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8985565/
https://www.ncbi.nlm.nih.gov/pubmed/35385985
http://dx.doi.org/10.1007/s00330-022-08725-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8985565/
https://www.ncbi.nlm.nih.gov/pubmed/35385985
http://dx.doi.org/10.1007/s00330-022-08725-3

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