Characterization of hypermetabolic lymph nodes after SARS-CoV-2 vaccination using PET-CT derived node-RADS, in patients with melanoma

Author:

Gennari Antonio G.ORCID,Rossi AlexiaORCID,Sartoretti ThomasORCID,Maurer AlexanderORCID,Skawran StephanORCID,Treyer ValerieORCID,Sartoretti Elisabeth,Curioni-Fontecedro AlessandraORCID,Schwyzer MoritzORCID,Waelti StephanORCID,Huellner Martin W.ORCID,Messerli MichaelORCID

Abstract

AbstractThis study aimed to evaluate the diagnostic accuracy of Node Reporting and Data System (Node-RADS) in discriminating between normal, reactive, and metastatic axillary LNs in patients with melanoma who underwent SARS-CoV-2 vaccination. Patients with proven melanoma who underwent a 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[18F]-FDG PET/CT) between February and April 2021 were included in this retrospective study. Primary melanoma site, vaccination status, injection site, and 2-[18F]-FDG PET/CT were used to classify axillary LNs into normal, inflammatory, and metastatic (combined classification). An adapted Node-RADS classification (A-Node-RADS) was generated based on LN anatomical characteristics on low-dose CT images and compared to the combined classification. 108 patients were included in the study (54 vaccinated). HALNs were detected in 42 patients (32.8%), of whom 97.6% were vaccinated. 172 LNs were classified as normal, 30 as inflammatory, and 14 as metastatic using the combined classification. 152, 22, 29, 12, and 1 LNs were classified A-Node-RADS 1, 2, 3, 4, and 5, respectively. Hence, 174, 29, and 13 LNs were deemed benign, equivocal, and metastatic. The concordance between the classifications was very good (Cohen’s k: 0.91, CI 0.86–0.95; p-value < 0.0001). A-Node-RADS can assist the classification of axillary LNs in melanoma patients who underwent 2-[18F]-FDG PET/CT and SARS-CoV-2 vaccination.

Funder

Swiss Government Excellence Scholarship

CRPP “AI Oncological Imaging Network”

Palatin fundation

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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