Characterization of hypermetabolic lymph nodes after SARS-CoV-2 vaccination using PET-CT derived node-RADS, in patients with melanoma.
Antonio Giulio GennariAlexia RossiThomas SartorettiAlexander MaurerStephan M Beintner-SkawranValerie TreyerElisabeth SartorettiAlessandra Curioni-FontecedroMoritz SchwyzerStephan L WaeltiMartin W HuellnerMichael MesserliPublished in: Scientific reports (2023)
This 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-[ 18 F]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[ 18 F]-FDG PET/CT) between February and April 2021 were included in this retrospective study. Primary melanoma site, vaccination status, injection site, and 2-[ 18 F]-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-[ 18 F]-FDG PET/CT and SARS-CoV-2 vaccination.
Keyphrases
- lymph node
- positron emission tomography
- computed tomography
- sars cov
- deep learning
- pet ct
- end stage renal disease
- machine learning
- ejection fraction
- squamous cell carcinoma
- low dose
- newly diagnosed
- prognostic factors
- small cell lung cancer
- peritoneal dialysis
- neoadjuvant chemotherapy
- sentinel lymph node
- oxidative stress
- ultrasound guided
- magnetic resonance
- patient reported outcomes
- type diabetes
- respiratory syndrome coronavirus
- metabolic syndrome
- insulin resistance
- adipose tissue
- blood pressure
- electronic health record
- pet imaging
- convolutional neural network
- skeletal muscle
- data analysis
- rectal cancer