Objectives: To present a method combining ultrasound (US) and contrast-enhanced ultrasound (CEUS) features for differential diagnosis of cervical tuberculous lymphadenitis (CTL) and primary lymphoma.
Methods: A total of 155 patients with CTL (n = 49) and lymphoma (n = 106) who underwent US and CEUS were retrospectively included. The features extracted from US and CEUS and the significant clinical data were created three models using the least absolute shrinkage and selection operator and logistic regression analysis. The diagnostic performance of the models was assessed using the area under the curve (AUC).
Results: The combined model outperformed US model and CEUS model in distinguish CTL from lymphoma achieved favorable performances in training set and validation set with AUCs of 0.958 and 0.946 as well as high accuracies (91.7% and 87.2%), sensitivities (95.9% and 84.4%) and specificities (82.4% and 93.3%). Delong's test showed that among the three models, combined model was significantly different from the other two models in training set (p = 0.011 and 0.029, respectively) and validation set (p = 0.018 and 0.001, respectively).
Conclusions: A combination of US and CEUS achieved good diagnostic performance in differentiating lymphoma and CTL, which might aid in clinical decision-making.
Keywords: Contrast-enhanced ultrasound; LASSO.; cervical tuberculous lymphadenitis; lymph nodes; lymphoma.