Differential diagnosis of cervical lymphadenopathy: Integration of postvascular phase of contrast-enhanced ultrasound and predictive nomogram model.

Background: Distinguishing benign from malignant cervical lymph nodes is critical yet challenging. This study evaluates the postvascular phase of contrast-enhanced ultrasound (CEUS) and develops a user-friendly nomogram integrating demographic, conventional ultrasound, and CEUS features for accurate differentiation.

Methods: We retrospectively analyzed 395 cervical lymph nodes from 395 patients between January 2020 and December 2022. The cohort was divided into training and validation sets using stratified random sampling. A predictive model, based on demographic, ultrasound, and CEUS features, was created and internally validated.

Results: The training set included 280 patients (130 benign, 150 malignant nodes) and the validation set 115 patients (46 benign, 69 malignant). Relative hypoenhancement in the postvascular phase emerged as a promising indicator for MLN, with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 96.7 %,52.3 %, 70.0 %, 93.2 %, and 76.1 %, respectively in the training set and 95.7 %, 52.2 %, 75.0 %, 88.9 %, and 74.8 % in the validation set. Age over 50 years, history of malignancy, short-axis diameter greater than 1.00 cm, focal hyperechogenicity, ill-defined borders, and centripetal perfusion were also identified as independent MLN indicators. The nomogram prediction model showed outstanding accuracy, with an area under the curve (AUC) of 0.922 (95 % CI: 0.892-0.953) in the training set and 0.914 (95 % CI: 0.864-0.963) in the validation set.

Conclusion: Relative hypoenhancement in the postvascular phase of CEUS, combined with demographics and ultrasound features, is effective for identifying MLNs. The developed prediction model, with a user-friendly nomogram, can facilitate clinical decision-making.