Predicting malignant neck lymphadenopathy using color duplex sonography based on multivariate analysis.

Purpose: To select the best predictors of cervical lymph node malignancy based on gray-scale and power Doppler sonography using multivariate analysis.

Methods: We evaluated sonographically a total of 97 lymph nodes in the neck that were subjected to fine-needle aspiration biopsy. The gray-scale and power Doppler sonography parameters that we analyzed using multivariate logistic regression included size, shape, echogenicity, echotexture, margins, hilum, presence of microcalcifications or necrosis, vascularization, and resistance index (RI).

Results: The three variables with a diagnostic accuracy exceeding 80% were an altered vascularization, heterogeneous echotexture, and abnormal hilum. Malignant nodes exhibited higher RI and larger sizes than benign nodes, and the best cutoff values to distinguish malignant from benign lymph nodes were an RI of 0.77 and a short axis ≥ 0.9 cm. Altered vascularization, a short axis ≥ 0.9 cm, and abnormal hilum were the best predictors of malignancy.

Conclusions: The best sonographic predictors of lymph node malignancy are, in descending order, an altered vascularization, a short axis ≥ 0.9 cm, an abnormal hilum, and a heterogeneous echotexture. © 2016 Wiley Periodicals, Inc. J Clin Ultrasound 44:587-594, 2016.