Elastography Enhances the Diagnostic Performance of Conventional Ultrasonography in Differentiating Benign from...

Lymph node (LN) evaluation is critical in diagnosing, staging, and managing various diseases, particularly lymphoma and metastatic cancer. Although conventional ultrasound (US) is widely used for this purpose, its limitations in reliably differentiating between benign and malignant LNs persist. Ultrasound elastography (US-E), which evaluates tissue stiffness, has emerged as a promising adjunct to improve diagnostic accuracy. This study aims to evaluate the diagnostic performance of conventional US, power Doppler US, and strain elastography (SE) in distinguishing malignant from benign superficial lymph nodes.

In this prospective study, 214 consecutive patients referred for US of enlarged LNs were enrolled. Conventional B-mode US, power Doppler, and SE were performed, and the strain ratio (SR) was calculated as a measure of LN stiffness. Histopathological examination was used as the reference standard. Diagnostic accuracy was assessed using receiver operating characteristic (ROC) analysis, and multivariable logistic regression models were applied to determine the independent predictive role of SR.

Among the 214 LNs (one for each patient), 74 (34.6%) were benign and 140 (65.4%) were malignant. The SR showed a significant association with malignancy (p < 0.001). For hematological malignancies, SR demonstrated high sensitivity (79-85%) and specificity (81-96%), with an overall area under the curve (AUC) of 0.91. Multivariable analysis confirmed that SR was an independent predictor of malignancy (continuous and dichotomous), with a 14% gain in predictive accuracy when treated as a continuous variable (p < 0.0001).

US-E, particularly SR, is a valuable tool in the differentiation of benign and malignant superficial LNs. SR provides significant diagnostic value, especially in hematological neoplasms like Hodgkin lymphoma, and can serve as an independent predictor of malignancy. This technique, when used in combination with conventional US features, offers enhanced diagnostic performance for LN evaluation.