Ultrasound-based Node-RADS: Introducing a new Scoring System for Ultrasound-based Classification of Lymphadenopathy

基于超声的淋巴结放射影像学和数据系统(Node-RADS):引入一种新的基于超声的淋巴结病变分类评分系统

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Abstract

INTRODUCTION: Lymphadenopathy often causes anxiety due to its association with malignancy or serious infections. This study investigates the role of ultrasound features in distinguishing benign from malignant neck lymphadenopathy and proposes a quantitative scoring system (Node-RADS). MATERIALS AND METHODS: This cross-sectional study was conducted at Omid Hospital, Mashhad University of Medical Sciences, Iran. Seven hundred ninety-one patients with neck lymphadenopathy underwent gray-scale and Doppler ultrasound, followed by fine needle aspiration (FNA) or core needle biopsy (CNB) for cytopathological confirmation. Key ultrasound features assessed included Short-Axis Diameter (SAD), Cortical/Hilar Echotexture, and Vascular patterns. A scoring system was developed by assigning malignancy coefficients to each variable. Malignancy coefficients (Wi) were assigned based on the prevalence of malignancy for each feature, and a quantitative Node-RADS score was derived. Diagnostic accuracy was evaluated using ROC analysis. RESULTS: Of 791 patients, 68.5% (542) had malignant lymphadenopathy, predominantly metastases (57.1%, 452). Malignancy coefficients (Wi = 9) were extracted to high-risk features: SAD >16 mm (82% malignancy), Isoechoic cortex with compressed hilum (89%), and non-hilar vascularity (91%). The proposed Node-RADS system achieved an AUC of 0.85 (95% CI: 0.817-0.889), demonstrating strong diagnostic performance. CONCLUSION: The proposed ultrasound-based Node-RADS scoring system correlates significantly with pathologic results, offering an appropriate tool for evaluating cervical superficial lymphadenopathy.

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