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Development and Validation of the So-RADS: An Ultrasound-Based Risk Stratification System for Soft-Tissue Masses
Yanyan Wu1, Ting Cui1, Renjie Feng1
1Department of Ultrasound, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Rationale And Objectives:
The accurate diagnosis of soft-tissue masses (STMs) remains challenging due to their heterogeneous histology and the lack of a standardized ultrasound reporting system, which leads to reliance on subjective interpretation. To address this limitation, we developed and validated the soft-tissue radiology reporting and data system (So-RADS), an ultrasound-based risk stratification tool for STMs.
Methods:
This retrospective study included 858 pathologically confirmed STMs. To enhance clinical applicability for uncertain cases, the model was developed using a cohort of lesions with ambiguous ultrasound features (n = 490). Independent predictors of malignancy, identified through multivariate logistic regression, were assigned points to create a scoring system. This score was then converted into the definitive So-RADS categories.
Results:
Seven independent predictors were identified and assigned points: age ≥ 50 y, size ≥ 50 mm, blurred margin, irregular shape, heterogeneous echogenicity, history of malignancy, and rich blood flow. Based on these predictors, the So-RADS system (score range 0-10) demonstrated excellent diagnostic performance, with an area under the receiver operating characteristic (ROC) curve of 0.900. A cut-off score of ≥ 4 points yielded a sensitivity of 78.1% and a specificity of 87.2%. The system employs a two-step classification scheme. First, masses are categorized as typical benign (So-RADS 2). Second, atypical masses are stratified as So-RADS 3 (low risk), 4 (moderate risk), or 5 (high risk), with each category linked to specific management recommendations. Interobserver agreement was substantial (weighted Kappa = 0.784).
Conclusion:
The So-RADS system is a robust and reproducible tool that standardizes US reporting for STMs, improves diagnostic accuracy, and provides clear management guidance.
