Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification

Area of Science:

• Radiology and Imaging
• Oncology
• Endocrinology

Background:

• Existing Thyroid Image Reporting and Data System (TIRADS) classifications vary globally.
• Ultrasound (US) parameters are crucial for thyroid nodule evaluation.
• The integration of sonoelastography (SE) can potentially refine risk stratification.

Purpose of the Study:

• To introduce a risk classification and management strategy for thyroid nodules.
• To incorporate sonoelastography into the existing Polish National Societies' guidelines.
• To evaluate the added value of SE in predicting malignancy compared to B-mode US alone.

Main Methods:

• Prospective study of 208 patients with 305 thyroid lesions.
• Assessment using B-mode ultrasound (composition, echogenicity, margins, shape, calcifications, capsule, size) and sonoelastography (Asteria scale).
• Univariate and multivariate logistic regression analyses to identify malignancy predictors.

Main Results:

• Significant univariate predictors of malignancy included solid composition, marked hypoechogenicity, ill-defined margins, micro/macrocalcifications, taller-than-wide shape, capsular infiltration, and Asteria score 4.
• Multivariate analysis identified ill-defined margins, marked hypoechogenicity, microcalcifications, capsular infiltration, macrocalcifications, and hard lesions on SE as independent predictors.
• The combination of irregular margins and Asteria scale 4 yielded the highest odds ratio (OR 20.21) for malignancy.

Conclusions:

• Sonoelastography significantly enhances the prediction of malignancy risk in thyroid nodules.
• Integrating SE allows for more precise categorization within the TIRADS system, potentially upgrading nodules to TIRADS 5.
• Irregular margins and specific SE findings (Asteria 3, 4) are strong indicators, with combined features offering the highest diagnostic accuracy.