ArticleInsights into imaging2024
Application of microvascular ultrasound-assisted thyroid imaging report and data system in thyroid nodule risk stratification.
Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Diagnostic value of the nomogram model based on multimodal ultrasound features combined with PS-Tg for differentiating benign and malignant thyroid nodules.Gland surgery · 2026Article
- Evaluating the clinical impact of integrating superb microvascular imaging and shear wave elastography into TI-RADS.Journal of ultrasound · 2025Article
- Usefulness of ultrasound quantitative assessment of microvascularity in the thyroid nodule risk stratification.Journal of ultrasound · 2025Article
- Microvascular Ultrasonography Vascularity Index as a Rapid and Simplified Assessment Tool for Differentiating Graves' Disease from Destructive Thyroiditis and Managing Thyrotoxicosis.Endocrinology and metabolism (Seoul, Korea) · 2025Article
- Optimizing C-TIRADS for sub-centimeter thyroid nodules using machine learning-derived feature importance.Frontiers in endocrinology · 2025Article
- Mapping the Evolution of Thyroid Ultrasound Research: A 30-year Bibliometric AnalysisCurrent medical imaging · 2025Review
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10 authors.
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Abstract
objectivesTo establish superb microvascular imaging (SMI) based thyroid imaging reporting and data system (SMI TI-RADS) for risk stratification of malignancy in thyroid nodules.
methodsIn total, 471 patients, comprising 643 thyroid nodules, who received conventional ultrasound (US), SMI, and a final diagnosis were extensively analyzed. A qualitative assessment of US features of the nodules was performed followed by univariable and multivariable logistic regression analyses, leading to the construction of the SMI TI-RADS, which was further verified using internal and external validation cohorts.
resultsAmong the stand-alone US, predictive factors were the shape and margins of the nodules, echogenicity and echogenic foci, vascularity, extrathyroidal extension, ring-SMI patterns, penetrating vascularity, flow-signal enlarged, and vascularity area ratio. SMI TI-RADS depicted an enhanced area under the receiver operating characteristic curve (AUC) of 0.94 (95% CI: 0.92, 0.96; p < 0.001 relative to other stratification systems), a 79% biopsy yield of malignancy (BYM, 189/240 nodules), and a 21% unnecessary biopsy rate (UBR, 51/240 nodules). In the verification cohorts, we demonstrated AUCs, malignancy biopsy yields, and unnecessary biopsy rates of 0.88 (95% CI: 0.83, 0.94), 79% (59/75 nodules), and 21% (16/75 nodules) for the internal cohort, respectively, and 0.91 (95% CI: 0.85, 0.96), 72% (31/43 nodules), and 28% (12/43 nodules) for the external cohort, respectively.
conclusionSMI TI-RADS was found to be superior in diagnostic sensitivity, specificity, and efficiency than existing TI-RADSs, showing better stratification of the malignancy risk, and thus decreasing the rate of unnecessary needle biopsy. CRITICAL RELEVANCE STATEMENT: To develop an imaging and data system based on conventional US and SMI features for stratifying the malignancy risk in thyroid nodules. KEY POINTS: SMI features could improve thyroid nodule risk stratification. SMI TI-RADS showed superior diagnostic efficiency and accuracy for biopsy guidance. SMI TI-RADS can provide better guidance for clinical diagnosis and treatment of thyroid nodules.
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