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Background <p>Thyroid nodules are increasingly detected with high-resolution imaging. While most are benign, accurate risk stratification is essential for identifying those requiring further investigation. Various classification systems have been developed to standardize assessment, with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) being widely adopted internationally. The Chinese TIRADS (C-TIRADS) offers an alternative approach with potential advantages in simplicity and practicality. These systems are well-studied in nodules &gt; 10 mm, but their comparative diagnostic performance in small thyroid nodules (&lt; 10 mm) remains understudied. This study aimed to compare ACR-TIRADS and C-TIRADS diagnostic performance for predicting malignancy in small thyroid nodules (&lt; 10 mm). </p> Results <p>This study included 128 thyroid nodules (84.3% benign and 15.6% malignant). The most common benign pathology was benign goiter (87%), while the most frequent malignancy was papillary thyroid carcinoma (85%). The ROC curves analyses indicated an AUC of 0.797 for ACR-TIRADS and 0.794 for C-TIRADS, with optimal cutoff points at ACR-TIR4 (sensitivity 80% and specificity 75.9%) and C-TIR4b (sensitivity 70% and specificity 83.3%). The ACR-TIRADS demonstrated higher sensitivity, but lower specificity compared to C-TIRADS. Both systems had high negative predictive values (&gt; 94%), ensuring reliable exclusion of malignancy. The C-TIRADS exhibited higher overall accuracy (81.3%) than ACR-TIRADS (76.5%) due to a better balance of sensitivity and specificity.</p> Conclusions <p>Both systems showed comparable diagnostic accuracy (AUCs: 0.797 vs 0.794) for small nodule stratification, suggesting complementary roles with distinct advantages. Given the modest sample size, particularly limited malignant cases, findings require validation in larger multicenter studies before definitive recommendations.</p>

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A comparative study of Chinese and ACR-TIRADS diagnostic accuracy in small thyroid nodule risk evaluation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月9日

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  • Rasha Nadeem Ahmed,
  • Maysaloon Shaman Saeed,
  • Nazar M. T. Jawhar,
  • Mohamed Tarek El-Diasty,
  • Noha Yahia Ebaid,
  • Mostafa Mohamad Assy

摘要

Background

Thyroid nodules are increasingly detected with high-resolution imaging. While most are benign, accurate risk stratification is essential for identifying those requiring further investigation. Various classification systems have been developed to standardize assessment, with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) being widely adopted internationally. The Chinese TIRADS (C-TIRADS) offers an alternative approach with potential advantages in simplicity and practicality. These systems are well-studied in nodules > 10 mm, but their comparative diagnostic performance in small thyroid nodules (< 10 mm) remains understudied. This study aimed to compare ACR-TIRADS and C-TIRADS diagnostic performance for predicting malignancy in small thyroid nodules (< 10 mm).

Results

This study included 128 thyroid nodules (84.3% benign and 15.6% malignant). The most common benign pathology was benign goiter (87%), while the most frequent malignancy was papillary thyroid carcinoma (85%). The ROC curves analyses indicated an AUC of 0.797 for ACR-TIRADS and 0.794 for C-TIRADS, with optimal cutoff points at ACR-TIR4 (sensitivity 80% and specificity 75.9%) and C-TIR4b (sensitivity 70% and specificity 83.3%). The ACR-TIRADS demonstrated higher sensitivity, but lower specificity compared to C-TIRADS. Both systems had high negative predictive values (> 94%), ensuring reliable exclusion of malignancy. The C-TIRADS exhibited higher overall accuracy (81.3%) than ACR-TIRADS (76.5%) due to a better balance of sensitivity and specificity.

Conclusions

Both systems showed comparable diagnostic accuracy (AUCs: 0.797 vs 0.794) for small nodule stratification, suggesting complementary roles with distinct advantages. Given the modest sample size, particularly limited malignant cases, findings require validation in larger multicenter studies before definitive recommendations.