Scholarlink

Background <p>The American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) 6th Edition’s updated definition of mixed solid and cystic breast lesions (MSCBLs) reflects the diagnostic challenges in assessing these lesions. This study aimed to develop and validate a scoring system based on ultrasound (US) features and clinical factors to differentiate benign from malignant MSCBLs.</p> Methods <p>This retrospective multicenter study included 499 MSCBLs from three medical centers, which were divided into a training cohort (<i>n</i> = 396, 79.4%) and an external validation cohort (<i>n</i> = 103, 20.6%). Ultrasound features and clinical characteristics were analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of malignancy, on the basis of which a nomogram was constructed. This nomogram was subsequently simplified into a practical scoring system. The performance of the scoring system was validated in the independent external cohort. Furthermore, its added diagnostic value was assessed across radiologists with different levels of experience.</p> Results <p>Multivariate logistic analysis identified age, lesion type, shape, vascularity, and lesion size as independent predictors of malignancy. The simplified scoring system demonstrated high diagnostic efficacy in the training cohort (area under the curve, AUC = 0.853, 95% CI: 0.813–0.892), with internal validation using bootstrap resampling confirming robust performance (optimism-corrected AUC = 0.834). In the external validation cohort, the scoring system demonstrated good diagnostic performance (AUC = 0.801, 95% CI: 0.710–0.893) and high interobserver agreement (weighted κ=0.78, 95% CI: 0.72–0.84). It also improved diagnostic performance for junior and intermediate radiologists, improving AUC from 0.66 to 0.74 for junior radiologists (<i>p</i> &lt; 0.001) and increasing specificity for intermediate radiologists.</p> Conclusion <p>The MSCBLs scoring system provides a reliable tool for risk stratification, enhancing the diagnostic performance of junior radiologists and ensuring high interobserver consistency, while serving as a valuable complement to existing risk stratification systems.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Enhancing mixed solid and cystic breast lesions diagnosis: a simplified scoring system integrating ultrasound features and clinical factors

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月19日

查看全文
  • Yingying Jia,
  • Qiong Lan,
  • Ting Liu,
  • Yangyang Zhu,
  • Cui Cao,
  • Xinyue Hu,
  • Fang Nie

摘要

Background

The American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) 6th Edition’s updated definition of mixed solid and cystic breast lesions (MSCBLs) reflects the diagnostic challenges in assessing these lesions. This study aimed to develop and validate a scoring system based on ultrasound (US) features and clinical factors to differentiate benign from malignant MSCBLs.

Methods

This retrospective multicenter study included 499 MSCBLs from three medical centers, which were divided into a training cohort (n = 396, 79.4%) and an external validation cohort (n = 103, 20.6%). Ultrasound features and clinical characteristics were analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of malignancy, on the basis of which a nomogram was constructed. This nomogram was subsequently simplified into a practical scoring system. The performance of the scoring system was validated in the independent external cohort. Furthermore, its added diagnostic value was assessed across radiologists with different levels of experience.

Results

Multivariate logistic analysis identified age, lesion type, shape, vascularity, and lesion size as independent predictors of malignancy. The simplified scoring system demonstrated high diagnostic efficacy in the training cohort (area under the curve, AUC = 0.853, 95% CI: 0.813–0.892), with internal validation using bootstrap resampling confirming robust performance (optimism-corrected AUC = 0.834). In the external validation cohort, the scoring system demonstrated good diagnostic performance (AUC = 0.801, 95% CI: 0.710–0.893) and high interobserver agreement (weighted κ=0.78, 95% CI: 0.72–0.84). It also improved diagnostic performance for junior and intermediate radiologists, improving AUC from 0.66 to 0.74 for junior radiologists (p < 0.001) and increasing specificity for intermediate radiologists.

Conclusion

The MSCBLs scoring system provides a reliable tool for risk stratification, enhancing the diagnostic performance of junior radiologists and ensuring high interobserver consistency, while serving as a valuable complement to existing risk stratification systems.