改善了异声甲状腺结节的癌症风险分层,以减少使用定量超声波进行不必要的活检
Poorani N Goundan1, Theresa Lye2,3, Andrew Markel2,4
1Section of Endocrinology, Diabetes, Nutrition and Metabolism, Boston Medical Center, Chobanian Avedisian School of Medicine, Boston, MA, United States.
Frontiers in endocrinology
|February 19, 2024
概括
定量超声波 (QUS) 显示出改善异声甲状腺结节 (TNs) 癌症风险分层的前景. 这种基于QUS的新型分类器可能会优于传统方法,减少不必要的细针活检.
科学领域:
- 医疗成像医学成像
- 诊断性的超声波检查
- 在瘤学瘤学.
背景情况:
- 灰度超声波 (US) 是甲状腺结节 (TN) 评估的标准,但与异声恶性TNS作斗争.
- 定量超声波 (QUS) 分析射频回声信号以评估组织微观架构,可能提供更好的诊断能力.
研究的目的:
- 为了确定定量超声波 (QUS) 是否可以提高异声性甲状腺结节 (TNs) 的癌症风险分层.
主要方法:
- 收集了来自274个TN (163个异声,111个低声) 进行细针活检 (FNB) 的B模式US和QUS数据.
- 开发并测试了基于QUS的分类器 (CQP) 对同声[CQP(i) ]和低声[CQP(h) ]TN进行分类.
- 与已建立的风险分层系统 (如ACR TI-RADS和ATA) 相比,对CQP的性能进行了比较.
主要成果:
- 同声波的QUS分类器 [CQP(i) ]实现了0.937的ROC AUC,明显超过了ACR TI-RADS (0.717) 和ATA (0.589).
- 在73%的同音响TN中,CQP显示了避免不必要的FNB的潜力,而在55.8% (ACR TI-RADS) 和11.8% (ATA) 则相比之下.
结论:
- 基于QUS的分类器显示,与传统的美国分层系统相比,在评估同响的TN方面表现优越.
- 需要在更大的研究中进一步验证,以探索这种QUS方法在甲状腺结节风险分层方面的临床实用性.
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