Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Department of Ultrasound, Department of Medical Ultrasonics, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Thyroid. 2024 Jan;34(1):88-100. doi: 10.1089/thy.2023.0429. Epub 2023 Dec 7.
Risk stratification systems for thyroid nodules are limited by low specificity. The fine-needle aspiration (FNA) biopsy size thresholds and stratification criteria are based on evidence from the literature and expert consensus. Our aims were to investigate the optimal FNA biopsy size thresholds in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and artificial intelligence (AI) TI-RADS and to revise the stratification criteria in AI TI-RADS. A total of 2596 thyroid nodules (in 2511 patients) on ultrasound examination with definite pathological diagnoses were retrospectively identified from January 2017 to September 2021 in 6 participating Chinese hospitals. The modified criteria for ACR TI-RADS were as follows: (1) no FNA for TR3; (2) FNA threshold for TR4 increased to 2.5 cm. The modified criteria for AI TI-RADS were as follows: (1) 6-point nodules upgraded to TR5; (2) no FNA for TR3; (3) FNA threshold for TR4 increased to 2.5 cm. The diagnostic performance and the unnecessary FNA rate (UFR) of modified versions were compared with the original ACR TI-RADS. Compared with the original ACR TI-RADS, the modified ACR (mACR) TI-RADS yielded higher specificity (73% vs. 46%), accuracy (74% vs. 51%), area under the receiver operating characteristic curve (AUC; 0.80 vs. 0.70), and lower UFR (25% vs. 48%; all < 0.001), although the sensitivity was slightly decreased (87% vs. 93%, = 0.057). Compared with the original ACR TI-RADS, the modified AI (mAI) TI-RADS yielded higher specificity (73% vs. 46%), accuracy (75% vs. 51%), AUC (0.81 vs. 0.70), and lower UFR (24% vs. 48%; all < 0.001), although the sensitivity tended to be slightly decreased (89% vs. 93%, = 0.13). There was no significant difference between the mACR TI-RADS and mAI TI-RADS in the diagnostic performance and UFR (all > 0.05). The revised FNA thresholds and the stratification criteria of the mACR TI-RADS and mAI TI-RADS may be associated with improvements in specificity and accuracy, without significantly sacrificing sensitivity for malignancy detection.
甲状腺结节的风险分层系统特异性较低。细针穿刺活检（FNA）活检的大小阈值和分层标准基于文献证据和专家共识。我们的目的是研究美国放射学院（ACR）甲状腺影像报告和数据系统（TI-RADS）和人工智能（AI）TI-RADS 中最佳的 FNA 活检大小阈值，并修订 AI TI-RADS 的分层标准。 2017 年 1 月至 2021 年 9 月，我们在中国 6 家参与医院的超声检查中，回顾性地确定了 2511 例患者的 2596 个明确病理诊断的甲状腺结节。修改后的 ACR TI-RADS 标准如下：（1）TR3 无需 FNA；（2）TR4 的 FNA 阈值增加至 2.5cm。AI TI-RADS 的修改标准如下：（1）6 分结节升级为 TR5；（2）TR3 无需 FNA；（3）TR4 的 FNA 阈值增加至 2.5cm。与原始 ACR TI-RADS 相比，比较了修改版本的诊断性能和不必要的 FNA 率（UFR）。 与原始的 ACR TI-RADS 相比，改良的 ACR（mACR）TI-RADS 具有更高的特异性（73% vs. 46%）、准确性（74% vs. 51%）、受试者工作特征曲线下面积（AUC；0.80 vs. 0.70）和更低的 UFR（25% vs. 48%；均<0.001），尽管敏感性略有降低（87% vs. 93%，=0.057）。与原始的 ACR TI-RADS 相比，改良的 AI（mAI）TI-RADS 具有更高的特异性（73% vs. 46%）、准确性（75% vs. 51%）、AUC（0.81 vs. 0.70）和更低的 UFR（24% vs. 48%；均<0.001），尽管敏感性略有降低（89% vs. 93%，=0.13）。mACR TI-RADS 和 mAI TI-RADS 的诊断性能和 UFR 之间没有显著差异（均>0.05）。 mACR TI-RADS 和 mAI TI-RADS 的修订 FNA 阈值和分层标准可能与特异性和准确性的提高有关，而不会显著牺牲恶性肿瘤检测的敏感性。
