甲状腺结节的风险分层系统因特异性低而受到限制。细针抽吸 (FNA) 活检尺寸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会 (ACR) 甲状腺成像报告和数据系统 (TI-RADS) 和人工智能 (AI) TI-RADS 中的最佳 FNA 活检大小阈值，并修订 AI TI 中的分层标准-RADS。回顾性分析2017年1月至2021年9月中国6家参与医院超声检查并确诊病理明确的2596个甲状腺结节（2511例患者）。 ACR TI-RADS 的修改标准为： (1) TR3 无 FNA； (2) TR4 的 FNA 阈值增加至 2.5 cm。 AI TI-RADS修改后的标准为：（1）6点结节升级至TR5； (2) TR3 无 FNA； (3) TR4 的 FNA 阈值增加至 2.5 cm。将修改版本的诊断性能和不必要的 FNA 率 (UFR) 与原始 ACR TI-RADS 进行了比较。与原始 ACR TI-RADS 相比，mACR（修改的 ACR）TI-RADS 产生了更高的特异性（73% vs 46%），尽管敏感性略有下降（87% vs 93%，P = 0.057），但准确度（74% vs 51%）、曲线下面积（AUC，0.80 vs 0.70）和较低的 UFR（25% vs 48%；所有 P < 0.001） ）。与原始 ACR TI-RADS 相比，mAI（改良 AI）TI-RADS 具有更高的特异性（73% vs 46%）、准确度（75% vs 51%）、AUC（0.81 vs 0.70）和更低的 UFR（24% vs 48） %；所有 P < 0.001），尽管灵敏度略有下降（89% vs 93%，P = 0.13）。 mACR TI-RADS和mAI TI-RADS在诊断性能和UFR方面无显着差异（均P>0.05）。mACR TI-RADS和mAI TI-RADS修订的FNA阈值和分层标准可能与改善有关特异性和准确性，而不会显着牺牲恶性肿瘤检测的灵敏度。

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 aim was 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 six participating Chinese hospitals. The modified criteria for ACR TI-RADS were: (1) no FNA for TR3; (2) FNA threshold for TR4 increased to 2.5 cm. The modified criteria for AI TI-RADS were: (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 unnecessary FNA rate (UFR) of modified versions were compared with the original ACR TI-RADS.Compared with original ACR TI-RADS, mACR (modified ACR) TI-RADS yielded higher specificity (73% vs 46%), accuracy (74% vs 51%), area under curve (AUC, 0.80 vs 0.70) and lower UFR (25% vs 48%; all P < 0.001) although the sensitivity was slightly decreased (87% vs 93%, P = 0.057). Compared with original ACR TI-RADS, mAI (modified AI) 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 P < 0.001), although the sensitivity tended to be slightly decreased (89% vs 93%, P = 0.13). There was no significant difference between mACR TI-RADS and mAI TI-RADS in the diagnostic performance and UFR (all P > 0.05).The revised FNA thresholds and stratification criteria of mACR TI-RADS and mAI TI-RADS may be associated with improvements in specificity and accuracy, without significantly sacrificing sensitivity for malignancy detection.