探讨S-detect人工智能技术在辅助住院医师诊断≤1 cm的甲状腺影像报告和数据系统（TI-RADS）4类甲状腺结节良恶性中的临床应用价值。

2021年3~4月前瞻性连续纳入在解放军总医院第一医学中心行甲状腺超声检查和甲状腺超声引导下穿刺活检及外科手术切除的133例患者，共133个最大径≤1 cm的TI-RADS 4类甲状腺结节，其中良性结节21个，恶性结节112个。采集上述甲状腺结节的超声图像、S-detect诊断模式图像。以手术病理为金标准，绘制常规超声、S-deteet技术及两者联合诊断甲状腺结节良恶性的受试者操作特征（ROC）曲线，采用McNemar检验对比分析住院医师应用常规超声、S-detect技术及两者联合诊断甲状腺结节良恶性的敏感度、特异度及准确性的差异，采用DeLong检验比较ROC曲线下面积的差异。

住院医师应用常规超声诊断甲状腺结节良恶性的敏感度为95.5%（107/112）、特异度为42.9%（9/21）、准确性为88.0%（116/133）；S-detect技术诊断的敏感度为93.8%（105/112）、特异度为52.4%（11/21）、准确性为87.2%（116/133）；S-detect技术与常规超声联合诊断的敏感度为92.0%（105/112）、特异度为76.2%（11/21）、准确性为89.5%（116/133）。常规超声、S-detect技术及两者联合鉴别诊断≤1 cm甲状腺结节良恶性的ROC曲线下面积分别为0.692、0.731和0.841。两者联合诊断的准确性、特异度和ROC曲线下面积均高于单独应用常规超声和S-detect技术，其中ROC曲线下面积比较差异具有统计学意义（P=0.007，P=0.028）。

S-detect人工智能技术辅助住院医师可提高对≤1 cm TI-RADS 4类甲状腺结节良恶性的诊断效能。

To evaluate the auxiliary diagnostic value of S-detect artificial intelligence system in the differential diagnosis of thyroid imaging reporting and data system (TI-RADS) 4 subcentimeter thyroid nodules by ultrasound residents.

From March 2021 to April 2021, 133 patients with 133 TI-RADS 4 thyroid nodules (maximum diameter ≤1 cm, including 112 malignant nodules and 21 benign nodules) undergoing thyroid ultrasound examination and ultrasound guided biopsy/thyroid surgery at the First Center of Chinese PLA General Hospital were consecutively enrolled. Ultrasound images and S-detect mode images were acquired by ultrasound residents. Taking pathological results as the golden standard, the receiver operating characteristic (ROC) curve was drawn and the diagnostic performance of residents using ultrasound, S-detect technique, and the combination of these two methods was analyzed. The sensitivity, specificity, and accuracy were compared using McNemar's test and the area under the curve (AUC) was compared using DeLong test.

The sensitivity, specificity, and accuracy of ultrasound in differential diagnosis of thyroid nodules ≤1 cm were 95.5% (107/112), 42.9% (9/21), and 88.0% (116/133), of S-detect were 93.8% (105/112), 52.4% (11/21), and 87.2% (116/133), and of the residents aided with S-detect were 92.0% (105/112), 76.2% (11/21), and 89.5% (116/133), respectively. The AUC values of ultrasound, S-detect, and the combination of the two methods were 0.692, 0.731, and 0.841, respectively. The accuracy, specificity, and AUC of the combined method were higher than those of ultrasound and S-detect alone; the AUC was statistically different (P=0.007 and P=0.028, respectively).

S-detect technique may be a complementary tool in imaging diagnosis, which contributes to the augment of diagnostic performance of ultrasound residents in differentially diagnosing TI-RADS 4 thyroid nodules ≤1 cm.