Analysis of Diagnostic Efficacy of AI-Assisted Diagnosis Combined with
C-TIRADS Classification for Thyroid Nodules
XU Ke, SHI Bo, ZHOU Chunmei, ZENG Zhuohua, XIE Yang, LIU Jiakai
Department of Ultrasound Medicine, The 2nd Affiliated Hospital of Chengdu Medical College, Nuclear Industry 416 Hospital,
Chengdu Sichuan 610057, China
Abstract：Objective To explore the diagnostic value of artificial intelligence (AI) diagnostic system combined with Chinese
thyroid imaging reporting and data system (C-TIRADS) in thyroid nodules. Methods The 225 cases of thyroid nodules that met
the inclusion and exclusion criteria were selected as the research objects, and C-TIRADS classification diagnosis, AI diagnosis, and
AI diagnosis combined with C-TIRADS classification diagnosis method were used for diagnosis respectively. The diagnosis results
of coarse needle puncture or surgical pathological were used as the gold standard, and the receiver operating characteristic (ROC)
curves were drawn. The area under the ROC curve (AUC), sensitivity, specificity, and Youden index of the three diagnosis methods
were compared. Results The AUC of combined diagnosis (0.952) was higher than that of C-TIRADS classification diagnosis
(0.900) and AI diagnosis (0.829), the specificity of combined diagnosis (95.74%) was higher than that of AI diagnosis (84.04%) and
C-TIRADS classification diagnosis (82.98%), the sensitivity of C-TIRADS classification diagnosis (96.95%) was higher than that
of combined diagnosis (94.66%) and AI diagnosis (81.68%). In the diagnosis of nodules ≤10 mm, the AUC of combined diagnosis
(0.978) was higher than that of AI diagnosis (0.897) and C-TIRADS classification diagnosis (0.778), the sensitivity of combined
diagnosis (98.36%) was higher than that of C-TIRADS classification diagnosis (93.44%) and AI diagnosis (90.16%), the specificity
of combined diagnosis (97.30%) was higher than that of AI diagnosis (89.19%) and C-TIRADS classification diagnosis (62.16%).
In the diagnosis of nodules >10 mm, the AUC of C-TIRADS classification diagnosis (0.982) was higher than that of combined
diagnosis (0.931) and AI diagnosis (0.775), the sensitivity of C-TIRADS classification diagnosis (100%) was higher than that of
combined diagnosis (91.43%) and AI diagnosis (74.29%), the specificity of C-TIRADS classification diagnosis (96.49%) was higher
than that of combined diagnosis (94.74%) and AI diagnosis (80.7%), and the differences were statistically significant (P<0.05).
徐可，石波，周春美，曾卓华，谢杨，刘家开. AI辅助诊断联合医师C-TIRADS分类对甲状腺结节的诊断效能分析[J]. 中国医疗设备, 2022, 37(10): 134-138.
XU Ke, SHI Bo, ZHOU Chunmei, ZENG Zhuohua, XIE Yang, LIU Jiakai. Analysis of Diagnostic Efficacy of AI-Assisted Diagnosis Combined with
C-TIRADS Classification for Thyroid Nodules. China Medical Devices, 2022, 37(10): 134-138.
