Diagnostic efficacy of computer aided diagnosis system in differentiating benign and malignant thyroid nodules and its influencing factors

doi:10.3877/cma.j.issn.1672-6448.2019.04.004

Abstract

Abstract:

Objective

To determine the diagnostic efficacy of the computer aided diagnosis (CAD) system in discriminating malignant and benign thyroid nodules and the possible influencing factors.

Methods

This retrospective study analyzed 1035 patients with 1065 thyroid nodules at Sun Yat-sen University Cancer Center between May 2013 and October 2017. All the nodules was proven by ultrasound guided fine needle aspiration cytology or thyroidectomy. The CAD system was used to analyze the thyroid nodules, according to the categories defined by the K-TI-RADS, ATA, and ACR-TI-RADS guidelines. Using pathology as the gold standard, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of the CAD system. In addition, the differences of CAD diagnostic efficacy were compared among different thyroid nodule sizes and thyroid background.

Results

The area under the ROC curve (AUC) of the ACR-TI-RADS was higher than those of the K-TI-RADS (Z=3.026, P=0.0025) and ATA (Z=3.669, P<0.001). The sensitivity of the ACR-TI-RADS was better than that of the K-TI-RADS (P<0.001), and was comparable to that of the ATA (P=0.7123). Using 4C as the cutoff value, the K-TI-RADS demonstrated a significantly higher specificity than the ATA and ACR-TI-RADS (P<0.001). The size of thyroid nodules influenced the diagnostic efficacy of CAD. The AUCs of CAD in the 5~<10 mm and ≥20 mm group were higher than those in the 10~<15 mm and 15~<20 mm group (P<0.001). There was no significant difference in AUC of the CAD between the normal background and Hashimoto thyroiditis background groups (P=0.82).

Conclusion

The CAD system exhibits a better diagnostic efficacy based on the ACR-TI-RADS, and the size of thyroid nodules influences the diagnostic efficacy of CAD

Key words: Thyroid nodule, Ultrasonography, Computer aided diagnosis

Min Xu, Feng Han, Xiao Luo, Jianwei Wang, Wei Zheng, Zhixing Guo, Qingguang Lin, Anhua Li. Diagnostic efficacy of computer aided diagnosis system in differentiating benign and malignant thyroid nodules and its influencing factors[J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2019, 16(04): 252-256.

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URL: https://chaosheng.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1672-6448.2019.04.004

https://chaosheng.cma-cmc.com.cn/EN/Y2019/V16/I04/252

Figures/Tables 5

References 14

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组别	AUC	最佳诊断临界点	诊断准确性（%）	敏感度（%）	特异度（%）	阳性预测值（%）	阴性预测值（%）
K-TI-RADS	0.703	4c	64.79	63.98	66.23	77.21	50.70
ATA	0.693	高度可疑恶性	75.59	90.04	49.74	76.21	73.64
ACR-TI-RADS	0.743	7分	75.96	91.95	47.38	75.75	76.69

组别	AUC	最佳诊断临界点	诊断准确性（%）	敏感度（%）	特异度（%）	阳性预测值（%）	阴性预测值（%）
K-TI-RADS	0.703	4c	64.79	63.98	66.23	77.21	50.70
ATA	0.693	高度可疑恶性	75.59	90.04	49.74	76.21	73.64
ACR-TI-RADS	0.743	7分	75.96	91.95	47.38	75.75	76.69

结节最大径线（mm）	个数	敏感度（%）	特异度（%）	AUC
5~<10	129	94.68	20.00	0.747
10~<15	279	95.93	27.59	0.626
15~<20	205	93.87	38.10	0.731
≥20	452	84.88	57.49	0.747

结节最大径线（mm）	个数	敏感度（%）	特异度（%）	AUC
5~<10	129	94.68	20.00	0.747
10~<15	279	95.93	27.59	0.626
15~<20	205	93.87	38.10	0.731
≥20	452	84.88	57.49	0.747

甲状腺背景	结节数目	敏感度（%）	特异度（%）	AUC
正常甲状腺	960	91.43	47.40	0.743
桥本甲状腺炎	105	79.55	64.71	0.723

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