Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
Korean J Radiol. 2020 Mar;21(3):369-376. doi: 10.3348/kjr.2019.0581.
To determine whether a computer-aided diagnosis (CAD) system for the evaluation of thyroid nodules is non-inferior to radiologists with different levels of experience.
Patients with thyroid nodules with a decisive diagnosis of benign or malignant nodule were consecutively enrolled from November 2017 to September 2018. Three radiologists with different levels of experience (1 month, 4 years, and 7 years) in thyroid ultrasound (US) reviewed the thyroid US with and without using the CAD system. Statistical analyses included non-inferiority testing of the diagnostic accuracy for malignant thyroid nodules between the CAD system and the three radiologists with a non-inferiority margin of 10%, comparison of the diagnostic performance, and the added value of the CAD system to the radiologists.
Altogether, 197 patients were included in the study cohort. The diagnostic accuracy of the CAD system (88.48%, 95% confidence interval [CI] = 82.65-92.53) was non-inferior to that of the radiologists with less experience (1 month and 4 year) of thyroid US (83.03%, 95% CI = 76.52-88.02; < 0.001), whereas it was inferior to that of the experienced radiologist (7 years) (95.76%, 95% CI = 91.37-97.96; = 0.138). The sensitivity and negative predictive value of the CAD system were significantly higher than those of the less-experienced radiologists were, whereas no significant difference was found with those of the experienced radiologist. A combination of US and the CAD system significantly improved sensitivity and negative predictive value, although the specificity and positive predictive value deteriorated for the less-experienced radiologists.
The CAD system may offer support for decision-making in the diagnosis of malignant thyroid nodules for operators who have less experience with thyroid US.
确定计算机辅助诊断（CAD）系统在评估甲状腺结节方面是否不劣于不同经验水平的放射科医生。
从 2017 年 11 月至 2018 年 9 月连续纳入具有明确良性或恶性结节诊断的甲状腺结节患者。3 名具有不同甲状腺超声（US）经验水平（1 个月、4 年和 7 年）的放射科医生在使用和不使用 CAD 系统的情况下对甲状腺 US 进行了回顾。统计分析包括 CAD 系统与经验较少的 3 名放射科医生（非劣效性边界为 10%）对恶性甲状腺结节的诊断准确性的非劣效性检验、诊断性能比较以及 CAD 系统对放射科医生的增值。
共有 197 名患者纳入研究队列。CAD 系统的诊断准确性（88.48%，95%置信区间[CI] = 82.65-92.53）不劣于经验较少的甲状腺 US 放射科医生（1 个月和 4 年）（83.03%，95% CI = 76.52-88.02；<0.001），但劣于经验丰富的放射科医生（7 年）（95.76%，95% CI = 91.37-97.96；=0.138）。CAD 系统的敏感性和阴性预测值显著高于经验较少的放射科医生，而与经验丰富的放射科医生无显著差异。US 与 CAD 系统的联合应用显著提高了敏感性和阴性预测值，尽管经验较少的放射科医生的特异性和阳性预测值有所恶化。
对于甲状腺 US 经验较少的操作人员，CAD 系统可为恶性甲状腺结节的诊断决策提供支持。
