Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University Cancer Center, Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Tongji University School of Medicine, Shanghai, China.
Department of Medical Ultrasound, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China.
Clin Hemorheol Microcirc. 2021;77(3):273-285. doi: 10.3233/CH-200985.
To propose a diagnostic algorithm for improving the diagnosis of atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS) thyroid nodules.
This study retrospectively enrolled 77 consecutive patients with 81 AUS/FLUS nodules who underwent preoperative BRAFV600E mutation analysis. A new diagnostic algorithm was proposed that BRAFV600E mutation analysis for the Fine-needle aspiration cytology specimen was firstly carried out, in which positive BRAFV600E mutation indicated malignancy and classification of the nodules with negative BRAFV600E mutation was further performed based on ultrasound pattern-based risk stratification of American Thyroid Association Guidelines. The diagnostic performance of the new diagnostic algorithm was evaluated.
The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the receiver operating characteristic curve (AUROC) of new diagnostic algorithm were 94.6%, 84.0%, 91.4%, 86.9%, 90.1%, and 0.893, respectively. The proposed diagnostic algorithm significantly increased the diagnostic performances (AUROC: 0.893 vs. 0.837 and 0.795), sensitivity (94.6% vs. 71.4% and 75.0%), and accuracy (90.1% vs. 79.0% and 77.8%) compared with BRAFV600E mutation analysis alone and ultrasound pattern-based risk stratification alone (all P < 0.05).
The proposed diagnostic algorithm is helpful for improving the diagnosis of AUS/FLUS nodules, which might be as a routine approach.
提出一种诊断算法，以提高对意义不明的不典型性或滤泡性病变不典型性（AUS/FLUS）甲状腺结节的诊断。
本研究回顾性纳入了 77 例 81 个 AUS/FLUS 结节的连续患者，这些患者均进行了术前 BRAFV600E 突变分析。提出了一种新的诊断算法，首先对细针穿刺细胞学标本进行 BRAFV600E 突变分析，其中 BRAFV600E 突变阳性提示恶性，BRAFV600E 突变阴性的结节进一步根据美国甲状腺协会指南的超声模式风险分层进行分类。评估新诊断算法的诊断性能。
新诊断算法的敏感性、特异性、阳性预测值、阴性预测值、准确性和受试者工作特征曲线（AUROC）下面积分别为 94.6%、84.0%、91.4%、86.9%、90.1%和 0.893。与 BRAFV600E 突变分析和超声模式风险分层单独相比，新诊断算法显著提高了诊断性能（AUROC：0.893 比 0.837 和 0.795）、敏感性（94.6% 比 71.4% 和 75.0%）和准确性（90.1% 比 79.0% 和 77.8%）（均 P<0.05）。
所提出的诊断算法有助于提高 AUS/FLUS 结节的诊断，这可能成为一种常规方法。
