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改良TI-RADS联合BRAFV600E可提高甲状腺乳头状癌的诊断效率:前瞻性研究

Modified TI-RADS Coupled with BRAFV600E Enhances Diagnostic Efficiency in Papillary Thyroid Carcinoma: Prospective Study.

作者信息

Wang Jing, Cheng Hong, Li Xu

机构信息

Department of Ultrasound, Bishan Hospital of Chongqing, Bishan Hospital of Chongqing Medical University, Chongqing, 402760, People's Republic of China.

出版信息

Int J Gen Med. 2024 Jul 10;17:3015-3025. doi: 10.2147/IJGM.S456820. eCollection 2024.

Abstract

BACKGROUND

Thyroid disorders, relatively common diseases of the endocrine system, have risen gradually in recent years. Early detection and accurate diagnosis of thyroid cancer hold exceptional importance. This study aimed to determine the efficacy of a modified TI-RADS and BRAFV600E mutation testing for thyroid cancer (PTC) diagnosis.

METHODS

Ninety five thyroid nodules (48 benign and 47 malignant) from 81 patients were examined using Kwak Thyroid Imaging Reporting and Data System (TI-RADS) were subjected to shear wave elasticity (SWE), BRAFV600E genotyping and fine needle aspiration (FNA) cytology.

RESULTS

The modified TI-RADS exhibited superior diagnostic accuracy compared to TI-RADS in differentiating benign nodules from malignant thyroid nodules. Moreover, the AUC of modified TI-RADS in conjunction with BRAFV600E was the highest at 95% CI (0.898-0.992, p=0.003), surpassing other diagnostic methods in enhanced sensitivity and maintaining high specificity.

CONCLUSION

The diagnostic efficiency of this combination surpassed that of individual diagnostic methods.

摘要

背景

甲状腺疾病是内分泌系统中相对常见的疾病,近年来呈逐渐上升趋势。甲状腺癌的早期检测和准确诊断尤为重要。本研究旨在确定改良的甲状腺影像报告和数据系统(TI-RADS)及BRAFV600E突变检测对甲状腺癌(PTC)诊断的有效性。

方法

对81例患者的95个甲状腺结节(48个良性和47个恶性)采用Kwak甲状腺影像报告和数据系统(TI-RADS)进行检查,并进行剪切波弹性成像(SWE)、BRAFV600E基因分型和细针穿刺(FNA)细胞学检查。

结果

在区分良性结节与恶性甲状腺结节方面,改良的TI-RADS比TI-RADS表现出更高的诊断准确性。此外,改良的TI-RADS联合BRAFV600E的曲线下面积(AUC)在95%置信区间最高,为(0.898 - 0.992,p = 0.003),在提高敏感性和保持高特异性方面超过了其他诊断方法。

结论

这种联合诊断方法的诊断效率超过了单一诊断方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/343b/11246655/9cbd9095d25e/IJGM-17-3015-g0001.jpg

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