Diagnostic value of high-frequency ultrasound combined with fine needle aspiration cytology and BRAF gene for papillary thyroid microcarcinoma
BRAF diagnostic in PTMC
Keywords:
Papillary thyroid microcarcinoma, high-frequency ultrasound, fine needle aspiration cytology, BRAF gene, diagnostic valueAbstract
We attempted to evaluate clinical application value of high-frequency ultrasound (HFUS), fine needle aspiration cytology (FNAC), BRAF gene, and combination of HFUS, FNAC, and BRAF gene in diagnosing papillary thyroid microcarcinoma (PTMC). The 150 patients with thyroid minimal lesions who underwent HFUS, FNAC and BRAF gene testing before surgery in our hospital from June 2020 to December 2021 were selected as research subjects. Patients were divided into two groups based on postoperative pathological results. The consistency of diagnostic results of HFUS, FNAC, and BRAF gene and their combination with those of pathological examination, diagnostic efficacy of HFUS, FNAC and BRAF gene combined detection and individual detection for PTMC lymph node metastasis, and diagnostic value of HFUS, FNAC and BRAF gene combined detection and individual detection for PTMC lymph node metastasis received analysis and comparison. The consistency of diagnostic results of combined detection with pathological examination exhibited elevation relative to that of HFUS, FNAC and BRAF gene detection alone (P < 0.05). The negative predictive value, sensitivity and accuracy of combined detection exhibited elevation relative to individual detection (P < 0.05). The AUC of combined detection in diagnosing PTMC lymph node metastasis exhibited elevation relative to that of HFUS and BRAF gene alone (P < 0.05). HFUS combined with FNAC and BRAF genes possesses high diagnostic value, with high diagnostic sensitivity, specificity, and accuracy. Thus, combined detection for PTMC before surgery can accurately determine whether lymph node metastasis occurs, reduce occurrence of missed diagnosis and misdiagnosis, and thus improve diagnostic precision.
Published
Issue
Section
License
Copyright (c) 2024 Chuang Li, Xiaojuan Zhao, Jingge Zhao, Jing Zhao, Lemei An, Gang Wu
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.