Ultrasound in medicine & biology · 2025
Which Intraoperative Monitoring Method More Accurately Predicts Voice Change After Thyroid Nodule Ablation: Transcutaneous Laryngeal Ultrasonography Versus Subjective Voice Assessment.
СтатьяСравнительное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Guo Xiaomin, Zheng Bowen, Wang Jinfen, Wu Tao, Yin Tinghui, Lian Yufan, Tan Lei, Ma Yanping, Guo Rui, He Yuting, Ren Jie
Аннотация
OBJECTIVE: Although subjective voice assessment (SVA) is recommended for the safety of thermal ablation (TA) for thyroid nodules (TNs), it is not reliable enough to predict voice quality. Transcutaneous laryngeal ultrasonography (TLUSG) can directly detect vocal cord mobility; however, only limited data on TA are available. Our aim was to determine a better method for predicting voice change after TA by comparing SVA and TLUSG.
METHODS: A total of 504 patients receiving TA for TNs were included. Both SVA and TLUSG were performed during the TA. Other clinical data were also collected.
RESULTS: Thirty-one patients (6.2%) showed a voice change at 1 d, and 19 patients (3.8%) continued to have symptoms at 1 mo after TA. The accuracy of TLUSG in predicting voice change was higher, with areas under the receiver operating characteristics curves (AUROCs) of 0.972 at 1 d and 0.956 at 1 mo, compared with that of SVA (0.853 at 1 d and 0.880 at 1 mo, both p < 0.05). When considering a single assessment method, four models are established. TLUSG models had higher AUROCs of 0.936 at 1 d and 0.986 at 1 mo, compared with that of SVA models (0.895 at 1 d and 0.941 at 1 mo, both p < 0.05). In addition, decision curve analysis indicated that TLUSG models had a better clinical net benefit than SVA models.
CONCLUSION: TLUSG demonstrated higher accuracy than SVA in predicting voice change after TA for TNs. Considering both methods' advantages, a comprehensive protocol combining both SVA and TLUSG could be suggested.
METHODS: A total of 504 patients receiving TA for TNs were included. Both SVA and TLUSG were performed during the TA. Other clinical data were also collected.
RESULTS: Thirty-one patients (6.2%) showed a voice change at 1 d, and 19 patients (3.8%) continued to have symptoms at 1 mo after TA. The accuracy of TLUSG in predicting voice change was higher, with areas under the receiver operating characteristics curves (AUROCs) of 0.972 at 1 d and 0.956 at 1 mo, compared with that of SVA (0.853 at 1 d and 0.880 at 1 mo, both p < 0.05). When considering a single assessment method, four models are established. TLUSG models had higher AUROCs of 0.936 at 1 d and 0.986 at 1 mo, compared with that of SVA models (0.895 at 1 d and 0.941 at 1 mo, both p < 0.05). In addition, decision curve analysis indicated that TLUSG models had a better clinical net benefit than SVA models.
CONCLUSION: TLUSG demonstrated higher accuracy than SVA in predicting voice change after TA for TNs. Considering both methods' advantages, a comprehensive protocol combining both SVA and TLUSG could be suggested.