Department of Surgery, Medical Faculty, Duzce University, Duzce, Turkey.
Department of Surgery, Haydarpasa Numune Teaching Hospital, Health Sciences University, Istanbul, Turkey.
Acta Chir Belg. 2022 Jun;122(3):185-191. doi: 10.1080/00015458.2021.1894733. Epub 2021 Mar 30.
Motor function of the external branch of superior laryngeal nerve (EBSLN) is vital for voice quality. We studied the rate of EBSLN identification and integrity in the era of intraoperative neuromonitoring (IONM).
Anatomic and functional identification of 515 EBSLNs-at-risk was performed under the guidance of IONM that motor integrity was electrophysiologically checked. The functional integrity was assessed with crico-thyroid muscle (CTM) twitches and/or recordable waveform amplitude. We tried to establish the systematic classification of EBSLN identification and integrity.
Visual, electrophysiological and total identification rates were 64.3%, 31.6% and 95.9%, respectively. We could identify 4.1% of EBSLNs neither anatomically nor electrophysiologically. We recorded CTM twitches alone or both CTM twitches and wave amplitude in 203(39.4%) and 291(56.5%) branches respectively. Identification features of EBSLNs were systematically classified under three main types: Visualized-monitored (1), non-visualized-monitored (2), unidentified (3), and electrophysiological integrity of EBSLNs under two subtypes: CTM twitches alone (a) and CTM twitches and wave amplitude (b).
Dedicated thyroid surgeon could visually identify EBSLNs. IONM contribution significantly increases the identification rate. Systematic classification of identification and electrophysiological integrity of EBSLNs may increase comprehensive knowledge about its motor function that is crucial for complication-free thyroidectomy.
喉上神经外支(EBSLN)的运动功能对于嗓音质量至关重要。我们研究了在术中神经监测(IONM)时代 EBSLN 识别和完整性的比率。
在 IONM 的指导下对 515 条有风险的 EBSLN 进行解剖和功能识别,通过电生理检查确认运动完整性。通过环甲肌(CTM)抽搐和/或可记录的波幅来评估功能完整性。我们试图建立 EBSLN 识别和完整性的系统分类。
视觉、电生理和总识别率分别为 64.3%、31.6%和 95.9%。我们可以识别出 4.1%的 EBSLN 既没有解剖学上也没有电生理学上的识别。我们分别在 203(39.4%)和 291(56.5%)支中记录到 CTM 抽搐单独或 CTM 抽搐和波幅。EBSLN 的识别特征系统地分为三类:可视化监测(1)、非可视化监测(2)、未识别(3),EBSLN 的电生理完整性分为两种亚型:CTM 抽搐单独(a)和 CTM 抽搐和波幅(b)。
专业的甲状腺外科医生可以通过视觉识别 EBSLN。IONM 的贡献显著提高了识别率。EBSLN 识别和电生理完整性的系统分类可能会增加对其运动功能的全面了解,这对无并发症的甲状腺切除术至关重要。