Enhancing Recurrent Laryngeal Nerve Detection with Neural Autofluorescence in Thyroid Surgery.

Abstract

Recurrent laryngeal nerve (RLN) injury is a common and serious complication of thyroidectomy. This study evaluates the sensitivity and specificity of nerve autofluorescence using near-ultraviolet (NUV) light for RLN identification during thyroidectomy. A retrospective review of prospectively collected data was performed on 614 patients undergoing thyroidectomy for various indications. RLNs were identified using both conventional white light (CWL) and NUV light autofluorescence techniques. Among the 614 patients, surgical indications included goiter (35%), well-differentiated thyroid carcinoma (WDTC, 20%), and thyroiditis (45%). A total of 1,230 RLN branches were identified using NUV light, compared to 840 identified under CWL. NUV light autofluorescence demonstrated a sensitivity of 100% (95% CI:99.2-100) and specificity of 98.5% (95% CI: 98.4-98.6) for RLN identification. Mean fluorescent light intensity (FLI) for RLN (134.3 ± 12.7 pixels [px]) was significantly higher than that of thyroid gland (33.7 ± 8.9 px) and adjacent tissues (14.4 ± 5.3 px) (one-way ANOV: F=842.1, p<0.001). NUV imaging enabled enhanced visualization of anatomical variations of the RLN. A single case (0.2%) of transient unilateral RLN palsy was observed, occurring in a patient with WDTC. NUV light-based nerve autofluorescence offers high sensitivity and specificity for RLN identification during thyroidectomy, outperforming traditional methods. Its real-time, non-invasive nature and ability to enhance anatomical visualization may contribute to improved surgical outcomes and reduced nerve injury risk.