Enhancing Recurrent Laryngeal Nerve Detection with Neural Autofluorescence in Thyroid Surgery
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FernandoDip
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ReneAleman
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Hector RDip
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AlbertoRancati
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GustavoEiben
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FedericoMarinelli
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JavierGhiselli
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DiegoSinagra
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JulioAleman
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Raul JRosenthal
BACKGROUND
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.
METHODS
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 and NUV light autofluorescence techniques.
RESULTS
Among the 614 patients, surgical indications included goiter (35%), well-differentiated thyroid carcinoma (20%), and thyroiditis (45%). A total of 1,230 RLN branches were identified using NUV light compared with 840 identified under conventional white light. NUV light autofluorescence demonstrated a sensitivity of 100% (95% CI 99.2 to 100) and specificity of 98.5% (95% CI 98.4 to 98.6) for RLN identification. Mean fluorescent light intensity for RLN (134.3 ± 12.7 pixels [px]) was significantly higher than that of the thyroid gland (33.7 ± 8.9 px) and adjacent tissues (14.4 ± 5.3 px; 1-way ANOVA: 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 well-differentiated thyroid carcinoma.
CONCLUSIONS
NUV light-based nerve autofluorescence offers high sensitivity and specificity for RLN identification during thyroidectomy, outperforming traditional methods. Its real-time, noninvasive nature and ability to enhance anatomical visualization may contribute to improved surgical outcomes and reduced nerve injury risk.