Near-infrared auto-fluorescence spectroscopy combining with Fisher's linear discriminant analysis improves intraoperative real-time identification of normal parathyroid in thyroidectomy.

2020 
BACKGROUND: To evaluate the efficacy of a sensitive, real-time tool for identification and protection for parathyroid glands during thyroidectomy. METHODS: Near-infrared (NIR) auto-fluorescence was measured intraoperatively from 20 patients undergoing thyroidectomy. Spectra were measured from suspicious parathyroid glands and surrounding neck tissues during the operation with a NIR fluorescence system. Fast frozen sections were performed on the suspicious parathyroid glands. Accuracy was evaluated by comparison with histology and NIR identification. Data were attracted for Fisher's linear discriminant analysis. RESULTS: The auto-fluorescence intensity of parathyroid was significantly higher than that of thyroid, fat and lymph node. The peak intensity of auto-fluorescence from parathyroid was 5.55 times of that from thyroid at the corresponding wave number. Of the 20 patients, the parathyroid was accurately detected and identified in 19 patients by NIR system, compared with their histologic results. One suspicious parathyroid did not exhibit typical spectra, and was proved to be fat tissue by histology. The NIR auto-fluorescence method had a 100% sensitivity of parathyroid glands identification and a high accuracy of 95%. The positive predictive value was 95%. The parathyroid gland have specific auto-fluorescence spectrum and can be separated from the other three samples through the Fisher's linear discriminant analysis. CONCLUSIONS: NIR auto-fluorescence spectroscopy can accurately identify normal parathyroid gland during thyroidectomy. The Fisher's linear discriminant analysis demonstrated the specificity of the NIR auto-fluorescence of parathyroid tissue and its efficacy in parathyroid discrimination.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    30
    References
    11
    Citations
    NaN
    KQI
    []