Near-Infrared Fluorescence Imaging in the Identification of Parathyroid Glands in Thyroidectomy

Objectives/Hypothesis To assess the ability of near-infrared fluorescence imaging (NIFI) to identify parathyroid glands (PGs) among histologically proven PG/non-PG specimens compared with a surgeon's visual acumen, and to determine NIFI sensitivity in detecting incidentally resected PGs from thyroidectomy specimens, compared to the surgeon's visual inspection. Study Design Prospective study. Methods With mean age of 61 years, 36 patients with various thyroid diseases were enrolled. Possible PGs (n = 28) and lymph nodes (n = 32) were identified by the experienced surgeon's visual inspection. Using NIFI, 15 PGs were further identified from thyroidectomy specimens. For these 75 specimens, the surgeon's judgments (PG vs. non-PG) were recorded. Histological evaluation was performed after examining the NIFI auto-fluorescence of each specimen. Results There were no significant differences in sensitivity, specificity, positive predictive value, and negative predictive value between the surgeon's visual inspection and NIFI in identifying PGs, with values of 100%/97.1%, 85.0%/87.5%, 85.4%/87.2%, and 100%/97.2%, respectively. The sensitivity of NIFI (82.9%) for detection of PGs from thyroidectomy specimens was significantly higher than that of the surgeon's visual inspection (61.0%). False negative specimens contained bleeding/congestion and/or encapsulation by thick tissues, whereas false positive specimens contained electrocoagulated tissues. Conclusions NIFI showed results comparable to the experienced surgeon's visual inspection in identifying PGs. This could benefit novice surgeons. NIFI may be useful for experienced surgeons to locate incidentally resected PGs within thyroidectomy specimens for auto-transplantation. Prevention of intra-gland bleeding and congestion, careful removal of thick capsules, and bloodless surgeries without electrocoagulation are important for reducing false positive and false negative results.Laryngoscope, 2020