Abstract
Objective. To investigate the feasibility of near-infrared autofluorescence (AF) and indocyanine green (ICG) fluorescence to identify parathyroid glands intraoperatively. Methods. Fluorescence imaging was carried out during open parathyroid and thyroid surgery. After visual identification, parathyroid glands were exposed to near-infrared (NIR) light with a wavelength between 690 and 770 nm. The camera of the Storz (R) NIR/ICG endoscopic system used detects NIR light as a blue signal. Therefore, parathyroid AF was expected to be displayed in the blue color channel in contrast to the surrounding tissue. Following AF imaging, a bolus of 5 mg ICG was applied intravenously. ICG fluorescence was detected using the same NIR/ICG imaging system. Well-vascularized parathyroid glands were expected to show a strong fluorescence in contrast to surrounding lymphatic and adipose tissue. Results. We investigated 78 parathyroid glands from 50 patients. 64 parathyroid glands (82%) displayed AF showing the typical bluish violet color. 63 parathyroid glands (81%) showed a strong and persistent fluorescence after application of ICG. The sensitivity of identifying a parathyroid gland by AF was 82% (64 true positive and 14 false negative results), while ICG imaging showed a sensitivity of 81% (63 true positive and 15 false negative results). The Fisher exact test revealed no significant difference between both groups at p < 0.05. Neither lymph nodes nor adipose tissue revealed substantial AF or ICG fluorescence. Conclusion. AF and ICG fluorescence reveal a high degree of sensitivity in identifying parathyroid glands. Further, ICG imaging facilitates the assessment of parathyroid perfusion. However, in the current setting both techniques are not suitable as screening tools to identify parathyroid glands at an early stage of the operation.
Dokumententyp: | Zeitschriftenartikel |
---|---|
Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-79130-0 |
ISSN: | 1687-8337 |
Sprache: | Englisch |
Dokumenten ID: | 79130 |
Datum der Veröffentlichung auf Open Access LMU: | 15. Dez. 2021, 14:47 |
Letzte Änderungen: | 11. Jan. 2023, 08:52 |