Validation of a semi-quantitative scoring system and workflow for analysis of fluorescence quantification in companion animals - Ram, Ann S.; Matuszewska, Kathy; McKenna, Charly; Petrik, Jim; Oblak, Michelle L. (Frontiers in Veterinary Science, 2024)
Significance: Many commercially available near-infrared (NIR) fluorescence imaging systems lack algorithms for real-time quantifiable fluorescence data. Creation of a workflow for clinical assessment and post hoc analysis may provide clinical researchers with a method for intraoperative fluorescence quantification to improve objective outcome measures.Aim: Scoring systems and verified image analysis are employed to determine the amount and intensity of fluorescence within surgical specimens both intra and postoperatively.Approach: Lymph nodes from canine cancer patients were obtained during lymph node extirpation following peritumoral injection of indocyanine green (ICG). First, a semi-quantitative assessment of surface fluorescence was evaluated. Images obtained with a NIR exoscope were analysed to determine fluorescence thresholds and measure fluorescence amount and intensity.Results: Post hoc fluorescence quantification (threshold of Hue = 165-180, Intensity = 30-255) displayed strong agreement with semi-quantitative scoring (k = 0.9734, p < 0.0001). Fluorescence intensity with either threshold of 35-255 or 45-255 were significant predictors of fluorescence and had high sensitivity and specificity (p < 0.05). Fluorescence intensity and quantification had a strong association (p < 0.001).The validation of the semi-quantitative scoring system by image analysis provides a method for objective in situ observation of tissue fluorescence. The utilization of thresholding for ICG fluorescence intensity allows post hoc quantification of fluorescence when not built into the imaging system.Indocyanine green (ICG) is a frequently reported fluorescent agent utilized for intraoperative sentinel lymph node (SLN) mapping and tumour bed imaging 1-3 due to its high signal-to-Formatted: Font: Italic