Abstract
SIGNIFICANCE: Determining the depth of injury in burn wounds is critical to inform surgical decision-making and enhance outcomes. Clinical assessment yields poor accuracy in the early post-burn period, and histologic analysis of biopsies (the gold standard) is time-consuming and clinically unfeasible. Indocyanine green angiography (ICGA) has provided very promising results; however, the evidence is still limited, and the details on instrumentation, measurement setup, and data processing/analysis (when reported) are considerably heterogeneous. AIM: A processing and analysis pipeline was developed to interpret ICGA data from experimental burn studies in a way that provides objective, generalizable, and reproducible interpretation. APPROACH: Different burns were created on the dorsal aspect of adult pigs, and ICGA was performed. ICGA measurements were then compared with different processing steps. Features were extracted from the indocyanine green angiography (ICG) kinetics curves at specific regions of interests and ran individual and group analyses to decide on the wound severity. To this end, the features were analyzed both separately and groupwise. RESULTS: The repeatability of the study was enhanced by processing steps where ICG curves were normalized by their area under the curve (AUC). Peak value ( IMAX ), residual AUC (rAUC), mean transit time (MTT), full width at half maximum (FWHM), and ingress ( s1 ) and egress ( s2 ) slopes presented the strongest correlation with burn severity. MTT and FWHM were almost independent of the processing steps included in the pipeline, providing high reliability between imaging sessions and inter-subject comparisons. Superficial burns presented significantly higher IMAX , rAUC, s1 , and s2 , as well as lower FWHM, when compared with the ICG kinetics from normal tissue, whereas the contrary happens for deep burns. CONCLUSIONS: We highlight the utility of a pre-processing step and judicious choice of parameters to use when interpreting ICGA data from indeterminate depth burn wounds to maximize the accuracy in severity estimation.