No abstract

The diagnosis of burn depth is based on a visual assessment and can be subjective. Near-infrared (NIR) spectroscopic devices were used preclinically with positive results. The purpose of this study was to test the devices in a clinical setting using easily identifiable burn wounds. Adult patients with acute superficial and full-thickness burns were enrolled. NIR point spectroscopy and imaging devices were used to collect hemodynamic data from the burn site and an adjacent unburned control site. Oxy-hemoglobin and deoxy-hemoglobin concentrations were extracted from spectroscopic data and reported as oxygen saturation and total hemoglobin. Sixteen patients (n=16) were included in the study with equal numbers in both burn wound groups. Point spectroscopy data showed an increase in oxygen saturation (p<0.0095) and total hemoglobin (<0.0001) in comparison with the respective control areas for superficial burn wounds. The opposite was true for full-thickness burns, which showed a decrease in oxygenation (p<0.0001) and total hemoglobin (p<0.0147) in comparison with control areas. NIR imaging technology provides an estimate of hemodynamic parameters and could easily distinguish superficial and full-thickness burn wounds. These results confirm that NIR devices can successfully distinguish superficial and full-thickness burn injuries.

Early surgical management of those burn injuries that will not heal spontaneously is critical. The decision to excise and graft is based on a visual assessment that is often inaccurate but yet continues to be the primary means of grading the injury. Superficial and intermediate partial-thickness injuries generally heal with appropriate wound care while deep partial- and full-thickness injuries generally require surgery. This study explores the possibility of using near-infrared spectroscopy to provide an objective and accurate means of distinguishing shallow injuries from deeper burns that require surgery. Twenty burn injuries are studied in five animals, with burns covering <1% of the total body surface area. Carefully controlled superficial, intermediate, and deep partial-thickness injuries as well as full-thickness injuries could be studied with this model. Near-infrared reflectance spectroscopy was used to evaluate these injuries 1 to 3 hours after the insult. A probabilistic model employing partial least-squares logistic regression was used to determine the degree of injury, shallow (superficial or intermediate partial) from deep (deep partial and full thickness), based on the reflectance spectrum of the wound. A leave-animal-out cross-validation strategy was used to test the predictive ability of a 2-latent variable, partial least-squares logistic regression model to distinguish deep burn injuries from shallow injuries. The model displayed reasonable ranking quality as summarized by the area under the receiver operator characteristics curve, AUC = 0.879. Fixing the threshold for the class boundaries at 0.5 probability, the model sensitivity (true positive fraction) to separate deep from shallow burns was 0.90, while model specificity (true negative fraction) was 0.83. Using an acute porcine model of thermal burn injuries, the potential of near-infrared spectroscopy to distinguish between shallow healing burns and deeper burn injuries was demonstrated. While these results should be considered as preliminary and require clinical validation, a probabilistic model capable of differentiating these classes of burns would be a significant aid to the burn specialist.

Near-infrared reflectance spectroscopic imaging is demonstrated to be a powerful augmentation to the standard clinical assessment of skin.