The accurate and objective evaluation of burn depth is a significant challenge in burn wound care. Herein, we used near infrared spectroscopy (NIRS) technology to measure the different depth of thermal burns in ex vivo porcine models. Based on the intensity of the spectral signals and the diffuse reflection theory, we extracted the optical parameters involved in functional (total hemoglobin and water content) and structural (tissue scattered size and scattered particles) features that reflect the changes in burn depth. Next, we applied support vector regression to construct a model including the optical property parameters and the burn depth. Finally, we histologically verified the burn depth data collected via NIRS. The results showed that our inversion model could achieve an average relative error of about 7.63%, while the NIRS technology diagnostic accuracy was in the range of 50 μm. For the first time, this novel technique provides physicians with real-time burn depth information objectively and accurately.
Keywords: Burn depth; Near infrared spectroscopy; Support vector regression.
© The Author(s) 2021. Published by Oxford University Press.