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.

中文翻译：

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一种通过近红外光谱客观、快速、准确地评估烧伤深度的新方法

烧伤深度的准确和客观评估是烧伤创面护理中的一项重大挑战。在这里，我们使用近红外光谱 (NIRS) 技术来测量离体猪模型中不同深度的热烧伤。基于光谱信号的强度和漫反射理论，我们提取了反映烧伤深度变化的功能（总血红蛋白和水含量）和结构（组织散射尺寸和散射颗粒）特征所涉及的光学参数。接下来，我们应用支持向量回归来构建包含光学特性参数和烧伤深度的模型。最后，我们在组织学上验证了通过 NIRS 收集的烧伤深度数据。结果表明，我们的反演模型平均可以达到7.63%左右的相对误差，而 NIRS 技术的诊断精度在 50 μm 范围内。这种新技术首次客观、准确地为医生提供实时烧伤深度信息。