Khatun Rokeya, Okura Kaisei, Parvez Md Anowar, Yashiro Kazuhiro, Nagahama Yuki, Tsunoi Yasuyuki, Kawauchi Satoko, Saitoh Daizoh, Sato Shunichi, Nishidate Izumi
Tokyo University of Agriculture and Technology, Graduate School of Bio-Applications and Systems Engineering, Tokyo, Japan.
Tokyo University of Agriculture and Technology, Department of Biomedical Engineering, Tokyo, Japan.
J Biomed Opt. 2025 Mar;30(3):036006. doi: 10.1117/1.JBO.30.3.036006. Epub 2025 Mar 24.
Burn injuries are a global public health problem and are estimated to cause more than 150,000 deaths annually. Even non-fatal burns result in prolonged hospitalization, disfigurement, and disability. The depth of the burn injury is crucial information for selecting adequate treatment for burns. The most common, convenient, and widely used method for assessing burn severity is visual examination, but the accuracy of this method is insufficient, at only 60% to 75%. Rapid and accurate assessment of burn severity is critical for optimal management and treatment of burn patients. Methods of burn severity assessment that are inexpensive, simple, rapid, non-contact, and non-invasive are thus needed.
We aim to propose an approach to visualize the spatial distribution of burn severity using hemoglobin parameters estimated from a snapshot red-green-blue (RGB) color image and to demonstrate the feasibility of this proposed approach for differentiating burn severity in a rat model of scald burn injury.
The approach to creating a spatial map of burn severity was based on canonical discriminant analysis (CDA) of total hemoglobin concentration, tissue oxygen saturation, and methemoglobin saturation as estimated from RGB color images. Burns of two different degrees of severity were created in rat dorsal skin by 10-s exposure to water maintained at 70°C and 78°C. RGB color images for the dorsal regions were acquired under anesthesia before burn injury and at 24, 48, and 72 h after injury.
Most areas of images in the groups with skin exposed to 70°C, 78°C, and 37°C water were classified as 70°C burn, 78°C burn, and non-burned normal skin, respectively, over 48 to 72 h. In contrast, classification images of the skin group exposed to 70°C water for 24 h showed a mixture of non-burned normal skin and 70°C burned areas, suggesting that burn severity was heterogeneous.
The proposed approach combining RGB color imaging and CDA appears promising for differentiating 78°C burns from 70°C burns and non-burned normal skin and non-burned normal skin from 70°C and 78°C burns at 24 to 72 h after burn injury in a rat model of scald burn injury.
烧伤是一个全球性的公共卫生问题，据估计每年导致超过15万人死亡。即使是非致命性烧伤也会导致长期住院、毁容和残疾。烧伤深度是选择合适烧伤治疗方法的关键信息。评估烧伤严重程度最常用、便捷且广泛使用的方法是目视检查，但该方法的准确性不足，仅为60%至75%。快速准确地评估烧伤严重程度对于烧伤患者的最佳管理和治疗至关重要。因此，需要廉价、简单、快速、非接触且非侵入性的烧伤严重程度评估方法。
我们旨在提出一种利用从快照红-绿-蓝（RGB）彩色图像估计的血红蛋白参数来可视化烧伤严重程度空间分布的方法，并证明该方法在烫伤大鼠模型中区分烧伤严重程度的可行性。
创建烧伤严重程度空间图的方法基于对从RGB彩色图像估计的总血红蛋白浓度、组织氧饱和度和高铁血红蛋白饱和度进行典型判别分析（CDA）。通过将大鼠背部皮肤暴露于70°C和78°C的水中10秒，造成两种不同严重程度的烧伤。在烧伤前以及伤后24、48和72小时，在麻醉状态下采集背部区域的RGB彩色图像。
在48至72小时内，皮肤暴露于70°C、78°C和37°C水的组中，图像的大多数区域分别被分类为70°C烧伤、78°C烧伤和未烧伤的正常皮肤。相比之下，皮肤暴露于70°C水24小时的组的分类图像显示未烧伤的正常皮肤和70°C烧伤区域混合存在，这表明烧伤严重程度存在异质性。
在烫伤大鼠模型中，所提出的结合RGB彩色成像和CDA的方法在烧伤后24至72小时区分78°C烧伤与70°C烧伤以及未烧伤的正常皮肤，以及区分未烧伤的正常皮肤与70°C和78°C烧伤方面似乎很有前景。
