A Practical Noncontact Model to Create Standardized Experimental Burn Wounds of Any Thickness: Blue Beam Laser Pointer for Burn Induction

Segmentation and quantitative analysis of optical coherence tomography (OCT) images of laser burned skin based on deep learning

Evaluation of skin recovery is an important step in the treatment of burns. However, conventional methods only observe the surface of the skin and cannot quantify the injury volume. Optical coherence tomography (OCT) is a non-invasive, non-contact, real-time technique. Swept source OCT uses near infrared light and analyzes the intensity of light echo at different depths to generate images from optical interference signals. To quantify the dynamic recovery of skin burns over time, laser induced skin burns in mice were evaluated using deep learning of Swept source OCT images. A laser-induced mouse skin thermal injury model was established in thirty Kunming mice, and OCT images of normal and burned areas of mouse skin were acquired at day 0, day 1, day 3, day 7, and day 14 after laser irradiation. This resulted in 7000 normal and 1400 burn B-scan images which were divided into training, validation, and test sets at 8:1.5:0.5 ratio for the normal data and 8:1:1 for the burn data. Normal images were manually annotated, and the deep learning U-Net model (verified with PSPNe and HRNet models) was used to segment the skin into three layers: the dermal epidermal layer, subcutaneous fat layer, and muscle layer. For the burn images, the models were trained to segment just the damaged area. Three-dimensional reconstruction technology was then used to reconstruct the damaged tissue and calculate the damaged tissue volume. The average IoU value and f-score of the normal tissue layer U-Net segmentation model were 0.876 and 0.934 respectively. The IoU value of the burn area segmentation model reached 0.907 and f-score value reached 0.951. Compared with manual labeling, the U-Net model was faster with higher accuracy for skin stratification. OCT and U-Net segmentation can provide rapid and accurate analysis of tissue changes and clinical guidance in the treatment of burns.

A New Ex Vivo Human Skin Burn Model

Currently, most burn models for preclinical testing are on animals. For obvious ethical, anatomical, and physiological reasons, these models could be replaced with optimized ex vivo systems. The creation of a burn model on human skin using a pulsed dye laser could represent a relevant model for preclinical research. Six samples of excess human abdominal skin were obtained within one hour after surgery. Burn injuries were induced on small samples of cleaned skin using a pulsed dye laser on skin samples, at varying fluences, pulse numbers and illumination duration. In total, 70 burn injuries were performed on skin ex vivo before being histologically and dermato-pathologically analyzed. Irradiated burned skin samples were classified with a specified code representing burn degrees. Then, a selection of samples was inspected after 14 and 21 days to assess their capacity to heal spontaneously and re-epithelize. We determined the parameters of a pulsed dye laser inducing first, second, and third degree burns on human skin and with fixed parameters, especially superficial and deep second degree burns. After 21 days with the ex vivo model, neo-epidermis was formed. Our results showed that this simple, rapid, user-independent process creates reproducible and uniform burns of different, predictable degrees that are close to clinical reality. Human skin ex vivo models can be an alternative to and complete animal experimentation, particularly for preclinical large screening. This model could be used to foster the testing of new treatments on standardized degrees of burn injuries and thus improve therapeutic strategies.

Experimental models for controlled burn injuries in rats: a systematic analysis of original methods and burn devices

AIM

Despite a wide variety of models found in literature, choosing the right one can be difficult as many of them are lacking precise methodology. This study aims to analyze and compare original burn models in terms of burn device and technique, parameters, and wound depth assessment.

METHODS

A systematic search was performed according to PRISMA guidelines on studies describing original experimental burn models in rats. The adapted PICO formula and ARRIVE checklist were followed for inclusion and assessment of quality of studies. Characteristics of animals, burn technique, burn parameters and method of histological confirmation of burn depth were recorded.

RESULTS

Twenty-seven studies were included in the final analysis. Most studies used direct contact with skin for burn infliction (n=20). The rat's dorsum was the most common site (n=18). Ten studies used manually controlled burn devices, while ten designed automatic burn devices with control over temperature (n=10), exposure time (n=5), and pressure (n=5). Most studies (n=7) used a single biopsy taken from the center of the wound to confirm burn depth immediately after burn infliction.

CONCLUSION

From the wide variety of burn models in current literature, our study provides an overview of the most relevant experimental burn models in rats aiding researchers to understand what needs to be addressed when designing their burn protocol. Models cannot be compared as burn parameters variate significantly. Assessment of burn depth should be done in a standardized, sequential fashion in future burn studies to increase reproducibility.

Coming to Consensus: What Defines Deep Partial Thickness Burn Injuries in Porcine Models?

Deep partial thickness burns are clinically prevalent and difficult to diagnose. In order to develop methods to assess burn depth and therapies to treat deep partial thickness burns, reliable, accurate animal models are needed. The variety of animal models in the literature and the lack of precise details reported for the experimental procedures make comparison of research between investigators challenging and ultimately affect translation to patients. They sought to compare deep partial thickness porcine burn models from five well-established laboratories. In doing so, they uncovered a lack of consistency in approaches to the evaluation of burn injury depth that was present within and among various models. They then used an iterative process to develop a scoring rubric with an educational component to facilitate burn injury depth evaluation that improved reliability of the scoring. Using the developed rubric to re-score the five burn models, they found that all models created a deep partial thickness injury and that agreement about specific characteristics identified on histological staining was improved. Finally, they present consensus statements on the evaluation and interpretation of the microanatomy of deep partial thickness burns in pigs.