Changes in epithelial thickness during the healing of excised full‐thickness skin wounds

Winstanley, E. W.

doi:10.1002/path.1711140308

Cited by 7 publications

(4 citation statements)

References 7 publications

(4 reference statements)

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“…5D). The epidermis gradually thickened as healing progressed between days 3 and 10 ( P = 0.0156) following trends that have been observed in similar excisional models [38].…”

Section: Resultssupporting

confidence: 57%

“…5D). Following trends common in excisional wound models [38], the epidermis increased in thickness gradually over time between days 3 and 10 ( P = 0.002). Assessments of 3D wound geometry are rarely made in part because it is particularly burdensome and time‐consuming to perform manual segmentation of entire 3D stacks, but the ability of this CNN to generate maps of the epidermis made evaluations of thickness in 3D possible within only a few minutes.…”

Section: Discussionmentioning

confidence: 61%

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Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label‐Free Multiphoton Microscopy Using Convolutional Neural Networks

2021

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Background and Objectives Histological analysis is a gold standard technique for studying impaired skin wound healing. Label‐free multiphoton microscopy (MPM) can provide natural image contrast similar to histological sections and quantitative metabolic information using NADH and FAD autofluorescence. However, MPM analysis requires time‐intensive manual segmentation of specific wound tissue regions limiting the practicality and usage of the technology for monitoring wounds. The goal of this study was to train a series of convolutional neural networks (CNNs) to segment MPM images of skin wounds to automate image processing and quantification of wound geometry and metabolism. Study Design/Materials and Methods Two CNNs with a 4‐layer U‐Net architecture were trained to segment unstained skin wound tissue sections and in vivo z‐stacks of the wound edge. The wound section CNN used 380 distinct MPM images while the in vivo CNN used 5,848 with both image sets being randomly distributed to training, validation, and test sets following a 70%, 20%, and 10% split. The accuracy of each network was evaluated on the test set of images, and the effectiveness of automated measurement of wound geometry and optical redox ratio were compared with hand traced outputs of six unstained wound sections and 69 wound edge z‐stacks from eight mice. Results The MPM wound section CNN had an overall accuracy of 92.83%. Measurements of epidermal/dermal thickness, wound depth, wound width, and % re‐epithelialization were within 10% error when evaluated on six full wound sections from days 3, 5, and 10 post‐wounding that were not included in the training set. The in vivo wound z‐stack CNN had an overall accuracy of 89.66% and was able to isolate the wound edge epithelium in z‐stacks from eight mice across post‐wound time points to quantify the optical redox ratio within 5% of what was recorded by manual segmentations. Conclusion The CNNs trained and presented in this study can accurately segment MPM imaged wound sections and in vivo z‐stacks to enable automated and rapid calculation of wound geometry and metabolism. Although MPM is a noninvasive imaging modality well suited to imaging living wound tissue, its use has been limited by time‐intensive user segmentation. The use of CNNs for automated image segmentation demonstrate that it is possible for MPM to deliver near real‐time quantitative readouts of tissue structure and function. Lasers Surg. Med. © 2021 Wiley Periodicals LLC

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“…5D). The epidermis gradually thickened as healing progressed between days 3 and 10 ( P = 0.0156) following trends that have been observed in similar excisional models [38].…”

Section: Resultssupporting

confidence: 57%

Section: Discussionmentioning

confidence: 61%

Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label‐Free Multiphoton Microscopy Using Convolutional Neural Networks

2021

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“…Finally, the observed reduction in epithelium thickness suggests a reduced thickening of the wound border zone. Thickening in the border zone in nonhealing wound models in large animals has been linked to an overactivated wound closure mechanism that might lead to scarring …”

Section: Discussionmentioning

confidence: 99%

“…Thickening in the border zone in nonhealing wound models in large animals has been linked to an overactivated wound closure mechanism that might lead to scarring. 49…”

Section: ■ Discussionmentioning

confidence: 99%

Multifunctional Nano and Collagen-Based Therapeutic Materials for Skin Repair

Lazurko

Khatoon

Goel

et al. 2019

ACS Biomater. Sci. Eng.

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A novel strategy is needed for treating nonhealing wounds, which is able to simultaneously eradicate pathogenic bacteria and promote tissue regeneration. This would improve patient outcome and reduce the number of lower limb amputations. In this work, we present a multifunctional therapeutic approach able to control bacterial infections, provide a protective barrier to a full-thickness wound, and improve wound healing in a clinically relevant animal model. Our approach uses a nanoengineered antimicrobial nanoparticle for creating a sprayable layer onto the wound bed that prevents bacterial proliferation and also eradicates preformed biofilms. As a protective barrier for the wound, we developed a thermoresponsive collagen-based matrix that has prohealing properties and is able to fill wounds independent of their geometries. Our results indicate that using a combination of the matrix with full-thickness microscopic skin tissue columns synergistically contributed to faster and superior skin regeneration in a nonhealing wound model in diabetic mice.

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Scanning electron microscopy of epidermal cell migration in wound healing during limb regeneration in the adult newt, Notophthalmus viridescens

Repesh

Oberpriller

1978

Am. J. Anat.

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The epidermal cells which migrate over the wound surface of the amputated limb of the adult newt were examined using the scanning electron microscope. Specimens were prepared routinely for scanning electron microscopy or were embedded in Epon 812 for light microscopic observations. A cuff of epidermal cells was seen at the edge of the wound, from which cells appeared to migrate over the wound surface. As early as five hours after transection of the limb, the basal layers of this cuff appeared to send out pseudopodial projections. These seemed to establish a physical contact with a fibrin-like substratum, which apparently served as a means of support for the migrating cells. Subsequently, the epidermal cells became elongate and had the appearance of streaming toward the center of the wound. Between 10 and 13 hours post-amputation, the cells in the central region of the stump were rounded up and some possessed microappendages resembling microplicae and microvilli. Throughout the entire period of wound coverage, the cells seemed to maintain contact with the fibrin network, which appeared to be the first structural element of wound architecture. As a result of these observations, the mechanism by which the epidermal cells migrate has been clarified.

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Changes in epithelial thickness during the healing of excised full‐thickness skin wounds

Cited by 7 publications

References 7 publications

Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label‐Free Multiphoton Microscopy Using Convolutional Neural Networks

Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label‐Free Multiphoton Microscopy Using Convolutional Neural Networks

Multifunctional Nano and Collagen-Based Therapeutic Materials for Skin Repair

Scanning electron microscopy of epidermal cell migration in wound healing during limb regeneration in the adult newt, Notophthalmus viridescens

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