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Updated: Jun 27, 2026

A Murine Model of a Burn Wound Reconstructed with an Allogeneic Skin Graft
Published on: August 8, 2020
Experimental Burn Induction in Laboratory Animals: A Scoping Review of Methods, Reproducibility, Operator-Dependent
Antonios Kyriakopoulos1, Michalis Katsimpoulas2, Vasilios Kyriakopoulos3
1Plastic Surgery Department, Evaggelismos General Hospital of Athens, 10676 Athens, Greece.
Background:
Experimental animal models remain central to burn research and soft-tissue reconstruction/repair, but method heterogeneity compromises reproducibility, comparability, and translation for depth/area endpoints.
Objective:
We aimed to map burn-induction methods and examine reproducibility, intentional depth modulation, wound-area stability, validation, and operator-dependent variability.
Methods:
A PRISMA-ScR review, informed by JBI guidance, was conducted without registration but with predefined questions, criteria, and charting domains. PubMed/MEDLINE, Scopus, Web of Science, Embase, and Google Scholar were searched from inception to 30 January 2026. Eligible studies were English peer-reviewed full-text original in vivo animal studies. Two reviewers independently screened records; one charted data, another checked it. Evidence was mapped by modality, exposure-control architecture, validation, and operator-sensitive steps.
Results:
Studies varied by species, modality, device design, exposure settings, and severity verification. Modalities were contact, scald, steam, and radiant/infrared. Wound area was more reproducible than depth, which depended on temperature, duration, force/pressure, geometry, equilibration, anatomical site, and assessment timing. Histopathology was the main standard, sometimes complemented by morphometry, optical, or perfusion techniques. Operator-sensitive variability involved force, alignment, contact stability, template integrity, exposure geometry, source stability/environmental control.
Conclusions:
Burn induction is a measurement-system problem; constraining operator-sensitive variables, predefined validation timing, and quantitative variability reporting may improve validity, comparability, and translation.

