Introduction: Burn care is a highly specialized area of medicine challenged by wounds of diverse severity and patients with equally diverse confounding illness or injuries impacting healing. Even burn experts are only 77% accurate in their burn depth assessment (BDA) leaving almost a quarter of patients to undergo unnecessary surgery or conversely suffer a delay in treatment. To aid clinicians in BDA, new technologies are being studied with machine learning algorithms calibrated to histologic standards. Unfortunately, histologic assessment is rarely done in burn care and can be discordant with visual assessment. Our goal was to review and assess the largest burn wound biopsy library and submit a burn biopsy algorithm (BBA) for categorizing BDA based-upon histologic analysis as a work-in-progress.

Methods: The study was an IRB-approved, prospective, multicenter design with multiple wounds per patient. Patients with burn wounds assessed by the burn expert as unlikely to heal and require excision and autograft were enrolled with 4mm biopsies procured every 25cm2. Burn biopsies were assessed histologically following hematoxylin and eosin staining by a board-certified dermatopathologist for presence or absence of epidermis, papillary dermis, and adnexal necrosis.

Results: At the time of submission, 65 patients were enrolled with 117 wounds and 487 biopsies. The burn biopsy algorithm was used to categorize 100% of the patients into four different categories. Still photos were obtained at the time of enrollment and before excision intraoperatively. The first two were likely to heal and note require excision and labeled 1st degree or Superficial 2nd degree. The last two were assessed unlikely to heal within 21 days and labeled deep 2nd degree or 3rd degree burn wounds.

Conclusions:  Our study demonstrates that a BBA with objective histologic criteria can be used to categorize BDA. Clinical intrigue regarding regenerative capacity remains an intrinsic component of this research that will hopefully be answered with additional data analysis as a component of the on-going study. This study serves as the largest analysis of burn biopsies by modern day burn experts and as a the first to define histologic parameters for BDA.