Comparison between multispectral imaging and laser Doppler imaging to predict burn wound requirements for surgery.

Background: Burn injuries significantly impact quality of life and physical functionality. Early, accurate evaluation of burn wounds is essential, yet assessing burns remains a challenge, especially for non-specialists. This pilot study examines the efficacy of an AI-powered diagnostic tool using multispectral imaging (MSI) to help medical teams determine whether conservative or surgical management is required for burn wounds.

Methods: Thirty-one acute burn wounds in adult patients (within 7 days of injury) were assessed at a super-regional burn center. Clinical examinations were performed by an experienced burn doctor, with two adjunct devices used: the AI-driven MSI DeepView SnapShot Imaging (Version 1.0.1) and the Moor Laser Doppler Imaging (LDI) device, as per NICE recommendations. Wounds on the face, hands, feet, and genitals were excluded. Predictive outcomes from MSI and LDI were compared to final clinical management decisions.

Results: MSI predicted clinical outcomes in 58 % of cases, while LDI achieved 90 % accuracy. Concordance between MSI and LDI was observed in 52 % of cases, with a statistically significant difference between their outcomes (McNemar's test p = 0.012).

Conclusion: This study highlights the potential of AI in burn wound management. However, the binary classification of current AI models may not fully address the complexities of burn healing. The observed accuracy suggests limitations in AI's ability to capture the multifactorial nature of burn wounds, indicating the need for further refinement and collaboration with clinical expertise.