Can computer vision algorithms facilitate accurate percent total body surface area (%TBSA) burn computation across the wide body habitus spectrum of the modern population?
In this cohort study, 3-dimensional image segmentation of 3047 adult laser body scans were integrated into a mobile application that computes %TBSA burn based on exact burn injury pattern, sex, and body habitus. There is wide individual variability in how much each body region contributes to %TBSA, and the tool developed in this study reflects measured body surface areas of adults across the wide body habitus spectrum of the modern population.
An intuitive, accurate, and practical mobile application may be an improvement over existing one-size-fits-all models for computing %TBSA burn, a foundational estimate for burn injury management.
Critical burn management decisions rely on accurate percent total body surface area (%TBSA) burn estimation. Existing %TBSA burn estimation models (eg, Lund-Browder chart and rule of nines) were derived from a linear formula and a limited number of individuals a century ago and do not reflect the range of body habitus of the modern population.
To develop a practical %TBSA burn estimation tool that accounts for exact burn injury pattern, sex, and body habitus.
Design, Setting, and Participants
This population-based cohort study evaluated the efficacy of a computer vision algorithm application in processing an adult laser body scan data set. High-resolution surface anthropometry laser body scans of 3047 North American and European adults aged 18 to 65 years from the Civilian American and European Surface Anthropometry Resource data set (1998-2001) were included. Of these, 1517 participants (49.8%) were male. Race and ethnicity data were not available for analysis. Analyses were conducted in 2020.
Main Outcomes and Measures
The contributory %TBSA for 18 body regions in each individual. Mobile application for real-time %TBSA burn computation based on sex, habitus, and exact burn injury pattern.
Of the 3047 individuals aged 18 to 65 years for whom body scans were available, 1517 (49.8%) were male. Wide individual variability was found in the extent to which major body regions contributed to %TBSA, especially in the torso and legs. Anterior torso %TBSA increased with increasing body habitus (mean [SD], 15.1 [0.9] to 19.1 [2.0] for male individuals; 15.1 [0.8] to 18.0 [1.7] for female individuals). This increase was attributable to increase in abdomen %TBSA (mean [SD], 5.3 [0.7] to 8.7 [1.8]) among male individuals and increase in abdomen (mean [SD], 4.6 [0.6] to 6.8 [1.7]) and pelvis (mean [SD], 1.5 [0.2] to 2.9 [0.9]) %TBSAs among female individuals. For most body regions, Lund-Browder chart and rule of nines estimates fell outside the population’s measured interquartile ranges. The mobile application tested in this study, Burn Area, facilitated accurate %TBSA burn computation based on exact burn injury pattern for 10 sex and body habitus-specific models.
Conclusions and Relevance
Computer vision algorithm application to a large laser body scan data set may provide a practical tool that facilitates accurate %TBSA burn computation in the modern era.
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Choi J, Patil A, Vendrow E, et al. Practical Computer Vision Application to Compute Total Body Surface Area Burn: Reappraising a Fundamental Burn Injury Formula in the Modern Era. JAMA Surg. Published online November 24, 2021. doi:10.1001/jamasurg.2021.5848
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