A system for 3D representation of burns and calculation of burnt skin area

Burns. 2011 Nov;37(7):1233-40. doi: 10.1016/j.burns.2011.05.018. Epub 2011 Jun 23.

Abstract

In this paper a computer-based system for burnt surface area estimation (BAI), is presented. First, a 3D model of a patient, adapted to age, weight, gender and constitution is created. On this 3D model, physicians represent both burns as well as burn depth allowing the burnt surface area to be automatically calculated by the system. Each patient models as well as photographs and burn area estimation can be stored. Therefore, these data can be included in the patient's clinical records for further review. Validation of this system was performed. In a first experiment, artificial known sized paper patches were attached to different parts of the body in 37 volunteers. A panel of 5 experts diagnosed the extent of the patches using the Rule of Nines. Besides, our system estimated the area of the "artificial burn". In order to validate the null hypothesis, Student's t-test was applied to collected data. In addition, intraclass correlation coefficient (ICC) was calculated and a value of 0.9918 was obtained, demonstrating that the reliability of the program in calculating the area is of 99%. In a second experiment, the burnt skin areas of 80 patients were calculated using BAI system and the Rule of Nines. A comparison between these two measuring methods was performed via t-Student test and ICC. The hypothesis of null difference between both measures is only true for deep dermal burns and the ICC is significantly different, indicating that the area estimation calculated by applying classical techniques can result in a wrong diagnose of the burnt surface.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Body Surface Area*
  • Burns / pathology*
  • Child
  • Child, Preschool
  • Computer Graphics*
  • Female
  • Humans
  • Imaging, Three-Dimensional / methods*
  • Infant
  • Male
  • Middle Aged
  • Young Adult