Plastic and Reconstructive Surgery, Global Open (Jun 2024)

Application to Quantify Ulcer Areas and Track Their Progress

  • Kazufumi Tachi, MD, PhD,
  • Koichi Gonda, MD, PhD

DOI
https://doi.org/10.1097/GOX.0000000000005922
Journal volume & issue
Vol. 12, no. 6
p. e5922

Abstract

Read online

Summary:. Chronic ulcer treatments, such as those for diabetic foot ulcers and pressure sores, require prolonged treatment periods. Availability of effective objective indicators to determine treatment method efficacy is limited. Ulcer area is the agreed-upon indicator for ulcer healing because it contracts and/or undergoes epithelialization as healing occurs. Ulcer surface properties such as healthy or infected granulation and slough or necrotic tissue are also used. This study aimed to develop a user-friendly application automating the ulcer area measurement process and included a graphical time-series display of ulcer components manually classified by users. Images of ulcers photographed with adjacent circular 1.5-cm diameter stickers were prepared. In the application, users manually categorized and color-coded each image into five component types based on different ulcer characteristics. The application calculated the area of each component in pixels and then estimated the actual area using the sticker area as a reference. It also collated color-coded images and presented graphical illustrations of changes in area over time. The results indicated the application successfully automated area measurements of each ulcer component and graphical displays of changes in ulcer component areas over time. It enabled users to visually track quality changes and the chronic ulcer healing process. Historically, ulcer assessments are subjectively conducted via visual examination by physicians, creating less reproducible, objective data. Although ulcer properties still required manual entry by users, our application streamlined ulcer area measurement and time-course visualization and sets the groundwork for a fully automated artificial-intelligence–driven ulcer diagnosis system.