A computational method for the investigation of burn scars topology based on 3D optical scan

Comput Biol Med. 2022 Oct:149:105945. doi: 10.1016/j.compbiomed.2022.105945. Epub 2022 Aug 15.

Abstract

Burn scar treatment is a difficult subject to address since the improper therapy can have a significant impact on people's quality of life. The evaluation of medical therapy over time should be based on objective measurement of the severity of burn scars and their progression. Unfortunately, most clinical assessments of scars are still reliant on physicians' subjective exams of patients. A profitable method to overcome the limitations of subjective assessment could be to leverage 3D scanning technologies. These could be used to retrieve the surface topology of burns. Accordingly, the goal of this study is to provide an objective approach for analysing the surface topology of burn scars using 3D scanning and roughness-based evaluation. In particular, two types of ISO-compliant profile and surface filters (Gaussian and Wavelet) derived from the analysis of roughness in the mechanical sector are implemented to discriminate form from roughness of scars. Once retrieved, the roughness surface is processed to derive a set of statistical parameters describing the scar surface topology. Three case studies were used to derive these parameters (a synthetic surface, an ostrich-skin surface and a set of scars). After the surface's roughness was determined, a comparison between healthy and unhealthy skin could be established. The devised methods prove their effectiveness in correctly retrieving the main surface characteristics of a burn scar. Therefore, by using the proposed method it will be possible to evaluate the effectiveness of medical therapy by comparing the healthy and scarred skin of a single subject.

Keywords: 3D scanning; Burn scars; Gaussian filtering; Roughness; Wavelet filtering.

MeSH terms

  • Burns* / diagnostic imaging
  • Burns* / therapy
  • Cicatrix* / diagnostic imaging
  • Humans
  • Quality of Life
  • Skin / diagnostic imaging