Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification

PLoS One. 2019 Oct 10;14(10):e0223682. doi: 10.1371/journal.pone.0223682. eCollection 2019.

Abstract

Objectives: An extended-wavelength diffuse reflectance spectroscopy (EWDRS) technique was evaluated for its ability to differentiate between and classify different skin and tissue types in an in vivo pig model.

Materials and methods: EWDRS recordings (450-1550 nm) were made on skin with different degrees of pigmentation as well as on the pig snout and tongue. The recordings were used to train a support vector machine to identify and classify the different skin and tissue types.

Results: The resulting EWDRS curves for each skin and tissue type had a unique profile. The support vector machine was able to classify each skin and tissue type with an overall accuracy of 98.2%. The sensitivity and specificity were between 96.4 and 100.0% for all skin and tissue types.

Conclusion: EWDRS can be used in vivo to differentiate between different skin and tissue types with good accuracy. Further development of the technique may potentially lead to a novel diagnostic tool for e.g. non-invasive tumor margin delineation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Machine Learning*
  • Organ Specificity*
  • Principal Component Analysis
  • Spectrum Analysis*
  • Swine

Grants and funding

This study was supported by the Swedish Government Grant for Clinical Research (2018-0188; MM), Skåne University Hospital (SUS) Research Grants (2018-310; MM), Skåne County Council Research Grants, Lund University Grant for Research Infrastructure (MM), the Swedish Cancer Foundation Crown Princess Margaret's Foundation (KMA103; MM), the Foundation for the Visually Impaired in the County of Malmöhus (MM), The Nordmark Foundation for Eye Diseases at Skåne University Hospital (MM), Lund Laser Center Research Grant (MM), IngaBritt and Arne Lundberg Research Foundation (2017-0014; MM), Carmen and Bertil Regnér Foundation (2018-00036; RS) and the Swedish Eye Foundation (MM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.