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

Summary, in English

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.

• Author: Ulf Dahlstrand; Rafi Sheikh; Cu Dybelius Ansson; Khashayar Memarzadeh; Nina Reistad; Malin Malmsjö
• Department/s: Ophthalmology Imaging Research Group; Ophthalmology, Lund; Atomic Physics; NPWT technology
• Publishing year: 2019
• Language: English
• Publication/Series: PLoS ONE
• Volume: 14
• Issue: 10
• Links: http://dx.doi.org/10.1371/journal.pone.0223682
• Document type: Journal article
• Publisher: Public Library of Science (PLoS)
• Topic: Biomedical Laboratory Science/Technology; Atom and Molecular Physics and Optics
• Status: Published
• Research group: Ophthalmology Imaging Research Group; NPWT technology
• ISBN/ISSN/Other: ISSN: 1932-6203