Work

Tissue optical properties combined with machine learning enables estimation of articular cartilage composition and functional integrity

Year: 2020

Type: article

Abstract: Absorption and reduced scattering coefficients ( μ a , μ s ′ ) of biological tissues have shown significant potential in biomedical applications. Thus, they are effective parameters for the characterization of tissue integrity and provide vital information on the health of biological tissues. This study investigates the potential of optical properties ( μ a , μ s ′ ) for estimating articular cartilage composition and biomechanical properties using multivariate and machine learning techniques. The results suggest that μ a could optimally estimate cartilage proteoglycan content in the superficial zone, in addition to its equilibrium modulus. While μ s ′ could effectively estimate the proteoglycan content of the middle and deep zones in addition to the instantaneous and dynamic moduli of articular cartilage.

Source: Biomedical Optics Express

DOI: 10.1364/boe.402929

Authors: Iman Kafian-Attari, Ervin Nippolainen, Dmitry Semenov, Markku Hauta-Kasari, Juha Töyräs, Isaac O. Afara

Institutions: University of Eastern Finland, The University of Queensland

Language: English

Topic: Optical Imaging and Spectroscopy Techniques

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,913