title: Penetration depth of photons in biological tissues from hyperspectral imaging in shortwave infrared in transmission and reflection geometries.
abstract: Measurement of photon penetration in biological tissues is a central theme in optical imaging. A great number of endogenous tissue factors such as absorption, scattering, and anisotropy affect the path of photons in tissue, making it difficult to predict the penetration depth at different wavelengths. Traditional studies evaluating photon penetration at different wavelengths are focused on tissue spectroscopy that does not take into account the heterogeneity within the sample. This is especially critical in shortwave infrared where the individual vibration-based absorption properties of the tissue molecules are affected by nearby tissue components. We have explored the depth penetration in biological tissues from 900 to 1650 nm using Monte–Carlo simulation and a hyperspectral imaging system with Michelson spatial contrast as a metric of light penetration. Chromatic aberration-free hyperspectral images in transmission and reflection geometries were collected with a spectral resolution of 5.27 nm and a total acquisition time of 3 min. Relatively short recording time minimized artifacts from sample drying. Results from both transmission and reflection geometries consistently revealed that the highest spatial contrast in the wavelength range for deep tissue lies within 1300 to 1375 nm; however, in heavily pigmented tissue such as the liver, the range 1550 to 1600 nm is also prominent.
authors.affiliation: Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States.
authors.forename: Hairong
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States.
authors.forename: Daniel
authors.initials: D
authors.lastname: Salo
authors.affiliation: Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States.
authors.forename: David M
authors.initials: DM
authors.lastname: Kim
authors.affiliation: Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States.
authors.forename: Sergey
authors.initials: S
authors.lastname: Komarov
authors.affiliation: Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States.
authors.forename: Yuan-Chuan
authors.initials: YC
authors.lastname: Tai
authors.affiliation: Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States.
authors.forename: Mikhail Y
authors.initials: MY
authors.lastname: Berezin
mesh_terms: D000818:Animals; D002645:Chickens; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000000981:diagnostic imaging; D008954:Models, Biological; D009010:Monte Carlo Method; D009132:Muscles / Q000000981:diagnostic imaging; D019047:Phantoms, Imaging; D017785:Photons; D019265:Spectroscopy, Near-Infrared / Q000379:methods*