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.
We explored the depth penetration in tissue-mimicking intralipid-based phantoms in SWIR (800-1650 nm) using a hyperspectral imaging system composed from a 2D CCD camera coupled to a microscope. Hyperspectral images in transmission and reflection geometries were collected with a spectral resolution of 5.27 nm and a total acquisition time of 3 minutes or less that minimized artifacts from sample drying. Michelson spatial contrast was used as a metric to evaluate light penetration. Results from both transmission and reflection geometries consistently revealed the highest spatial contrast in the wavelength range of 1300 to 1350 nm.
In order to identify the optimal imaging conditions for the highest spatial contrast in biological tissue, we explored the properties of a tissue-mimicking phantom as a function of the wavelengths in a broad range of near-infrared spectra (650 to 1600 nm). Our customized multispectral hardware, which featured a scanning transmission microscope and imaging spectrographs equipped with silicon and InGaAs charge-coupled diode array detectors, allowed for direct comparison of the Michelson contrast obtained from a phantom composed of a honeycomb grid, Intralipid, and India ink. The measured contrast depended on the size of the grid, luminance, and the wavelength of measurements. We demonstrated that at low thickness of the phantom, a reasonable contrast of the objects can be achieved at any wavelength between 700 and 1400 nm and between 1500 and 1600 nm. At larger thicknesses, such contrast can be achieved mostly between 1200 and 1350 nm. These results suggest that distinguishing biological features in deep tissue and developing contrast agents for in vivo may benefit from imaging in this spectral range.
In order to identify the optimal imaging conditions for the highest contrast in biological tissue, we explored the optical contrast of a phantom as a function of depth and wavelengths of excitation. Our customized optical hardware featured a scanning microscope, and imaging spectrographs equipped with silicon and InGaAs CCD diode array detectors allowed directed comparison of the intensity of NIR (650-900 nm) and exNIR (1000-1600 nm) light transmitted through a phantom (milk). We demonstrated that the contrast depends on the phantom thickness and the wavelength. At low depths (less than 3 mm) NIR light provides the best contrast while exNIR light shows significantly higher contrast in phantoms thicker than 4.5 mm. Our results suggest that distinguishing biological features in deep tissue may benefit from the application of the exNIR for in vivo.
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