When light interacts with tissue, it can be absorbed, scattered or reflected. Such quantitative information can be used to characterize the optical properties of tissue, differentiate tissue types in vivo, and identify normal versus diseased tissue. The purpose of this research is to develop an algorithm that determines the reduced scattering coefficient (μs’) of tissues from a single optical reflectance spectrum with a small source-detector separation.
The basic relationship between μs’ and optical reflectance was developed using Monte Carlo simulations. This produced an analytical equation containing μs’ as a function of reflectance. To experimentally validate this relationship, a 1.3-mm diameter fiber optic probe containing two 400-micron diameter fibers was used to deliver light to and collect light from Intralipid solutions of various concentrations. Simultaneous measurements from optical reflectance and an ISS oximeter were performed to validate the calculated μs’ values determined by the reflectance measurement against the 'gold standard’ ISS readings. The calculated μs’ values deviate from the expected values by approximately ∓ 5% with Intralipid concentrations between 0.5 − 2.5%. The scattering properties within this concentration range are similar to those of in vivo tissues. Additional calculations are performed to determine the scattering properties of rat brain tissues and to discuss accuracy of the algorithm for measured samples with a broad range of the absorption coefficient (μa).
KEYWORDS: Reflectivity, Diffusion, Tissues, Data modeling, Tissue optics, Monte Carlo methods, Signal detection, Geometrical optics, Visible radiation, Near infrared
Theoretical models available for optical reflectance with small source-detector separations are limited. In this study we reported two modified diffusion models for steady-state, broadband (500 - 590 nm) reflectance with source-detector separations of 0.125 - 0.25 mm and 0.25 - 1.0 mm. For the former case, the major modifications are D equals 1/3(mu) s, and z0 equals 1/(mu) s'; for the latter case, an additional modification is to multiply the separation by a factor of 2. Monte Carlo simulations were used to confirm the modified models at three different hemoglobin concentrations with relative errors of 12% or smaller. These models provide the possibility to extract local optical and physiological parameters of blood-perfused tissues from reflectance data measured with a needle-like probe.
During deep brain stimulation, a neurosurgical procedure to relieve tremors, a thin electrode is inserted into deep brain regions to provide stimulation. Accurate electrode placement is crucial to provide tremor suppression without damaging adjacent optical and motor regions. A portable, real-time display fiber optic reflectance probe is used to obtain reflected signals from living, human brain tissues. The optical results are compared to pre-operative MRI scans to confirm anatomical structures and verify electrode placement. In addition to reflectance, tissue oxygen saturation may assist brain tissue identification.
Parkinson's disease is a neuro-degenerative disease affecting the globus pallidus (GP), a deep brain gray matter structure surrounded by white matter. During a pallidotomy a thin radio frequency probe is inserted into the GP to generate a small lesion. A fiber optic reflectance probe was developed and used during surgery. This instrument provides real-time display of the optical reflectance spectra as well as assisted lesion localization. Our 1.5-mm probe contains seven 100-micrometers fibers, one delivers light and six return the reflected light to a spectrometer. During clinical studies, the probe was placed against the surface of the brain and the spectrum between 350 - 850 nm was recorded. Measurements were repeated at 1-mm increments from the surface of the brain to 60-mm deep (GP level). This provided optical reflectance signals from both gray and white matter. Clinical results show that gray matter reflectance is approximately 50% of white matter between 650 - 800 nm. By calculating the slope between 700 - 850 nm, the signals can be differentiated between gray and white matter. We can quantify the absorption and scattering coefficients of the locally measured brain tissue by fitting the two-flu theory of Kubelka and Munk with our measurements.
KEYWORDS: Brain, Reflectivity, In vivo imaging, Tissue optics, Tissues, Monte Carlo methods, Scattering, Absorption, Calibration, Algorithm development
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