Evaluation of a fiberoptic-based system for measurement of optical properties in highly attenuating turbid media

Abstract

Background: Accurate measurements of the optical properties of biological tissue in the ultraviolet A and short visible wavelengths are needed to achieve a quantitative understanding of novel optical diagnostic devices. Currently, there is minimal information on optical property measurement approaches that are appropriate for in vivo measurements in highly absorbing and scattering tissues. We describe a novel fiberoptic-based reflectance system for measurement of optical properties in highly attenuating turbid media and provide an extensive in vitro evaluation of its accuracy. The influence of collecting reflectance at the illumination fiber on estimation accuracy is also investigated.

Methods: A neural network algorithm and reflectance distributions from Monte Carlo simulations were used to generate predictive models based on the two geometries. Absolute measurements of diffuse reflectance were enabled through calibration of the reflectance system. Spatially-resolved reflectance distributions were measured in tissue phantoms at 405 nm for absorption coefficients (mu(a)) from 1 to 25 cm-1 and reduced scattering coefficients (mu'(s)) from 5 to 25 cm-1. These data and predictive models were used to estimate the optical properties of tissue-simulating phantoms.

Results: By comparing predicted and known optical properties, the average errors for mu(a) and mu'(s) were found to be 3.0% and 4.6%, respectively, for a linear probe approach. When bifurcated probe data was included and samples with mu(a) values less than 5 cm-1 were excluded, predictive errors for mu(a) and mu'(s) were further reduced to 1.8% and 3.5%.

Conclusion: Improvements in system design have led to significant reductions in optical property estimation error. While the incorporation of a bifurcated illumination fiber shows promise for improving the accuracy of mu's estimates, further study of this approach is needed to elucidate the source of discrepancies between measurements and simulation results at low mu(a) values.

Figure 1

System Diagram. Diagram includes (a) experimental setup and (b) fiberoptic probe face.

Figure 2

Reduction of detected signal range. Monte Carlo simulations and experimental data for μ_a = 25 cm^-1, μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@ = 15 cm^-1. The signal range in the experimental data was reduced by using neutral density filters to preferentially attenuate the channels closest to the source fiber.

Figure 3

Diagram of bifurcated probe. A bifurcated fiberoptic probe was used to measure reflectance at the illumination site.

Figure 4

Comparison of experimental and simulated reflectance with linear array probe. These graphs present absolute diffuse reflectance data as determined by experimental measurements (filled shapes) and Monte Carlo simulations (open shapes). Graph (a) shows the effect of μ_a on reflectance when μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@ is held constant at 15 cm^-1, whereas (b) shows the effect of μ_s on the reflectance when μ_a is held constant at 15 cm^-1.

Figure 5

Accuracy of optical property estimates with linear array probe. These graphs present results for estimates of (a) μ_a and (b) μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@. Each of the 60 points represents the difference between predicted and true values.

Figure 6

Accuracy of diffuse reflectance measurements with bifurcated probe. This graph provides a comparison of simulated (open shapes) and measured (filled shapes) diffuse reflectance for the bifurcated probe. Squares represent the effect of variations in μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@ (for a constant μ_a = 15 cm^-1). Circles represent the effect of μ_a (for a constant μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@ = 15 cm^-1).

Figure 7

Accuracy of optical property estimates with combined linear-bifurcated probe. These graphs present results for estimates of (a) μ_a and (b) μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@. Each of the 60 data points represents the difference between predicted and true optical property values.