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

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.