Optimized diffusion approximation.

Area of Science:

• Biomedical optics
• Radiative transport theory
• Computational modeling

Background:

• The diffusion approximation (DA) is widely used to model light propagation in biological tissues.
• Conventional DA models have limitations in accuracy, particularly near tissue boundaries.
• An adjustable parameter within the DA has been identified but not fully explored.

Purpose of the Study:

• To investigate a previously unexplored adjustable parameter in the diffusion approximation (DA) for radiative transport.
• To optimize the DA by determining the ideal value for this parameter, termed the reduced extinction coefficient.
• To enhance the accuracy of light propagation modeling in biomedical optics.

Main Methods:

• Identified an adjustable parameter related to the exponential decay rate of reduced intensity in the DA.
• Determined the optimal value for this parameter, the reduced extinction coefficient.
• Compared the accuracy of the optimized DA against conventional DA models near medium boundaries.

Main Results:

• The optimized DA with the reduced extinction coefficient significantly improves accuracy near tissue boundaries (within a few transport mean free paths).
• Relative error in predicted diffuse optical energy density decreased from approximately 30% to less than 1%.
• The enhanced DA extends the applicability of diffusion models for shallow tissue imaging.

Conclusions:

• The introduction of the reduced extinction coefficient optimizes the diffusion approximation for light transport in tissues.
• This optimization substantially increases model accuracy, especially in near-boundary regions.
• The improved DA is beneficial for applications like shallow-layer tomographic imaging in reflection geometry.